Author: Guy Kawasaki’s Remarkable People

  • Duncan Wardle: Disney’s Creative Genius

    Duncan Wardle: Disney’s Creative Genius

    AI transcript
    0:00:11 The most successful social video I ever produced for Disney, and it was still the most successful one we ever produced, was because I refused to go through the approval process, which was, I’m sure if it had gone wrong, I’m sure I’d have been fired.
    0:00:13 But sometimes you have to stand up in what you believe for.
    0:00:18 I loved Disney because if you had a big idea, somebody would fund it for you.
    0:00:30 I have to say that of the 260 guests we’ve had on this podcast, you have by far the best background behind you.
    0:00:35 And it’s real, it’s drawn, it’s painted, so it’s not one of those fake backgrounds.
    0:00:38 I worked for this guy for 30 years.
    0:00:44 I finished as Head of Innovation and Creativity at Disney, Pixar, Lucasfilms, Marvel, but it didn’t start that way.
    0:00:46 I started as a coffee boy in the London office.
    0:00:49 I used to go and get my boss six cappuccinos a day from a bar at Tannehill, First Street.
    0:00:54 And about three weeks into the role, I was told I would be the character coordinator at the Royal,
    0:00:58 that’s the person that looks after the characters that walk around, at the Royal Premier of Who Frames Roger Rabbit,
    0:01:01 in the presence of the Princess of Wales.
    0:01:02 Diana was like, what do I do?
    0:01:05 They said, well, you stand at the bottom of the stairs, Roger Rabbit will come down the stairs,
    0:01:09 the princess will come in along the receiving line, she’ll greet him or she’ll blow him off.
    0:01:12 How could you possibly screw that up?
    0:01:14 Well, that was the day when I found out what a contingency plan was.
    0:01:19 A contingency plan would tell you if you’ve got to bring a very tall rabbit with spectacularly long feet
    0:01:24 down a giant staircase towards the princess of Wales, you might want to measure the width of the steps first.
    0:01:25 So I hadn’t.
    0:01:29 Roger trips on the top step and he’s now hurtling like a bullet, head and feet,
    0:01:34 directly down the stairs towards Diana’s head, whereupon he was met in midair by two Royal Protection officers
    0:01:35 who just took him out.
    0:01:38 There’s a very famous picture of Reuters of Roger going back like this,
    0:01:40 two Secret Service heavies diving towards him in a suit,
    0:01:44 and a 21-year-old PR guy from Disney in the back going, ah, shit, I’m fired.
    0:01:49 So I got a call the next day from a place called Burbank, which I’d never heard of,
    0:01:53 from somebody called a CMO, didn’t know what they were either, I thought I was going to tell him I’m fired.
    0:01:59 And all I heard was, that was great publicity, was that I can make a career out of this.
    0:02:06 And so basically for 20 years at Disney I did, I got to have some of the more mad, audacious, outrageous ideas.
    0:02:07 That’s kind of what I did.
    0:02:16 Well, Madison, I think that that was probably the best start of a podcast in the history.
    0:02:17 They’re remarkable people.
    0:02:21 Usually, Duncan, we like to introduce the guests, but, you know,
    0:02:26 we’ve got to get out of that box and let the guests tell their own story.
    0:02:30 When people ask me to, they want me to read my bio when I get up on the stage
    0:02:32 and was like, do you remember the Charlie Brown cartoons?
    0:02:33 You remember the principle?
    0:02:37 Wah, wah, wah, wah, wah, don’t read the bio, please don’t.
    0:02:39 So I always do two truths of the lie.
    0:02:41 And the funny thing is, when you get off the stage, you think,
    0:02:44 ah, this person’s coming up to me, they’re going to ask me a really important question.
    0:02:47 They go, oh, they just want to know which one was the lie.
    0:02:56 Okay, so clearly we are not going to do a tradition or introductions.
    0:03:04 So, you know, I have to ask you this dumb question, but man, what was it like to work at Disney?
    0:03:10 I mean, was it like being the Super Bowl MVP and every year you go to Disneyland?
    0:03:12 What was it like?
    0:03:14 I hosted pretty much all of those guys.
    0:03:17 My job was, this was in the days before contracts.
    0:03:21 So you literally, at the end of the game, you had to get onto the field at the end of the game,
    0:03:25 grab the MVP, but everybody else was yanking your cameras,
    0:03:26 and throwing them all over the place.
    0:03:30 So your job was just get to the MVP, get the line up, go to Disney World,
    0:03:33 get them on the corporate jet and fly them down to Disney World.
    0:03:38 That sounds easy, but there’s the MVP who doesn’t want to go with you.
    0:03:39 They want to go drinking somewhere.
    0:03:42 So I got separated on the field from my cameraman.
    0:03:44 And he comes on the radio and goes, where are you?
    0:03:46 I said, I’m on the pitch at the halfway line.
    0:03:49 And somebody else goes, I think he means he’s on the field at the 50-yard line.
    0:03:55 So I worked for, basically for, I suppose, 50% of my career was with Michael Eisner,
    0:03:57 50% with Bob Iger.
    0:04:01 But Roy Disney was still there all the time, and I loved Roy and John Lasseter.
    0:04:06 They were the old school, but the old school were just, they had less corporations.
    0:04:08 We’ve got so tight and tidy and pretty now.
    0:04:10 I think they pushed boundaries more.
    0:04:13 I admired them both because they broke the rules.
    0:04:17 The most successful social video I ever produced for Disney, and it was still the most successful
    0:04:22 one we ever produced, was because I refused to go through the approval process, which was,
    0:04:24 I’m sure if it had gone wrong, I’m sure I’d have been fired.
    0:04:26 But sometimes you have to stand up in what you believe for.
    0:04:32 I loved Disney because if you had a big idea, somebody would fund it for you.
    0:04:35 And I loved working for Michael in particular, because every time he walked in the door,
    0:04:38 he was always respectful and very courteous, but he’d say, you know what?
    0:04:40 We’re the world’s number one entertainment company.
    0:04:42 Come back when you’ve got something that scares me.
    0:04:43 Come on, all right, bring it.
    0:04:44 And so it was great.
    0:04:50 And working with Bob was also fascinating because here comes Pixar, Marvel, Lucasfilms, ESPN,
    0:04:56 ABC, and suddenly you’ve got all these cultures who are very unique, who, but the challenge
    0:04:58 was everybody was better than everybody else.
    0:05:03 So the task that Bob gave me was how might we embed a culture of innovation and creativity
    0:05:04 into everybody’s DNA?
    0:05:08 So the first thing I did was hire somebody else who knew what they were doing.
    0:05:10 I said, make me look good.
    0:05:11 They were a consultant.
    0:05:14 They were never around for execution, but they were never going to show me how they did what
    0:05:16 they did, or they were frightened I wouldn’t hire them again.
    0:05:19 Model number two, I’ll be in charge of innovation and creativity.
    0:05:20 What could possibly go wrong?
    0:05:23 Well, it’s kind of like having a legal team or a marketing team or a sales team.
    0:05:26 When you have an innovation team, you’ve kind of told everybody else you’re off the hook.
    0:05:27 So that model failed.
    0:05:32 The accelerator program, we bring in some young tech startups and take a 50-50 stake in their
    0:05:32 business.
    0:05:34 For them, we could scale.
    0:05:35 That’s what Disney does.
    0:05:38 For them, they could help us bring products and services to market much quicker than we normally did.
    0:05:43 But we’d failed in Bob’s overall goal, which was, how might we embed a culture of innovation
    0:05:45 and creativity into everybody’s DNA?
    0:05:50 And so I asked 5,000 people, I said, what were the biggest barriers to being more innovative
    0:05:51 and creative where you work?
    0:05:53 Number one, don’t have time to think.
    0:05:55 Number two, we don’t have the resources.
    0:05:59 Number three, we say we’re consumer and client-centric, but we measure by quality results.
    0:06:03 Number four, our ideas seem to get stuck, diluted or killed as they move through approval
    0:06:03 process.
    0:06:06 And number five, we all had a very different definition of creativity.
    0:06:09 So I set out to create a toolkit that has three principles.
    0:06:13 Takes the BS out of innovation and makes it more accessible to normal, hardworking people.
    0:06:17 Makes creativity tangible for people who are uncomfortable with ambiguity and great.
    0:06:19 Far more importantly, make it fun.
    0:06:22 Give people tools they choose to use when you and I are not around.
    0:06:24 So I was with Disney for 30 years.
    0:06:28 I got the Jiminy Cricket, thank you, for 30 magical years of service bronze.
    0:06:31 And I looked at it and I thought, shit, I’m nearly dead.
    0:06:33 I’ve got to do something else.
    0:06:37 So I left and I went home to England for a while and sat in the pub and felt sorry for
    0:06:37 myself.
    0:06:39 I thought, OK, what do I do now?
    0:06:41 And somebody said, could you come and give a speech?
    0:06:41 Sure.
    0:06:43 And it just took off.
    0:06:46 But see, I am the antithesis of so many other people.
    0:06:49 The word, the creative, drives me nuts.
    0:06:50 I’m sorry, it just does.
    0:06:53 I know some people are better at writing stories.
    0:06:55 Some people are better at writing music.
    0:06:56 Some people are better at acting.
    0:06:58 I believe everybody’s creative.
    0:07:02 When you were a kid and you were given a gift for Christmas, it came in a huge box.
    0:07:04 It took you ages to take the toy out of the box.
    0:07:05 What do you spend the rest of the week playing with?
    0:07:06 The box.
    0:07:07 It was your rocket ship.
    0:07:07 It was your force.
    0:07:08 It was your creative.
    0:07:09 But here’s the challenge.
    0:07:11 Here comes AI.
    0:07:14 And I was working with the engineer on their DeepMind project.
    0:07:18 And I asked her, I said, how am I going to compete with what you do and what you’re
    0:07:18 creating?
    0:07:23 She said, well, she believed the most employable skill sets of the near term will be the ones that
    0:07:25 will be the hardest for her to program into AI.
    0:07:26 What are they?
    0:07:28 Well, the ones with which we’re born.
    0:07:29 We’re born with imagination.
    0:07:30 We’re born creative.
    0:07:31 We’re born curious.
    0:07:32 We used to ask why, why, why again.
    0:07:35 We’re born with MP and we’re born with intuition.
    0:07:36 Will they be programmed one day?
    0:07:37 I don’t know the answer.
    0:07:39 But in the short term, probably not.
    0:07:41 But the problem is that we go to school.
    0:07:44 And the first thing our first grade teacher tells us to do is don’t forget to cover in
    0:07:44 between the lines.
    0:07:47 And then they say, stop asking why because there’s only one right answer.
    0:07:49 So I did a talk at a university.
    0:07:51 I had 3,000 students at university age.
    0:07:55 So I brought in one first grade class of 30 little six-year-olds and sat them in the middle
    0:07:56 with their teacher.
    0:07:57 I said, hands up here.
    0:07:57 Who’s creative?
    0:07:58 Me, me, me, me, me, me, me.
    0:08:00 A 30 little hand shot into the air.
    0:08:02 The other 3,000 stayed down.
    0:08:05 We are taught that we are not creative.
    0:08:07 By the time we’re 18, most people have given up.
    0:08:11 And yet here comes AI, which would doubtless take away many roles but create new ones.
    0:08:13 But what have we got left?
    0:08:15 I genuinely believe the things with which we were born.
    0:08:23 Duncan, has anybody ever told you that you need to come out of your shell and learn to
    0:08:24 express yourself?
    0:08:27 And I haven’t had a drink yet.
    0:08:35 If you don’t mind, I’d like to ask a few questions in my podcast.
    0:08:48 So I want to hear about the philosophical impact of Disney calling people guests, not customers.
    0:08:49 What’s behind that?
    0:08:51 There’s a tool I call HowElse.
    0:08:53 How by simply reframing a challenge?
    0:08:57 Can you get people to stop thinking the way they always do and give them permission to think
    0:08:57 differently?
    0:09:00 So we’ll try and experiment and then I’ll answer your question.
    0:09:01 Where do you live, by the way?
    0:09:03 I live in Watsonville, California.
    0:09:08 So if I was coming to Watsonville and you and I were going to open a car wash together,
    0:09:12 tell me if you would, what are the three essential ingredients, three or four things we must have
    0:09:12 in a car wash?
    0:09:15 I would say good Wi-Fi is number one.
    0:09:16 Wi-Fi.
    0:09:16 All right.
    0:09:22 And then obviously you have to have the car really clean.
    0:09:22 Yeah.
    0:09:26 And I would say the third thing is that…
    0:09:27 Well, the essential ingredients.
    0:09:33 The essential ingredients is your car comes out clean and then while you’re waiting for it,
    0:09:34 you’re somewhat entertained.
    0:09:37 And I would say that’s about it.
    0:09:39 Well, maybe there’s a third.
    0:09:45 The third one would be that I hope that the water and the resources are being effectively
    0:09:46 recycled.
    0:09:47 We’re just not polluting.
    0:09:48 Okay.
    0:09:50 So now you’re an high venture capitalist.
    0:09:53 We’ve been invited to open a new franchise of auto spas.
    0:09:55 Who are a spa?
    0:09:56 What have you seen in a spa?
    0:09:58 What would you like to see in your auto spa?
    0:09:58 Anything you want.
    0:10:00 What would you love to have in your auto spa?
    0:10:07 So I think what you’re trying to say is that if you define it as car wash, you think of
    0:10:09 just the rollers and the sprays.
    0:10:13 But if you say auto spa, you think of manicure, pedicure, massage.
    0:10:16 You think of like hippie music.
    0:10:18 You think of relaxation.
    0:10:19 You think of zen.
    0:10:21 You’re not thinking of…
    0:10:22 And that’s exactly how Walt used the tool.
    0:10:23 Just getting your toenails cut.
    0:10:27 Yeah, that’s exactly how Walt used the tool.
    0:10:32 He said, look, July 17th, 1955, when he opened the doors to Disneyland, which has come out
    0:10:34 for a 70th in a couple of months.
    0:10:35 Now I feel old.
    0:10:38 He said, we will not have any customers in our park.
    0:10:39 We will only have guests.
    0:10:40 We will not have any employees.
    0:10:41 We’ll only have cast members.
    0:10:43 They’ll be cast for a role in the show.
    0:10:45 They’ll wear a costume, not a uniform.
    0:10:46 They’ll work on stage, not backstage.
    0:10:51 With that simple re-expression of the relationship between the employee and the customer as the
    0:10:55 cast member and the guest, Walter created a culture of hospitality that’s rarely
    0:10:56 been repeated elsewhere.
    0:11:00 So now, fast forward, how is it actually used in business today?
    0:11:04 In 2011, if we’d asked the question, how might we make more money, we’d have put the
    0:11:05 gate price up at Walt Disney World.
    0:11:06 People would have complained.
    0:11:06 They’d have still come.
    0:11:08 We’d have made our quarterly results.
    0:11:10 You don’t get to iterate in a post-pandemic world.
    0:11:13 So instead of saying, how might we make more money, we reversed the challenge and said,
    0:11:16 how might we solve the biggest consumer pain point?
    0:11:17 Everybody knew what it was.
    0:11:18 It was called standing in line.
    0:11:20 And I said, well, what if there were no lines?
    0:11:21 Didn’t know how to do it.
    0:11:23 Again, if you know how to do it, you’re iterating.
    0:11:24 If it scares you a bit, you’re innovating.
    0:11:27 So we used another tool, which is about looking outside.
    0:11:31 I believe a lot of the insights for innovation come from looking outside of your industry.
    0:11:36 And we found a very small pharmacy in Tokyo, Japan, that used RFID technology to enable
    0:11:38 people not to stand in line when they came to pick up their prescriptions.
    0:11:39 Bing!
    0:11:41 Welcome to the World of Disney’s Magic Band.
    0:11:42 I’m not wearing one today.
    0:11:42 Oh, wait a minute.
    0:11:43 Yes, I am.
    0:11:43 Here we go.
    0:11:46 Do they come in red or grey in the mail?
    0:11:47 Yes, of course they do.
    0:11:47 Why?
    0:11:49 Because you’ll look great to the Star Wars edition or the Mickey Jedi edition.
    0:11:51 Does it come in matching merchandise?
    0:11:52 Of course it does.
    0:11:53 This is my room key.
    0:11:55 I don’t check in or check out of a Disney resort today.
    0:11:56 It’s my theme park ticket.
    0:11:57 The turnstiles are gone.
    0:12:00 My reservations for my favourite character meet and greets, my favourite rides.
    0:12:01 I can pay for food with it.
    0:12:03 I can pay for merchandise with it.
    0:12:07 I walk into the restaurant when I want to walk in and the food comes fresh to me.
    0:12:11 Had we started by saying how might we make more money, we’d have made a 3% profit margin.
    0:12:16 But by reversing the challenge and saying how might we solve the biggest consumer pain point,
    0:12:20 the average guest at Walt Disney World today has over two hours free time they didn’t have
    0:12:21 each and every day six years ago.
    0:12:22 What has that resulted in?
    0:12:23 Record intent to recommend.
    0:12:25 Record intent to return.
    0:12:28 And what is it you lovely people do with your free time at Disney e-books?
    0:12:30 Spend money.
    0:12:33 One of the biggest single revenue generating ideas Disney ever created.
    0:12:36 And what’s the consumer doing every second of every day?
    0:12:40 They’re crowdsourcing the future of every product and service Disney creates by telling
    0:12:41 what they like and what they don’t.
    0:12:43 And it comes in themed merchandise.
    0:12:49 I swear, I have my list of questions and I was going to ask you about this wristband case.
    0:12:55 So is this something that if you go back, it was like somebody in innovation thought of it
    0:13:00 or was it security thought of it or the hotel lobby staff thought of it?
    0:13:02 Like what was the genesis of this?
    0:13:06 Well, the genesis was how might we stop people from standing in line?
    0:13:08 When you’re hosting 25 million guests a year, that’s going to be tricky.
    0:13:12 And so we looked in the theme park industry, but nobody was solving the issue.
    0:13:17 So this tool is about where in the world has somebody already solved the challenge of people
    0:13:18 not standing in line?
    0:13:21 So you look outside of your industry and borrow about the underlying principle.
    0:13:23 And that’s how we found the pharmacy.
    0:13:27 But I will tell you there’s another story, not specific, not pertain to the magic band,
    0:13:29 but it is all about I love Ed Catnall.
    0:13:31 He always said creativity doesn’t follow job titles.
    0:13:32 It just comes from where it comes from.
    0:13:34 I love the naive expert.
    0:13:35 Actually, do you have a pen and a piece of paper?
    0:13:37 Yes, I do.
    0:13:37 Good.
    0:13:38 All right.
    0:13:38 Come on then.
    0:13:41 So the naive expert, who or what is a naive expert?
    0:13:44 They are somebody who doesn’t know what you’re working on.
    0:13:46 What does that give them permission to do that you can’t?
    0:13:49 Well, they can ask the silly question you’re too embarrassed to ask in front of your colleagues.
    0:13:53 They can throw out the audacious idea ungoverned by your river of thinking.
    0:13:55 I define our river of thinking.
    0:13:59 And the more experience, the more expertise we have, the more reasons we know why the new
    0:14:00 idea won’t work.
    0:14:01 So we constantly shoot it down.
    0:14:03 So I was bringing a naive expert.
    0:14:08 We were designing a new retail dining and entertainment complex for Hong Kong Disney in the room that
    0:14:10 day with the Disney Imagineers, the people you would expect.
    0:14:14 But on that particular day, I was faced with 12 white male American architects over 50.
    0:14:16 So I brought in a young girl from China.
    0:14:16 Why?
    0:14:18 She was female, not male, under 20.
    0:14:20 This is the dim sum girl.
    0:14:20 Right.
    0:14:21 Exactly right.
    0:14:22 So hang on.
    0:14:24 So I gave them the same challenge I’m going to give you now then.
    0:14:26 So I’ll give you seven seconds to draw a house.
    0:14:27 Go.
    0:14:27 Come on.
    0:14:28 Seven.
    0:14:29 Come on.
    0:14:29 Draw that house, guy.
    0:14:30 Come on.
    0:14:31 Seven.
    0:14:31 Six.
    0:14:32 Five.
    0:14:33 Four.
    0:14:34 Three.
    0:14:34 Two.
    0:14:34 One.
    0:14:35 Here’s the thing.
    0:14:39 See, if you’d drawn it, I know it’s going to look like this.
    0:14:39 So here’s the thing.
    0:14:43 Everybody drew this except the young female Chinese chef.
    0:14:43 She drew.
    0:14:45 Let’s see if I’ve got a picture of it over here.
    0:14:46 Let’s see.
    0:14:48 Oh, here we go.
    0:14:50 She gave dim sum architecture.
    0:14:50 Why wouldn’t she?
    0:14:52 She’s a young female Chinese chef.
    0:14:54 Never occurred to her to draw the house the same way we would.
    0:14:58 On the way out the door, somebody put a post-it note over her drawing that simply said,
    0:15:00 distinctly Disney, authentically Chinese.
    0:15:05 Seven years later, the strategic brand position, the guy did the entire design of the Shanghai
    0:15:06 Disney Resort.
    0:15:08 Distinctly Disney, authentically Chinese.
    0:15:11 The point is this, and companies don’t understand it.
    0:15:13 Diversity is innovation.
    0:15:16 If somebody doesn’t look like you, they don’t think like you.
    0:15:18 And that, shockingly enough, they can help you think differently.
    0:15:21 And I believe that sometimes we get leadership meeting.
    0:15:24 Well, for goodness sake, inviting somebody who’s not a leader.
    0:15:29 Some young 28 superstar who’s been on touchscreen technology since the day they were born.
    0:15:31 Virtual reality since the day they were five.
    0:15:34 And they’ve been on ChatGPT for a year longer than any of us.
    0:15:35 But we don’t.
    0:15:37 Because why do we do leaders and leaders?
    0:15:38 Because that’s the way we’ve always done it here.
    0:15:40 Maybe think about it differently.
    0:16:01 I see a lot of companies where there’s like a chief innovation officer.
    0:16:03 There’s a department of innovation.
    0:16:06 There’s R&D specifically tasked with innovation.
    0:16:11 But should everybody in the company be thinking creatively in innovation?
    0:16:11 Yes.
    0:16:15 Or just these people who are supposed to be tasked with this?
    0:16:16 The creatives.
    0:16:17 Oh, give me a break.
    0:16:18 There was a lady.
    0:16:19 I won’t go through the whole story.
    0:16:25 So we were doing a strategic pricing session surrounded by the EVPs, the SVPs, and the gods
    0:16:26 from Mount Olympus had joined us for a day.
    0:16:28 So how might we make more money?
    0:16:32 And they were all strategists and future planners and accountants and finance.
    0:16:33 So I invited in Maggie.
    0:16:34 Well, who’s Maggie?
    0:16:37 Maggie was a 78-year-old cast member from our call centre.
    0:16:40 Now, why would I invite Maggie into a strategic pricing session?
    0:16:41 Let me think.
    0:16:44 She spends eight hours a day talking to our guests at the call centre.
    0:16:45 We don’t.
    0:16:47 So we were just chatting during the lunch break.
    0:16:49 And I said to her, I said, Maggie, why do you do this?
    0:16:50 You’re 78.
    0:16:51 You should be retired.
    0:16:52 She goes, well, no, dear.
    0:16:53 My husband passed away a few years ago.
    0:16:54 And this keeps me company.
    0:16:56 And I like making people happy.
    0:16:57 I was like, oh, you lovely person.
    0:17:00 I said, if you don’t mind my asking, what do you not like about your job?
    0:17:01 She goes, oh, that’s easy, dear.
    0:17:02 My boss.
    0:17:04 I said, hang on a minute.
    0:17:05 Why don’t you like your boss?
    0:17:06 She goes, he makes me get off the phone.
    0:17:08 It’s obvious she’s there for the gossip and the chat.
    0:17:12 I said, if you don’t mind my asking, how many people do you book in a shift?
    0:17:17 She goes, for every 20 calls I get, I’ll probably book a, convert one, one of those phone calls
    0:17:18 to a Walt Disney World vacation.
    0:17:19 I said, is that good or bad?
    0:17:20 I don’t know how to think about it.
    0:17:23 She goes, I reckon I could get three or four out of 20 if people would trust me.
    0:17:24 Maggie, you’re a grandmother.
    0:17:25 Everyone trusts me.
    0:17:27 You work for the most trusted brand on the planet.
    0:17:28 She goes, no, dear, they don’t.
    0:17:29 I said, why not?
    0:17:31 She says, oh, we’ve got this policy called guest request and suggest.
    0:17:33 I said, oh, God, who came up with that title?
    0:17:34 So I said, what’s that?
    0:17:39 She said, if the consumer is online, and let’s say it’s the Valentine’s Day offer, let’s say
    0:17:43 you have to travel, book in January, travel in February, you get a free character breakfast
    0:17:44 with Anna and Elsa.
    0:17:48 She said, if the consumer doesn’t mention that offer in those three specific bullet points
    0:17:50 first, I’m not allowed to mention it.
    0:17:51 My intuition was like, ah, that sounds good.
    0:17:55 So I went off to meet the head of strategic pricing, and yes, I should have been a bit
    0:17:56 more diplomatic in my response.
    0:17:59 I said, tell me about guest requests, don’t suggest.
    0:18:02 And he said, it’s worth X million dollars in incremental revenue.
    0:18:03 And I said, what, by cheating people?
    0:18:04 Probably didn’t come quite out the right way.
    0:18:06 And he said, we’re not cheating people.
    0:18:07 We just don’t make the offer first.
    0:18:11 I said, listen, Maggie here reckons she could get three or four out of 20 if we take her out
    0:18:12 of your policy.
    0:18:16 Could you think we could take her and six of her colleagues out of your policy for six weeks
    0:18:17 to see how they perform?
    0:18:20 Six weeks later, they were all booking three or four out of 20.
    0:18:24 The policy went away, and Disney made X amount of dollars in incremental revenue.
    0:18:28 I am a great believer that ideas come from anywhere.
    0:18:30 I was head of the innovation department.
    0:18:31 I think that was a mistake.
    0:18:40 Well, you know, you spend a lot of time in your book talking about no, because, as opposed
    0:18:41 to yes, and.
    0:18:46 So now, I understand the concept there, but can you just tell us, how do you walk the fine
    0:18:49 line, because you cannot say yes to everything?
    0:18:51 You cannot say no to everything either.
    0:18:54 So how do you decide what’s yes or no?
    0:18:55 I’m very clear in my signaling.
    0:18:57 I say, this is an expansionist session today.
    0:19:00 We will be having a reductionist session, but today we’re expansionist.
    0:19:03 And in this session, you don’t get to say no because.
    0:19:05 And I don’t let people say no because.
    0:19:08 I’ll make them stand up just like an alcoholic and say, I’m a reductionist.
    0:19:09 And we all laugh and cheer, and they sit back down again.
    0:19:13 You must clearly signal what you’re looking for from people today.
    0:19:18 As long as they know they’ll have the opportunity to evaluate the ideas later on, they’ll stay
    0:19:19 with you on the yes end.
    0:19:21 I also think a physical room is very important.
    0:19:23 Steve created it first at Pixar.
    0:19:28 These rooms like the greenhouse or the Toy Story room, rather than room 3450.
    0:19:29 I mean, come on.
    0:19:30 You could have the Death Star room.
    0:19:35 And these physical signals to everybody that when we’re in this room, we don’t get to shoot
    0:19:36 ideas down.
    0:19:40 The challenge for all of us is the more experience and the more expertise we have, the more reasons
    0:19:41 we know why the new idea won’t work.
    0:19:43 So we constantly shoot it down.
    0:19:47 So I actually have an exercise that I do when I actually, do you want to play?
    0:19:47 Why not?
    0:19:51 OK, so are we going to do a Star Wars party or a Harry Potter party?
    0:19:52 What would you prefer?
    0:19:53 Star Wars.
    0:19:53 All right.
    0:19:55 So I’m going to come at you with some ideas for a Star Wars party.
    0:19:59 I’d like you to start each and every response with the words, you know, you’ve heard every
    0:19:59 day.
    0:20:00 No, because.
    0:20:02 And then you’ll tell me no because and tell me why not.
    0:20:05 So I was thinking we could actually take over some.
    0:20:08 Oh, that the new blimp, the Goodyear, they’re coming out with that new blimp again.
    0:20:12 And we could turn it into the Death Star and we could have a Death Star canteen with food
    0:20:13 and wine from Hoth and Naboo and Tatooine.
    0:20:17 And now I’m supposed to say no because and come up with a reason.
    0:20:18 No because and tell me why not.
    0:20:18 Yeah.
    0:20:19 OK.
    0:20:22 No, because the blimp cannot hold that many people.
    0:20:25 People will be waiting for hours in line to get on the blimp.
    0:20:26 All right.
    0:20:30 But I tell you what, then we do it at Disneyland at Galaxy’s Edge and everybody could come dressed
    0:20:31 in their favorite character.
    0:20:33 Tall people could be Vader and small people would be Ewoks.
    0:20:34 Pretty great.
    0:20:38 Well, then security will go crazy because everybody will look like Darth Vader.
    0:20:40 And how do we know one of them isn’t a criminal?
    0:20:41 Fair point.
    0:20:45 What if we just did a 24 hour movie marathon and people could get free coke and popcorn?
    0:20:53 Well, how many people can really take a 24 hour kind of movie marathon?
    0:20:55 Yeah, it sounds great on paper.
    0:20:57 But how many people will actually do it?
    0:20:57 All right.
    0:20:58 So we’ll stop there.
    0:20:59 And now we can do the exercise again.
    0:21:04 This time, I want you to start each and every response with the words yes and and we’ll just
    0:21:06 build on each other’s idea as we go.
    0:21:07 Can we do Harry Potter?
    0:21:08 Sure.
    0:21:09 Cool.
    0:21:11 So I’m going to cover you some ideas for a Harry Potter party.
    0:21:14 I’d like you to start each and every response with yes and and build on the idea.
    0:21:19 So I was thinking we could come to your house, put a sorting hat inside the front door and
    0:21:22 all the good people get the Gryffindor party and all the dark, mysterious people get the
    0:21:23 Slytherin party.
    0:21:24 Yeah.
    0:21:28 And then we could have this Quidditch contest and I have a bocce court.
    0:21:32 We could convert it to some kind of Quidditch court and have everybody flying around in
    0:21:33 their brooms.
    0:21:33 Yes.
    0:21:34 And we could.
    0:21:34 Yeah.
    0:21:37 Put them in one of those anti-gravity chambers where they could actually fly.
    0:21:39 Yeah.
    0:21:42 All right.
    0:21:42 So we’ll stop there.
    0:21:46 Listen, a lot more laughter, a lot more energy.
    0:21:48 And most of it became Italian for the first time.
    0:21:51 In the first exercise, do you think our idea was getting bigger or smaller as we were going
    0:21:52 through the Star Wars idea?
    0:21:54 Which direction was it?
    0:21:54 Smaller.
    0:21:57 And with the Harry Potter idea, are we getting bigger or smaller?
    0:22:00 Bigger and bigger, yes.
    0:22:04 Now, we have colleagues and clients and constituents to bring on board with our ideas at work.
    0:22:06 Sometimes it’s hard, the bosses and colleagues, et cetera.
    0:22:10 By the time we just finished building the Harry Potter idea together, whose idea was it by the
    0:22:11 time we finished?
    0:22:13 I hope all of us.
    0:22:14 Exactly.
    0:22:17 Yes, and has the power to turn a small idea into a big one really quickly.
    0:22:21 We can always value engineer a big idea back down again, but far more importantly inside
    0:22:26 as any organization has the power to transfer my idea to our idea and accelerate its opportunity
    0:22:27 to get done.
    0:22:29 That is the value of yes and.
    0:22:33 But I want to come back to when I ask people who are the most creative people you ever met,
    0:22:34 people always say kids.
    0:22:37 And you ask, what do kids do better than you?
    0:22:37 I say play.
    0:22:40 And then I’ll ask people, who’s encouraging playful at work every day?
    0:22:42 And nobody puts their hand up.
    0:22:44 So, let me ask you a question.
    0:22:45 Close your eyes.
    0:22:46 We’re going to play a word association game.
    0:22:48 I want you to shout out.
    0:22:48 Keep your eyes closed.
    0:22:52 I have to violate HIPAA here, Duncan.
    0:22:56 I am deaf and I’m listening to you through a cochlear implant.
    0:22:59 And I’m also seeing a simultaneous transcription.
    0:23:03 So, if I were to close my eyes and just depend on audio,
    0:23:05 I probably won’t understand what you’re saying.
    0:23:06 That’s fine.
    0:23:08 So, keep your eyes open.
    0:23:11 But I just want you to shout out the first word that pops into your mind
    0:23:13 when I ask you the following question.
    0:23:14 Where are you usually?
    0:23:17 And what are you doing when you get your best ideas?
    0:23:20 I am surfing and it is between sets.
    0:23:23 So, I have nothing to do but think.
    0:23:26 So, people will say surfing, jogging, walking, playing, exercising,
    0:23:28 in the park, in the forest.
    0:23:30 And do you know I’ve done it with up to 20,000 people?
    0:23:32 And I get them to write it down, that one word.
    0:23:35 And I say, hands up, who put down at work?
    0:23:37 Nobody ever has our best ideas at work.
    0:23:38 Why not?
    0:23:41 You remember that classic argument you were in with somebody recently?
    0:23:43 A bit of a shouting match, angry at each other.
    0:23:45 You turn to walk away from that argument.
    0:23:47 And the second you turn to walk away from the argument,
    0:23:48 what just popped into your head?
    0:23:50 The second you turn to walk away from that argument, what was it?
    0:23:52 How I could have wanted.
    0:23:53 The killer one line.
    0:23:55 Yeah, that one perfect, beautiful line.
    0:23:56 You wished you’d used, but you didn’t, did you?
    0:23:56 No.
    0:23:57 Why?
    0:24:00 Because when you’re in an argument, your brain is moving at 1,000 miles an hour,
    0:24:01 defending itself.
    0:24:05 At work, emails, presentations, weekly meetings, compliance training.
    0:24:08 I hear myself say, I don’t have time to think.
    0:24:10 And when we say we don’t have time to think,
    0:24:11 we’re in the brain state called beta.
    0:24:12 I call it busy beta.
    0:24:14 We’re the reticular activating system.
    0:24:18 Much easier, remember, as a door between your conscious and subconscious brain
    0:24:19 is firmly closed.
    0:24:23 When that door is closed, you only have access to your conscious brain.
    0:24:25 So what percentage of our brain is conscious?
    0:24:27 13% of our brain is conscious.
    0:24:30 87% of our brain is subconscious.
    0:24:34 But everything is back here to help you solve the challenge that you’re working on right now.
    0:24:36 But when the door is shut, you don’t have access to it.
    0:24:37 So what do I do?
    0:24:38 I run an energizer.
    0:24:39 What’s an energizer?
    0:24:40 It’s a silly exercise.
    0:24:41 Why am I doing that?
    0:24:42 To make you laugh.
    0:24:42 Why?
    0:24:46 Because the moment I hear laughter, I know that metaphorically, I placed you back in on the
    0:24:50 surfboard where it is where you have your best ideas into the brain state science calls alpha,
    0:24:54 where the door is just wide enough open between your conscious and subconscious brain.
    0:24:57 You can still make an informed decision, but you can still have a big idea.
    0:25:00 I don’t expect people to be playful every second of every day.
    0:25:03 I do expect people to be playful when they’re trying to have big ideas.
    0:25:05 That’s what children do better than they’ve done.
    0:25:11 When I was reading your book and I came to that section about the four states of a brain,
    0:25:15 when I read alpha, I said, guy, you are Mr. Alpha.
    0:25:20 I am an alpha when I’m in the shower, when I’m surfing, when I’m driving.
    0:25:21 Ask Madison.
    0:25:24 I’m like all alpha all the time.
    0:25:27 And can I ask you a question about these four states?
    0:25:30 Because you brought up a point here I didn’t quite understand.
    0:25:34 So the four states are alpha, beta, theta, and delta.
    0:25:41 Now in theta and delta, you talked about Edison and dropping a penny and then it woke him up again.
    0:25:48 And then you talk in the delta, the dreamy state about Dolly dropping a key and that would wake him up.
    0:25:56 So I didn’t understand why Edison dropping a penny is on theta and Dolly dropping a key is in delta.
    0:25:59 It seems like those are very similar things.
    0:26:00 Yes and no.
    0:26:01 So here’s how it works.
    0:26:06 If you know the expression when the penny drops, that eureka moment when I get the big idea, it came from Thomas Edison.
    0:26:07 He used thoughtful theta.
    0:26:12 He used to fall asleep at night, seated on an armchair with a tin tray on the floor.
    0:26:13 The penny was between his knees.
    0:26:14 He would fall asleep.
    0:26:15 His muscles would relax.
    0:26:16 The penny would drop.
    0:26:20 It would hit the tin tray and it would wake him up and he’d write down whatever he was thinking.
    0:26:21 And we might say, well, that’s nuts.
    0:26:22 I’d never do that.
    0:26:25 Well, who had more painted inventions in the 20th century than anybody else?
    0:26:28 Dolly used to fall asleep against his easel.
    0:26:31 As he fell asleep, he’d fall over and that would wake him up.
    0:26:33 And he would sketch whatever he was dreaming.
    0:26:35 Of course, I want to know he was smoking before he went to bed.
    0:26:36 But he’s not one of those.
    0:26:38 But neither of them were unsuccessful.
    0:26:46 If one of those people who gets our best ideas as we’re falling asleep or waking up, A, keep a notepad by the bed because you promise yourself you won’t forget it by six o’clock in the morning.
    0:26:53 Far more importantly, when you’re working with your colleagues, I hear so often clients will come to me and say, could you solve something in two hours?
    0:26:54 You’re like, yeah, right, sure.
    0:26:56 And the door was shut because we’re stressed.
    0:26:59 And so the door between our conscious and subconscious brain firmly stressed.
    0:27:01 Brief it in a week or two in advance.
    0:27:08 Give people time to go wherever they are, whether they’re in the shower, whether they’re falling asleep, whether they’re in dreaming delta, which is way in the middle of the night.
    0:27:11 So theta is the difference in answer to your question between theta and delta.
    0:27:15 Theta is just as you’re beginning to wake up in the morning or just as you’re nodding off at night.
    0:27:17 Delta is the doors are off.
    0:27:20 You’re riding pink ponies and unicorns through the universe at three o’clock.
    0:27:24 Probably not the best brain state for creativity at work.
    0:27:28 I find the best brain state for creativity at work is the one that you live in is alpha.
    0:27:30 How do we get there by being playful?
    0:27:32 I want you to answer that question.
    0:27:33 How do you get to alpha?
    0:27:37 I don’t have a problem getting to alpha, but how do other people get a problem?
    0:27:38 There’s a series of them in the book.
    0:27:39 They’re called energizers.
    0:27:40 They are 60 second X.
    0:27:45 When I walk into a room, the first thing I do is sand down and say, hands up, who’s creative?
    0:27:47 About 3% of the audience will put their hands up.
    0:27:54 So then I get them to stand up in pairs and I tell person A they are the leading designer of Parachutes for Elephants.
    0:27:55 Person B, they’re a news reporter.
    0:27:58 They have to interview person A about how they get their job done.
    0:28:02 And for the next two minutes, you just stand back and listen to the laughter in the room.
    0:28:10 All I’m doing is opening the door between the conscious and subconscious brain and putting them back in wherever it is when they have their best ideas, when they’re an amazing alpha.
    0:28:12 That’s what the energizers are for.
    0:28:14 They are playfulness with purpose.
    0:28:17 And again, ask us who are the most creative people we’ve ever met.
    0:28:18 Kids, what do they do?
    0:28:18 Play.
    0:28:19 This is not rocket science.
    0:28:27 I have to tell you, Duncan, that I’m almost afraid to admit this because people in California might go crazy when I tell them this.
    0:28:33 But I take three showers a day and I’m thinking in those showers all the time.
    0:28:35 And I surf once a day.
    0:28:36 Plenty of ideas.
    0:28:37 An idea factory.
    0:28:42 Ask Madison, am I an idea factory or not?
    0:28:43 Yes, very much so.
    0:28:44 Always new ideas.
    0:28:50 And Madison always says, no, because.
    0:28:54 Madison, yes, Angel.
    0:28:55 Yes, Anne, come on.
    0:28:57 I’ll work on it.
    0:29:03 Madison is my beta.
    0:29:08 Between my alpha and her beta, we are an unstoppable team.
    0:29:18 I would love to find out, do you even think it’s possible or does it merit doing this?
    0:29:20 But how do you measure creativity?
    0:29:23 That’s a tough one.
    0:29:24 I know how to measure an idea.
    0:29:25 Would that help?
    0:29:27 Yes, that’s close enough.
    0:29:35 So, you know, at the end of the brainstorm, we finish the brainstorm and we’re told we can put our three purple dots on the three ideas we like the most, the best.
    0:29:37 So we read all of the ideas and then we look around the room.
    0:29:38 Where’s our boss?
    0:29:39 Oh, yeah, they’re over there.
    0:29:41 Where are they going to put their red dots?
    0:29:42 Oh, idea number 17.
    0:29:46 So we line up right behind them and we put our idea on our dot on number 17.
    0:29:47 We tell them how much we liked it, too.
    0:29:48 But guess what?
    0:29:49 We didn’t.
    0:29:57 And so when the idea goes off to execution, it will get stuck, diluted or killed because the people who are responsible for getting it done were not passionate about it in the first place.
    0:30:02 So I have a talk called Passionometer where I allow people to vote anonymously on their favorite ideas.
    0:30:03 This is voting with your heart.
    0:30:05 Got nothing to do with the head, nothing to do with strategy.
    0:30:09 This is the idea that I want to take home and tell my loved ones I got to work on this.
    0:30:10 It was one of my ideas.
    0:30:11 That’s Passionometer.
    0:30:14 You want to find out where the passion of the team is first.
    0:30:19 I can get down from 50 ideas to about eight in a nanosecond doing that exercise, but it is done anonymously.
    0:30:24 Then I’ll share with you this tool that I borrowed with pride from Richard Branson.
    0:30:26 I love Richard Branson.
    0:30:29 When was the last time anybody ever called him a CEO?
    0:30:29 Never.
    0:30:30 Yes, he is.
    0:30:30 Of course he is.
    0:30:31 He’s an entrepreneur.
    0:30:32 He’s an entrepreneur.
    0:30:34 So think of all the things he’s launched that failed.
    0:30:41 Coca-Cola, Virgin Cola, Virgin Volca, Virgin Massages, Virgin Mobile, Virgin, you name it.
    0:30:41 So what?
    0:30:43 Virgin Bride?
    0:30:45 Yes, Virgin Wedding’s got to remember.
    0:30:47 He uses a tool called Stargazer.
    0:30:50 So this is about voting with your head, not your heart.
    0:30:52 Virgin is a very elastic brand, right?
    0:30:54 Disney is a very non-elastic brand.
    0:30:57 So Virgin, he’s done condoms and space travel and everything in between.
    0:31:03 So how does Virgin evaluate what new ideas and products and services they should bring to market?
    0:31:05 I use the same tool.
    0:31:06 I call it Stargazer.
    0:31:10 Let’s just say for today’s argument, is this idea a strategic brand fit?
    0:31:11 I’m making that up.
    0:31:14 People would choose their own criteria, obviously.
    0:31:16 Is this idea embedded in consumer truth?
    0:31:19 Maybe our target audience today is 21 to 24-year-olds.
    0:31:24 Can I get this idea executed in the next 12 to 18 to 24 months?
    0:31:25 My boss wants that done.
    0:31:27 Is it going to make us a bucket load of money?
    0:31:28 You’ll have a financial goal.
    0:31:30 And is it socially engaging?
    0:31:34 Is it going to get the 21 to 24-year-olds to talk about it on their social media?
    0:31:36 And all you do is you take each idea.
    0:31:40 And the problem with ideas are they’re horribly subjective, right?
    0:31:40 You like pink.
    0:31:41 I like blue.
    0:31:41 Our boss likes yellow.
    0:31:43 It’s a very good chance we’ll be doing the yellow idea.
    0:31:46 All you do is you go around and score the idea.
    0:31:50 Does it do a poor job, a good job, or an outstanding job of being aligned with our brand?
    0:31:51 It does a pretty good job.
    0:31:53 Is it going to make us a bucket load of money?
    0:31:54 Oh, hell yes.
    0:31:55 Is it socially engaging?
    0:31:56 It’s fairly good.
    0:31:59 Can I get it in the market the next 18 to 24 months?
    0:32:00 Not a chance.
    0:32:01 Is it embedded in consumer truth?
    0:32:02 It does a fairly good job.
    0:32:06 And then with a different colour for each of the last eight ideas you’ve got,
    0:32:11 at some point, one idea will rise to the top as to meeting your criteria the most,
    0:32:12 not the one you like the best.
    0:32:16 By the way, the other thing that Branson always said was,
    0:32:20 if it’s not a three out of three of embedded in consumer truth
    0:32:24 and aligned with the Virgin brand, we must have the courage to throw it out.
    0:32:27 When we were bringing two new Disney cruise ships into market,
    0:32:29 we were bringing the big ones in,
    0:32:31 we had to decide where the old ones would go.
    0:32:34 Like any big corporation, that conversation takes too long.
    0:32:36 And, oh, Dave’s not here today.
    0:32:37 Oh, Sally’s not here today.
    0:32:38 Oh, I’ve got to wait for Sally.
    0:32:38 No.
    0:32:41 Or it comes to all the VPs sitting in the room and go,
    0:32:42 do you know what?
    0:32:43 Last year I went to the Med.
    0:32:44 It was great.
    0:32:46 Oh, my wife loved the Alaska cruise.
    0:32:47 I don’t give a toss.
    0:32:49 We use this tool.
    0:32:52 We’re 16 senior vice presidents of the Walt Disney Company.
    0:32:55 We made a decision in 59 minutes.
    0:33:01 Because one of them was, can I actually get a berth in the port in which we want in the next 12 months?
    0:33:03 And if you can’t, you shouldn’t be doing it.
    0:33:05 And it’s just great for cutting through all the nonsense.
    0:33:08 And again, the tools are designed to be simple, powerful, fun.
    0:33:18 So just as a little bit of realism here, if you looked at the top of the funnel when everything was yes and,
    0:33:23 and the bottom of the funnel, like what percentage gets out and into reality?
    0:33:24 That’s very fair.
    0:33:29 So people often ask me what percentage of time they should spend in expansive versus reductive.
    0:33:32 And so everybody says, oh, 80% expansive.
    0:33:33 No, it’s the opposite.
    0:33:36 It’s 20% expansive, 80% reductive.
    0:33:37 The hard stuff is getting it done.
    0:33:40 Having ideas, like you said, hundreds a day.
    0:33:44 Getting them done through all the corporate approval processes, et cetera, et cetera, et cetera.
    0:33:45 That takes time.
    0:33:47 And that’s where the innovation tools come in.
    0:33:50 My favorite, as you could probably guess, is the one called What If.
    0:33:51 Why?
    0:33:52 Because it’s about breaking the rules.
    0:33:54 So it was a marvelous tool.
    0:33:58 It was created by Walt Disney for the film Fantasia in 1940.
    0:34:01 He wanted to pump mist into the theater and heat into the theater.
    0:34:03 And the theater owner said, no, Walt, too expensive.
    0:34:04 That’s not the way we do it here.
    0:34:07 So Walt, step one, list the rules of your challenge.
    0:34:10 So he just wrote down the rules of going to a movie theater.
    0:34:11 I must sit down.
    0:34:12 I must be quiet.
    0:34:12 It is dark.
    0:34:13 I must go to set time.
    0:34:15 I must watch the previews.
    0:34:16 I, Walt, can’t control the environment.
    0:34:18 Step one, list the rules.
    0:34:19 Step two, pick one.
    0:34:20 He chose the environment.
    0:34:22 And he said, what if I could control the environment?
    0:34:24 Well, that wasn’t audacious enough.
    0:34:30 The more audacious, outrageous and provocative your what if, the further out of your own river of thinking you’ll jump.
    0:34:35 So he said, well, OK, if I can’t control the environment inside the theaters, what if I take my movies out of the theater?
    0:34:36 Don’t be daft, Walt.
    0:34:36 They’re two-dimensional.
    0:34:37 They fall over.
    0:34:39 What if I made them three-dimensional?
    0:34:40 How do you do that, Walt?
    0:34:43 What if I just had people dressed as princesses and cowboys and pirates?
    0:34:45 People would be more immersed in that.
    0:34:47 Yeah, but you can’t have Cinderella standing next to Jack Sparrow.
    0:34:49 People would be immersed in her story.
    0:34:51 So he said, well, what if I put them in different themed lands?
    0:34:52 Boom.
    0:34:53 What if I called it Disneyland?
    0:34:57 Now, for people watching, it’s easy to say, oh, but I don’t have the resources.
    0:34:58 So I’ll give you another example.
    0:35:00 If I give you a big one, give you a small one.
    0:35:05 There was a very small company in Great Britain in the 60s that used to make glasses that we drink out of.
    0:35:08 They found too much breakage and not enough production when the glasses were being shipped and wrapped.
    0:35:13 So they went down to the shop floor, observed the industry and wrote down the rules.
    0:35:16 26 employees convey about 12 glasses to a box.
    0:35:17 Boxes made out of cardboard.
    0:35:18 Six on the top, six on the bottom.
    0:35:20 Glasses separated by corrugated cardboard.
    0:35:22 Glasses wrapped individually in newspaper.
    0:35:24 Employees reading the newspaper.
    0:35:27 So somebody asked the somewhat provocative, outrageous, what if question.
    0:35:28 They said, what if we poke their eyes out?
    0:35:30 That’s against the law and it’s not very nice.
    0:35:34 But because they had the courage to ask it, somebody sitting next to them, the lady said, hang on a minute.
    0:35:36 Why don’t we just hire blind people?
    0:35:37 So they did.
    0:35:38 Production up 26 percent.
    0:35:40 Breakage down 42 percent.
    0:35:44 The British government gave a 50 percent salary subsidy for hiring people with disabilities.
    0:35:50 It’s about listing the rules of the challenge, taking one and asking the most audacious, what if question.
    0:35:54 Why didn’t they just put newspapers in language that the people didn’t read?
    0:35:58 Ooh, see, there you are, an amazing alpha again.
    0:35:59 Dude, nice one.
    0:36:00 Should have done it in Japanese.
    0:36:08 Okay, but I asked you a very specific question from the top of the funnel to the bottom.
    0:36:10 Like, what’s a percentage?
    0:36:13 One out of 100, 20 out of 100.
    0:36:16 What’s the order of magnitude that get through this?
    0:36:19 I don’t think there’s a set percentage key.
    0:36:22 I will tell you one of the things that helped me get things done was persistence.
    0:36:24 I was like a bulldog and I wouldn’t let go.
    0:36:27 If I believed in something long enough, I would go at it and go.
    0:36:30 I would drive my boss absolutely mental, I would drive my boss absolutely mental and I wouldn’t give up on it.
    0:36:39 As I mentioned earlier on that the social video that we produced, which was the most successful social video we ever produced, I refused to go through the approval process.
    0:36:46 Because the approval process will get everybody in from brand strategy touching everything and diluting the content completely.
    0:36:49 And when we produced the video, somebody said, where’s our logo?
    0:36:50 I said, he’s five foot two.
    0:36:52 He’s got big black ears and everybody loves him.
    0:36:53 Get over yourself.
    0:36:55 Probably not the best.
    0:36:59 If you want somebody who stays inside the raw box, that’s probably not me.
    0:37:05 But the percentage of ideas that we came up with Disney that came back out the other end, 5% maybe.
    0:37:07 Up next on Remarkable People.
    0:37:11 We were tasked by Disneyland Paris to get more people to come more often spend more money.
    0:37:15 Our data told us who could afford the brand, who had affinityed the brand, who had been shopping online.
    0:37:16 It was a 10 out of 10 of I’m coming this year.
    0:37:17 Well, they hadn’t come.
    0:37:20 So our intuition told us our data was missing something.
    0:37:22 These people were either liars or procrastinators.
    0:37:23 So let’s go find out.
    0:37:36 Thank you to all our regular podcast listeners.
    0:37:39 It’s our pleasure and honor to make the show for you.
    0:37:45 If you find our show valuable, please do us a favor and subscribe, rate, and review it.
    0:37:48 Even better, forward it to a friend.
    0:37:50 A big mahalo to you for doing this.
    0:37:55 You’re listening to Remarkable People with Guy Kawasaki.
    0:38:02 How do you feel about these requirements of returning to the office?
    0:38:10 Do you think that returning to the office increases collaboration or returning to the office is going to kill the alpha state in most people?
    0:38:10 Think about this for a moment.
    0:38:11 Who’s making that decision?
    0:38:13 Oh, the boomers generation.
    0:38:13 Yeah.
    0:38:14 Okay, great.
    0:38:15 Well done, you.
    0:38:16 And what are you going to do?
    0:38:17 You’re going to lose talent.
    0:38:19 Because the talented people can leave.
    0:38:20 They can get a job somewhere else.
    0:38:23 If they don’t need to be there, they don’t need to be there.
    0:38:23 I’m sorry.
    0:38:24 I just vehemently disagree.
    0:38:27 As long as you get your job done, I don’t care if you’re standing on the moon.
    0:38:31 Here’s the biggest challenge facing corporate America in the next five to ten years.
    0:38:32 Guess what?
    0:38:33 Generation Z doesn’t want to work for you.
    0:38:34 You already know it.
    0:38:35 It terrifies you.
    0:38:39 How would you stay relevant if this entire generation doesn’t want to work for you?
    0:38:39 Why?
    0:38:41 Because you’ve been driven by quarterly results.
    0:38:42 They’re driven by purpose.
    0:38:44 You think they’ll bend to change to you.
    0:38:49 No, they won’t, just because you had to bend to change to your elders, because you could
    0:38:51 only tell two people down the park.
    0:38:52 They can tell the world.
    0:38:57 So I was asked to give a talk to, let’s just call it the largest tool manufacturer, about
    0:38:58 innovation and millennials.
    0:39:02 So I didn’t know anything about this generation in terms of how they reacted with tools.
    0:39:06 So I went down to Home Depot and Lowe’s, hung out in the aisle like some creepy dude.
    0:39:10 And I was just listening and watching at the point of purchase that we’re taking this home.
    0:39:14 And I went back to this brand, who is the largest manufacturer of tools in the United States
    0:39:16 and I said, listen, this generation has never heard of your brand.
    0:39:17 They didn’t mention you once.
    0:39:20 They didn’t mention your products, the hammer, the chisel, the sword.
    0:39:22 They didn’t even talk about the price, but they talked about what’s important to them.
    0:39:25 We’re going to remodel our dream kitchen, our dream bathroom, our dream apartment.
    0:39:29 I said, your purpose, if you choose to create one, is you could be the brand who helps people
    0:39:30 build their dreams.
    0:39:33 You could see the finance guys going, how quickly can we get this guy out of here?
    0:39:34 I said, well, hang on a minute.
    0:39:37 If you’re the brand who can help people build their dreams, could you be in banking?
    0:39:37 Yes.
    0:39:37 Finance?
    0:39:38 Yes.
    0:39:39 Engineering?
    0:39:39 Yes.
    0:39:40 Health?
    0:39:40 Yes.
    0:39:41 Education?
    0:39:41 Yes.
    0:39:42 Hospitality?
    0:39:42 Sport?
    0:39:43 You’d be in any line of it.
    0:39:44 No, no, we make tools.
    0:39:45 We’re really good at it.
    0:39:47 In fact, we’re going to expand into Mexico and India.
    0:39:48 They have a great middle class.
    0:39:49 They will buy our tools.
    0:39:50 Oh, yeah.
    0:39:51 OK, good luck with that.
    0:39:53 Have we seen the world of 3D printing recently?
    0:39:53 Right.
    0:39:56 India bypassed laptop computers and went to mobile phones.
    0:40:00 Generation Z will bypass tools and go to 3D printing.
    0:40:02 There’s a chap now.
    0:40:04 I don’t know if you saw the CBS special January last year.
    0:40:06 That’s how much impact it had on me.
    0:40:13 young guy in his 30s in Texas building houses fully sustainable for $1,500 in five days and
    0:40:14 the first houses he gave to the homeless.
    0:40:20 NASA have now employed him to print a landing pad on the moon from which he can print a printer
    0:40:21 from which he can build housing.
    0:40:25 And if we don’t have purpose, I believe Generation Z won’t work for us.
    0:40:32 And if you don’t have a new generation of employees, cast members, staff members, then I don’t care how successful you are today.
    0:40:33 You’re not going to be around 10 years from now.
    0:40:40 I got to say that if I’m listening to this and I’m buying into this, my first question would be, I’m stuck in this company.
    0:40:44 It’s full of no because and my bosses and stuff.
    0:40:45 What do I do?
    0:40:46 Now run to the door.
    0:40:47 Run for the exit.
    0:40:49 Literally, you’re saying leave.
    0:40:52 Here’s what I do with senior executives.
    0:40:55 I get them to do that no because yes and exercise.
    0:40:57 You can’t tell people what to do.
    0:40:58 They have to do it for themselves, right?
    0:41:00 And so people learn different ways.
    0:41:03 Some people will learn by seeing, some by doing, some by listening.
    0:41:08 And so I get them to do the no because and the yes and exercise because then they get, oh, I’m a no becauseer.
    0:41:11 And I tell them, I know you have responsibilities.
    0:41:12 You’re the CEO of you.
    0:41:17 So just remind yourselves, we’re not greenlighting this idea for execution today.
    0:41:19 We’re merely greenhousing it together using yes and.
    0:41:22 But I want to come back on those learning abilities for a moment.
    0:41:25 I can’t get you to close your eyes, but we’ll try it anyway.
    0:41:26 How many days are there in September?
    0:41:28 30, I would guess.
    0:41:29 Okay.
    0:41:29 How did you know?
    0:41:30 How did you remember?
    0:41:31 How did you learn it?
    0:41:33 What did you just think of?
    0:41:36 What could you see with your metaphorically eyes closed?
    0:41:38 How did you know there were 30 days in September?
    0:41:41 Madison, how did you know there were 30 days in September?
    0:41:44 Just remembering like a calendar when I was younger.
    0:41:44 A calendar.
    0:41:46 So Madison can see it.
    0:41:46 Okay.
    0:41:47 Guy, how did you remember it?
    0:41:52 I did it because I figured there’s very few months with 29 days.
    0:41:54 So it’s 30 or 31.
    0:41:56 And so it’s 50, 50.
    0:41:59 So just pick one and you’ll rewrite half at a time.
    0:42:02 30% of any audience would do this.
    0:42:04 30 days have September, blah, blah, blah.
    0:42:04 And November all the way.
    0:42:06 They are auditory learners.
    0:42:07 How do I know that?
    0:42:10 They just told me because how old were they when they learned the rhyme?
    0:42:10 Six.
    0:42:11 How do they remember it?
    0:42:12 Because they heard it.
    0:42:14 40% of the audience would do what Madison just did.
    0:42:17 They go, oh, no, I could just see a candle with a number 30, the word September.
    0:42:19 They’re your visual learners.
    0:42:21 And then these, but you’ve never seen anybody do this?
    0:42:24 January, February, March, April, May, June, July, August.
    0:42:25 These are kinesthetic learners, right?
    0:42:26 They learn by doing.
    0:42:30 And when I decided to create a book, I said to the publisher, it’s not a book.
    0:42:31 He goes, what do you mean it’s not a book?
    0:42:32 I said, it’s not a book.
    0:42:32 If it’s a book, we fail.
    0:42:33 Why?
    0:42:36 Because when you see a book in an office, where is it?
    0:42:37 It’s on the coffee table.
    0:42:37 It’s on the bookshelf.
    0:42:38 That’s a waste of money, isn’t it?
    0:42:43 So I decided, OK, what nonfiction book have I ever read where I could read one page today,
    0:42:45 put the rest of the book down, but know exactly what to do next?
    0:42:47 I thought, my mum’s cookbook.
    0:42:48 You want shepherd’s pie?
    0:42:49 I said, page 67.
    0:42:49 Cherry trifle?
    0:42:50 Page 42.
    0:42:52 So the book is designed the same way.
    0:42:54 It says, have you ever been to the contents page?
    0:42:56 It literally says, have you ever been to a brainstorm where nothing ever happened?
    0:42:57 Go to page 12.
    0:42:59 Work in a heavily regulated industry?
    0:43:00 Go to page 42.
    0:43:04 But it’s also designed for our visual, kinesthetic, and auditory learners.
    0:43:05 There’s QR codes throughout.
    0:43:07 They’re dynamic, so I can change them at any time.
    0:43:11 For the auditory learners, it’s Sposify, but I’ll change it to an audio book over time.
    0:43:15 For the visual learners, I am now an animated character, because I love doing things I haven’t
    0:43:16 done before.
    0:43:20 So I went into a studio in LA and bounced around with some characters.
    0:43:23 I teach you how to use the tools inside the imagination.
    0:43:28 But for the kinesthetic learners, I don’t know if it’s the first, but I haven’t seen another
    0:43:29 one.
    0:43:32 It’s the first ever fully integrated artificial intelligence book.
    0:43:36 So you can ask the book questions through the QR code on the back of the book, and the
    0:43:37 book will answer you.
    0:43:39 Now, here’s the power of AI, right?
    0:43:43 So I thought, ooh, I live in the most litigious country on the planet, so careful now.
    0:43:46 So I thought, okay, I could just say, how do I use the tool on Pay67?
    0:43:47 Nah, who cares?
    0:43:48 I’ve just read the book.
    0:43:48 Why would I need that?
    0:43:53 No, you can ask the book, how do I use the tool on Pay67 to sell more orange pencils in
    0:43:55 the state of Pennsylvania on January the 3rd next year?
    0:43:57 The book will answer you.
    0:44:00 But I thought, oh, but if they lose money on the orange pencils, are they going to sue me?
    0:44:03 So it’s like, here come the terms and conditions.
    0:44:05 I love doing things I haven’t done before.
    0:44:07 That’s the only thing that excites me.
    0:44:09 If I know how to do it, I get bored really easily.
    0:44:11 So the book is, it’s a toolkit.
    0:44:12 Now, I wanted to give it away for free.
    0:44:14 The publisher had slightly different ideas.
    0:44:18 Still want to give it away for free for students, because these are tomorrow, and these are the
    0:44:21 people being told to stop asking why, because there’s only one right answer.
    0:44:22 Don’t forget to color between the lines.
    0:44:26 And they’re identifying as not creative by the time they leave university.
    0:44:27 And that’s just sad.
    0:44:29 I read your book cover to cover.
    0:44:32 And wow, there’s so much in there.
    0:44:34 30 bloody years, mate.
    0:44:35 Try to get into 12 pages.
    0:44:37 The editor had a field day.
    0:44:40 So the next book I want to write is called Rolling Back the Ears.
    0:44:43 It’s all the fun stuff that happens behind the magic to make it happen.
    0:44:46 Like the day I stole the turkey from the president of the United States of America on Thanksgiving
    0:44:50 Day, or the day I sent my son’s Buzz Lightyear into space for the opening of Toy Story.
    0:44:52 That’s what I love doing about Disney.
    0:44:56 What I loved the most was this Henry Ford quote.
    0:44:58 Whether or not you think you can or think you can’t, you’re probably right.
    0:45:00 It was Disneyland’s 50th anniversary.
    0:45:02 The actual anniversary was over.
    0:45:03 The media were tired of hearing from us.
    0:45:06 I was like, what else do the media have to cover, even if they don’t want to?
    0:45:09 Well, Mother’s Day, Father’s Day, Thanksgiving, Halloween, etc.
    0:45:10 I said, tell me about Thanksgiving.
    0:45:13 And this bloke said, well, the president pardons a turkey.
    0:45:14 I said, well, hang on.
    0:45:17 That’s the only turkey that doesn’t get killed that year.
    0:45:17 He goes, yeah.
    0:45:19 I said, wouldn’t that make him the happiest turkey on earth?
    0:45:23 And everybody goes, oh, don’t even go there, dude, because Disneyland is the happiest place
    0:45:23 on earth.
    0:45:24 So I’m a great believer.
    0:45:25 You pick up the phone.
    0:45:26 You make your pitch.
    0:45:26 They can laugh.
    0:45:27 They can say no.
    0:45:28 They can put the phone down.
    0:45:28 Who cares?
    0:45:32 So I phoned the White House and I got through to the director of communications.
    0:45:34 I said, hey, what do you do with a turkey after the pardoning ceremony?
    0:45:36 He says, oh, we give it to the National Turkey Federation.
    0:45:38 I was like, oh, didn’t know we have one.
    0:45:39 Couldn’t give me their number, could you?
    0:45:42 So I called the president of the National Turkey Federation.
    0:45:43 I said, what do you do with the turkeys after?
    0:45:45 He said, oh, we’re just putting on a petting seal.
    0:45:46 I said, well, can I have them?
    0:45:46 He goes, yeah.
    0:45:49 I was like, oh, aren’t we supposed to negotiate or haggle?
    0:45:53 Then I found out more about turkeys than you could possibly want to know.
    0:45:56 Turkeys, when grown to a certain size, have heart attacks and die.
    0:45:57 I thought, oh, great.
    0:45:57 You want coverage.
    0:46:01 The one turkey pardoned by the president of the United States of America
    0:46:03 is killed by a British PR guy on a stunt for Disney.
    0:46:06 So in a moment of total and utter stupidity,
    0:46:08 guy, we’ve all had those moments in our career
    0:46:10 which seemed like a good idea at the time.
    0:46:12 Well, I sent Pilgrim Mickey, the walk-around character,
    0:46:16 and the parade music up to the pen, get the turkey kind of acclimatized.
    0:46:18 And then I phoned the National Turkey Federation.
    0:46:20 I said, you have told the White House we’re taking the turkey, right?
    0:46:21 He said, no.
    0:46:23 I said, you have to because we’re going to do the Super Bowl spot.
    0:46:24 Turkey won.
    0:46:26 You’ve just been pardoned by the president of the United States of America.
    0:46:27 What do you do next?
    0:46:27 Gobble, gobble.
    0:46:28 I’m going to Disneyland.
    0:46:31 So they phoned back and said, no, the White House is in.
    0:46:31 I said, oh, great.
    0:46:33 So then I get a call from our chairman.
    0:46:35 He said, Duncan, I see you booked the corporate jet
    0:46:38 for the 23rd of November from Washington, D.C. to L.A.
    0:46:41 Can you tell me the passenger manifest, please?
    0:46:44 I was like, well, Jay, I’ve got a couple of turkeys I need to move.
    0:46:45 He goes, absolutely not.
    0:46:49 I said, Jay, this is the second busiest travel day of the year.
    0:46:50 It’s two days before Thanksgiving.
    0:46:52 If you cancel, we can’t get this done.
    0:46:53 And the president says we’re doing it.
    0:46:54 He goes, I don’t care.
    0:46:55 We’re not doing it.
    0:46:57 Which I realized why afterwards.
    0:47:02 I wish he just told me this would be his first request of the corporate jet from Bob because
    0:47:03 Bob would just become CEO.
    0:47:05 And imagine being your first request.
    0:47:06 I need the corporate jet.
    0:47:07 What for?
    0:47:08 A couple of turkeys.
    0:47:11 So I’m now in my favorite meeting of my 30 years at Disney.
    0:47:13 36 people around a table.
    0:47:15 Very serious conversation.
    0:47:18 Animal welfare rights, corporate communications, operations, entertainment.
    0:47:23 If the turkey dies halfway down Main Street, USA, will we run out and shroud it?
    0:47:25 Or will you just look the other way and pretend it didn’t happen?
    0:47:29 So then, God bless America, unbeknownst to any of us, the turkey that travels to the White
    0:47:31 House travels with a stunt double.
    0:47:32 This is what I loved about Disney.
    0:47:35 When you said, here’s a problem, somebody went, I got you.
    0:47:38 So this guy called Denny from Entertainment pops up out of nowhere.
    0:47:41 He goes, do you remember the old spy movies, the black and white ones?
    0:47:43 I was like, Denny, you really want to bring that up right now?
    0:47:44 He goes, yeah, yeah.
    0:47:47 Remember when the bad guy’s running away, the good guy’s running away from the bad guys?
    0:47:49 He hits the wall and the wall turns around.
    0:47:50 He’s on the other side of it.
    0:47:51 I said, yeah.
    0:47:53 He goes, I’ll build you one of those.
    0:47:56 We’re going to put turkey one out the front of the float, turkey two out the back.
    0:47:58 If turkey one goes down, I’ve got your back.
    0:47:59 I said, oh, genius.
    0:48:03 So now when you think nothing else could possibly go wrong, there’s a couple of weeks to go.
    0:48:05 Bird flu hits the United States of America.
    0:48:08 So I phoned up the director of comms at United Airlines.
    0:48:10 I said, come on, we’re going to have a bit of fun with this.
    0:48:13 And unbeknownst to us, they’d work with the Federal Aviation Authority.
    0:48:15 So we walk into the airport.
    0:48:20 And this is back in 2005 now, where the airports used to go, where the flights would drop down.
    0:48:24 And it just came, instead of United Airlines 253, it just said, Turkey one.
    0:48:26 I was like, oh, my God.
    0:48:29 So then we get on the plane and they’ve got postcards in all the seats.
    0:48:35 This is in honor of today’s guests, Marshmallow and Yam, who have been pardoned by the Presidents of the United States of America on their way to Disneyland.
    0:48:38 We will not be serving turkey sandwiches in today’s flight.
    0:48:39 We’ll be serving ham or cheese.
    0:48:41 So now we get into the briefing room.
    0:48:43 And the very first, we did it for seven years.
    0:48:45 We did it with George Bush and President Obama.
    0:48:53 George Bush comes in, unbeknownst to any of us, his script writer finds out where the turkeys are going, decides to have a bit of fun at our expense, but nobody had told us.
    0:48:55 And I’m in charge of public relations at the time.
    0:49:01 So George comes in, he goes, this year, Marshmallow and Yam were a little bit nervous about going back to a place called Frying Pan Park.
    0:49:03 I was like, who the hell called it Frying Pan Park?
    0:49:05 He goes, so this year, the turkeys are going to Disneyland.
    0:49:08 I was like, oh, my God, did the President of the United States of America just…
    0:49:11 And he goes, not only that, they were served the rest of their days at Disneyland.
    0:49:12 I was like, my God, he said it twice.
    0:49:19 And then he wrapped up his speech, he said, and not only that, they were served as grand marshals in Disneyland’s Thanksgiving Day Parade.
    0:49:20 I was like, I can retire.
    0:49:22 This is the best day of my life.
    0:49:27 So the head of entertainment for Disney Parks comes across the room looking really angry, very frustrated.
    0:49:28 It was like, dude, chill out.
    0:49:29 This is the best day of my life.
    0:49:32 He goes, we don’t have a Thanksgiving Day Parade.
    0:49:34 I was like, oh, my God.
    0:49:38 He goes, in order to build you two floats in a couple of days, it’s going to cost you a couple of hundred thousand dollars.
    0:49:40 I said, well, Matt, I don’t have any money.
    0:49:42 The President says we’re doing it.
    0:49:42 So over to you.
    0:49:51 And two days later, God bless Matt, Marshmallow and Yam came down the street of Main Street USA at Disneyland as grand marshals in Disneyland’s Thanksgiving Day Parade.
    0:49:57 To me, it’s the epitome of, I love the Thomas Edison quote, whether or not you think you can or think you can’t, you’re probably right.
    0:50:03 I dare you to try this again this November.
    0:50:05 Don’t go there, don’t go there.
    0:50:06 Don’t, do not.
    0:50:08 Do not go there.
    0:50:12 You and Elon with two turkeys.
    0:50:13 I can see that.
    0:50:18 There’s a joke there somewhere, but I’m not going.
    0:50:19 I’m not reaching for it.
    0:50:27 My last question for you is that you mentioned the concept of how to read your customer.
    0:50:29 Oh, not, I used the C word.
    0:50:33 How do you read your guest’s mind?
    0:50:35 How do you read the mind of your guests?
    0:50:37 Yeah, intuition.
    0:50:42 So if I were to ask people, have you ever stared at the back of the head of somebody you think looks totally hot?
    0:50:44 And that person is a total stranger.
    0:50:46 They immediately turn around and look at you to look away really quickly.
    0:50:47 Well, we’ve all done it.
    0:50:48 How did we know?
    0:50:48 How did they know?
    0:50:53 We have 120 billion neurons in this brain and 120 million neurons in this brain.
    0:50:58 The brain with which we as consumers and as business people make a lot of our decisions when we say we went with our gut.
    0:51:02 So what is the power of intuition in an AI dominated world?
    0:51:06 We were tasked by Disneyland Paris to get more people to come more often spend more money.
    0:51:10 Our data told us who could afford the brand, who had affinity to the brand, had been shopping online.
    0:51:11 It was a 10 out of 10 of them coming this year.
    0:51:12 Well, they hadn’t come.
    0:51:15 So our intuition told us our data was missing something.
    0:51:17 These people were either liars or procrastinators.
    0:51:18 So let’s go find out.
    0:51:22 So we went to go and live with one of 26 different families for a day.
    0:51:26 Now, going into hypotheses based on data and data alone was if we build it, they will come.
    0:51:29 Well, that’s a $250 million capital investment strategy.
    0:51:30 So you better be right.
    0:51:32 So we went off to live with a series of different families.
    0:51:34 Now, let me ask you a question, Guy.
    0:51:34 Do you have children?
    0:51:36 Four of them.
    0:51:40 OK, so I kind of need you to close your eyes, but not close your eyes.
    0:51:42 So picture the favorite photograph.
    0:51:44 It’s in your house somewhere.
    0:51:45 It’s a physical photograph.
    0:51:47 It’s that favorite one of your children.
    0:51:50 It makes you smile every time you think of it.
    0:51:52 Which room is that favorite photograph in?
    0:51:55 It is a picture of me with my children.
    0:51:57 We’re all in wetsuits.
    0:51:58 We’re holding our surfboards.
    0:51:59 We just finished surfing.
    0:52:01 And where were you that day?
    0:52:03 Where was the photograph taken?
    0:52:06 Well, there’s two versions of that photo.
    0:52:09 One is in Waikiki and the other is in Santa Cruz.
    0:52:10 But let’s say the Waikiki one.
    0:52:11 OK, Waikiki one.
    0:52:14 And are you comfortable telling us your children’s names?
    0:52:15 Oh, of course.
    0:52:19 It’s Nick, Noah, Noemi and Nate.
    0:52:22 Nick, Noah, Noemi and Nate.
    0:52:24 How old were they the day the photograph was taken?
    0:52:33 Oh, something like 22, 20, 13 and 11.
    0:52:33 Something like that.
    0:52:35 And how old are they today?
    0:52:38 Oh, they are 32, 30.
    0:52:40 I know I’m going to get this wrong.
    0:52:43 And 21 and 19.
    0:52:44 Something like that.
    0:52:45 So give or take the photograph.
    0:52:47 I hope my wife doesn’t listen to this.
    0:52:50 So give or take the photograph about 12 years old.
    0:52:51 The one that you just thought of.
    0:52:54 OK, so I asked the lady that I was living with.
    0:52:56 I said, how old are your children?
    0:52:59 The photograph looked like they were 24, 24 or five.
    0:53:01 She goes, oh, no, love, they’re 24 and 25.
    0:53:02 So I wrote it down.
    0:53:03 It’s an individual clue.
    0:53:04 It means nothing at the time.
    0:53:05 It’s an individual data point.
    0:53:08 So when we got back together, we all had the same data point.
    0:53:10 When we asked the parent, when I asked you just now,
    0:53:12 when I asked her how old the children were,
    0:53:14 they turned out the picture was 20 years older in reality.
    0:53:17 So my intuition was like, well, why is that?
    0:53:20 But why did you just pick the one that you just thought of?
    0:53:22 Why have people who are watching today or listening today,
    0:53:25 who don’t have children, close your eyes
    0:53:27 and think about that one in your parents’ house.
    0:53:30 The dorky one of you from 15 or 20 years ago
    0:53:31 where you look like a complete and utter dickhead.
    0:53:32 But it’s still there, isn’t it?
    0:53:34 Yes, staring you in the face every time you walk in.
    0:53:35 Why?
    0:53:36 Why is it still there?
    0:53:38 So I use the seven whys like a child.
    0:53:39 Why, why, why, why, why, why?
    0:53:42 The insight for innovation comes on the fifth or sixth way,
    0:53:43 not the first or second way.
    0:53:46 And all the mums talked about three moments in time
    0:53:48 through which a parent and a child must cross.
    0:53:49 I’ve been through all three.
    0:53:50 I know where I was for all three.
    0:53:54 I knew when I was the day that my son, who was about nine,
    0:53:55 he had tears in his eyes.
    0:53:56 He said, are you Santa Claus?
    0:54:00 And what hurt was, what was behind what he said?
    0:54:01 I’m not your little boy anymore, daddy.
    0:54:02 I’m growing up.
    0:54:04 I know where I was when my daughter was 13,
    0:54:06 dropped my hand in public for the first time.
    0:54:08 It’s a seminal moment between a father and a daughter.
    0:54:11 And I’m sure, like me, you know exactly where you were
    0:54:12 when you had to say to your eldest,
    0:54:16 goodbye for the very first time in their freshman year of college.
    0:54:17 And you had to turn around and walk away.
    0:54:20 And so our going in hypothesis was,
    0:54:21 if we build it, they will come.
    0:54:22 But what we realized was,
    0:54:24 despite what our data was telling us,
    0:54:25 there isn’t a single mum on the planet
    0:54:26 that woke up this morning saying,
    0:54:29 oh, I wonder if Disneyland’s got a new attraction this year.
    0:54:32 But mum wakes up every morning, as she does every day,
    0:54:34 worried about how quickly her children are growing up
    0:54:36 and how she wants to make special memories for them.
    0:54:37 While they still believe,
    0:54:38 while they still hold my hand,
    0:54:39 while they’re still here.
    0:54:41 That’s the segmented communication campaign.
    0:54:42 Disneyland Paris,
    0:54:43 while Johnny still believes.
    0:54:44 Disneyland Paris,
    0:54:45 while Sarah will still hold your hand.
    0:54:46 Disneyland Paris,
    0:54:47 where Dave is still here.
    0:54:51 Drove a 21% incremental attendance to the parks
    0:54:54 and turned a somewhat arrogant product-centric organization
    0:54:56 to a genuinely consumer-centric organization.
    0:54:58 It’s now mandatory for every Disney executive
    0:55:00 to go sweep the streets of Disneyland
    0:55:01 one day or two days a year.
    0:55:03 and one day a year in the living room
    0:55:04 of one of our consumers
    0:55:06 using our intuition.
    0:55:08 And that happens to this day.
    0:55:09 That still happens.
    0:55:09 Yeah.
    0:55:10 Oh, God, yes.
    0:55:11 The thing is, right,
    0:55:12 when you get to my age,
    0:55:13 you get down on your knees
    0:55:14 to do some pin training with a small child.
    0:55:15 Then you think,
    0:55:17 shit, I can’t get back up again.
    0:55:19 Oh, my.
    0:55:24 Duncan, I…
    0:55:27 Man, it’s seldom we have a podcast
    0:55:29 at such a pace.
    0:55:34 And this is like the real drinking out of a river.
    0:55:37 I know you use the concept of river,
    0:55:39 of thinking in a negative way
    0:55:40 where you’re stuck in that river,
    0:55:42 but this is drinking from a river
    0:55:44 of creativity and innovation.
    0:55:47 So I thank you for being on my podcast.
    0:55:49 I’m going to look at Disneyland
    0:55:51 and Disney a whole different way,
    0:55:53 even more positive if that’s possible.
    0:55:55 And congratulations on your book.
    0:55:57 Again, Duncan’s book’s name
    0:56:00 is Imagination Emporium.
    0:56:02 And I cannot think of a book
    0:56:04 that is designed the way this one is
    0:56:06 and with the colors and the illustrations.
    0:56:08 So, yeah, as you would expect
    0:56:10 the book from Duncan Wardell
    0:56:11 to look like,
    0:56:13 it fulfills your every fantasy.
    0:56:16 So thank you very much, Duncan.
    0:56:16 And thank you, Madison.
    0:56:18 Yes, thank you.
    0:56:18 I’m going to thank
    0:56:20 the Remarkable People team,
    0:56:22 which is, of course, Madison Neismar,
    0:56:24 producer and co-author,
    0:56:26 Tessa Neismar, researcher,
    0:56:28 who dug up all the dirt on you for me.
    0:56:32 And there is my sound design engineers,
    0:56:34 which is Shannon Hernandez and Jeff C.
    0:56:36 So we are the Remarkable People team.
    0:56:39 And I find it hard to believe
    0:56:41 that you’re not a little bit more remarkable
    0:56:43 after listening to this episode
    0:56:44 and you’re going to be more creative
    0:56:46 and innovative and change the world
    0:56:48 and empathetic and all that good stuff.
    0:56:50 And you’re going to look at turkeys
    0:56:52 in a completely new way.
    0:56:55 So thank you, Duncan.
    0:56:56 And until next time,
    0:56:58 mahalo and aloha
    0:57:00 from the Remarkable People team.
    0:57:07 This is Remarkable People.

    What if the secret to innovation isn’t having a dedicated innovation department, but rather unleashing the creative potential in every employee? In my latest Remarkable People episode, I sat down with Duncan Wardle, former Head of Innovation and Creativity at Disney, who transformed how one of the world’s most creative companies approaches innovation. Through captivating stories – like “borrowing” presidential turkeys for Disneyland – Duncan reveals practical tools that anyone can use to unlock their creative potential. His new book Imagination Emporium embodies his innovative approach, breaking traditional business book rules with AI integration and personalized learning paths. The key lesson? Innovation isn’t about job titles or special departments – it’s about creating an environment where everyone can contribute by replacing “no, because” thinking with “yes, and” possibilities.

    Guy Kawasaki is on a mission to make you remarkable. His Remarkable People podcast features interviews with remarkable people such as Jane Goodall, Marc Benioff, Woz, Kristi Yamaguchi, and Bob Cialdini. Every episode will make you more remarkable.

    With his decades of experience in Silicon Valley as a Venture Capitalist and advisor to the top entrepreneurs in the world, Guy’s questions come from a place of curiosity and passion for technology, start-ups, entrepreneurship, and marketing. If you love society and culture, documentaries, and business podcasts, take a second to follow Remarkable People.

    Listeners of the Remarkable People podcast will learn from some of the most successful people in the world with practical tips and inspiring stories that will help you be more remarkable.

    Episodes of Remarkable People organized by topic: https://bit.ly/rptopology

    Listen to Remarkable People here: **https://podcasts.apple.com/us/podcast/guy-kawasakis-remarkable-people/id1483081827**

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  • Yoni Appelbaum: How America Got Stuck

    Yoni Appelbaum: How America Got Stuck

    AI transcript
    0:00:05 It takes a large chunk of the population that makes it clear that it has a set of priorities
    0:00:10 that they will hold politicians accountable for pursuing, and politicians will respond
    0:00:12 to that incentive 10 times out of 10.
    0:00:16 I think it’s one thing that Donald Trump has done really well is he’s made it entirely
    0:00:22 clear to all Republican elected office holders that his voters will respond to him, they
    0:00:26 will show up, they will vote, and they will vote against the people who cross them.
    0:00:31 If you want to push back against that, you’ve got to show that you can be equally powerful
    0:00:37 at organizing from the bottom up.
    0:00:38 My name is Guy Kawasaki.
    0:00:43 This is the Remarkable People podcast, and as you may gather, we’re in the business of
    0:00:49 helping people be remarkable by finding other remarkable people to interview and find out
    0:00:54 their story and find out what they’re doing and how they got to where they are.
    0:00:57 And we have a Remarkable Guest, of course, for you today.
    0:01:06 His name is Yoni Applebaum, and he is the Deputy Executive Editor of The Atlantic.
    0:01:09 And I want people to know I love The Atlantic.
    0:01:13 It is a bastion of freedom of expression and freedom of thought.
    0:01:17 And Yoni, I want you to know I am a paid subscriber.
    0:01:21 I’m not just free-loading on your intellectual efforts, okay?
    0:01:22 Love to hear it.
    0:01:30 Now, Yoni has also taught at Harvard, Babson, Babson, that enlightened educational institution
    0:01:32 gave me an honorary doctor.
    0:01:33 I love Babson.
    0:01:35 I’ve got to make sure I pronounce this right.
    0:01:37 Is it Brandeis or Brandeis?
    0:01:38 How do you say that at university?
    0:01:39 Brandeis.
    0:01:40 Brandeis.
    0:01:41 All right.
    0:01:43 So, obviously, I didn’t go there.
    0:01:51 And I have to tell you that Yoni has one of the best stories about how he got his job
    0:01:55 – ever, ever.
    0:01:58 So I know you must be tired of telling this story.
    0:02:01 It’s like when people ask me, “What was it like to work for Steve Jobs?”
    0:02:07 But I got to ask you, “Please tell the story of how you got this job at The Atlantic.”
    0:02:10 I got my job by procrastinating.
    0:02:14 I was a doctoral student in American history.
    0:02:17 And what you do if you’re getting a doctorate is you write a dissertation.
    0:02:21 What you actually do if you’re getting a doctorate is you do almost anything to avoid
    0:02:22 writing the dissertation.
    0:02:24 It’s a really big project.
    0:02:25 It’s really hard.
    0:02:27 And I was prone to distraction.
    0:02:33 And I was on my computer one day when I was supposed to be writing and clicked over and
    0:02:36 saw a new blog I’d never seen before.
    0:02:39 And the blogger had written something that I thought was wrong.
    0:02:43 So I jumped into his comment section to tell him why I thought he was wrong.
    0:02:47 This is the kind of thing a lot of people waste a lot of time doing on the internet.
    0:02:51 But something really unusual happened, which is that he jumped into the comment section
    0:02:53 himself and said, “Oh, that’s a really good point.
    0:02:54 I’m glad you said that.”
    0:02:56 I thought, “That’s unusual.”
    0:03:01 So I came back the next day and engaged on his next post and we struck up a conversation.
    0:03:06 I was commenting anonymously and was mortified when one day he reached out to me and said,
    0:03:08 “You sound like you’re a historian.”
    0:03:14 And I thought, “On the internet, nobody’s supposed to know if you’re a dog, right?
    0:03:18 I’m writing in such stilted paragraphs and in such a long-winded way that it’s obvious
    0:03:21 to him I’m an academic because who else talks like that?”
    0:03:24 And so he outed me and so we talked.
    0:03:28 And he was a staff writer for The Atlantic and his name was Ta-Nehisi Coates.
    0:03:33 And he was thinking out loud on his blog and inviting others into the conversation.
    0:03:38 And he’s a wonderful and warm and generous guy and he went to his editor about me.
    0:03:39 I didn’t know that.
    0:03:42 I’m sitting at my desk one day and the phone rings.
    0:03:45 The editor of The Atlantic is on the other end of the line and he says, “Ta-Nehisi says
    0:03:48 there’s a guy in this comment section who should be writing for us.
    0:03:51 How would you like to be a contributor to The Atlantic?”
    0:03:54 And that’s how I ended up doing journals.
    0:03:57 Man, when I read that story, I said, “Wow.”
    0:04:02 That is literally the only positive thing I’ve ever heard coming from commenting on
    0:04:05 somebody else’s podcast or somebody else’s column.
    0:04:08 That’s a great story.
    0:04:09 Oh, man.
    0:04:14 But do you think it’s because he has such an open mind and he’s so smart?
    0:04:18 I mean, I don’t know if this would work with most people.
    0:04:23 I wrote for The Atlantic for five years and then I got another call and they said, “Why
    0:04:28 don’t you resign your post to Harvard, give up the only profession that still offers a
    0:04:34 guarantee of lifetime employment, and switch to journalism?”
    0:04:36 That was an IQ test, Shione.
    0:04:37 And I failed.
    0:04:38 That’s the sad thing I failed.
    0:04:41 I did switch it, but it was a hard choice, right?
    0:04:44 It was another one of those branching moments in my life where I thought, “God, why would
    0:04:45 I do that?
    0:04:46 I’m doing what I love.
    0:04:47 I really loved teaching.
    0:04:52 I loved writing, and I thought, why would I give that up to switch to a profession that
    0:04:54 seems like it’s in free fall?”
    0:04:56 But this is the answer to your question.
    0:04:58 The two things that drew me to journalism.
    0:05:01 One was when I was an academic, I was supposed to have all the answers.
    0:05:05 I’d stand in front of the classroom and my students would ask me things, and I needed
    0:05:06 to know.
    0:05:12 As a journalist, and this was, I think, Tanhasi’s superpower, you’re encouraged to be ignorant.
    0:05:14 You’re not supposed to have the answers.
    0:05:17 You get this amazing privilege just because you’re a journalist.
    0:05:21 You get to pick up the phone and call people or stop them on the street corner and say,
    0:05:23 “Hey, I’d like to understand this.
    0:05:24 Could you explain it to me?
    0:05:27 Could you tell me how the world looks through your eyes?
    0:05:30 Could you explain this complicated thing that I don’t get?”
    0:05:33 It was a privilege to be ignorant.
    0:05:34 It was a privilege to be curious.
    0:05:38 To get to ask the questions rather than have to have the answers.
    0:05:39 That was one reason I left.
    0:05:44 I think it was the big thing about Tanhasi that really set him apart was he took that
    0:05:45 to the end degree.
    0:05:48 He was relentlessly, is relentlessly curious.
    0:05:52 He was open to hearing different things from different people, and I’ve tried to model
    0:05:53 myself on that.
    0:05:56 The other part of it was academia.
    0:05:57 It’s a solitary pursuit.
    0:06:01 I was pursuing my own glory, my own research, sat in my own office on the end of a long
    0:06:05 hall with a lot of other brilliant people who were smarter than I was, who were sitting
    0:06:06 in their offices.
    0:06:09 Sometimes I’d see them down by the coffee machine.
    0:06:14 In the job I moved into, my job as an editor is to make other people’s work better.
    0:06:17 That just turned out to be a lot more satisfying.
    0:06:22 Pray tell, did this job change involve a physical move?
    0:06:24 I’m glad you asked that.
    0:06:26 It involved an involuntary move.
    0:06:30 I was very happy where I was, and they said, “You’re going to have to leave Cambridge,
    0:06:33 Massachusetts,” which is where I was living, and move down to Washington, D.C. if you
    0:06:36 want to take this job, and so I did.
    0:06:39 You weren’t stuck.
    0:06:45 I wasn’t, but I was thinking about it already, and what you’re getting at there is the thesis
    0:06:49 of my new book, which is about moving.
    0:06:54 We will come back to the subject of stuck, because I know you’re on my podcast, not
    0:07:00 because you like me, but you want people to read your book, which is, I understand that.
    0:07:02 You have such an interesting background.
    0:07:08 Let me fast forward to March 2019, and you know what questions is coming.
    0:07:13 You write this piece recommending the impeachment of Donald Trump.
    0:07:17 Just tell me, when you write a piece like that at The Atlantic, what the hell happens
    0:07:18 to you?
    0:07:24 Do you just get shitloads of angry emails, and what happens when you do something like
    0:07:25 that?
    0:07:26 Yeah.
    0:07:32 So as an argument, I backed my way, and I started writing a piece about President Andrew
    0:07:36 Johnson, and the first impeachment, I thought, “What could I learn from this history?”
    0:07:40 And by the time I was done with the research, I thought, “Well, I’ve learned a big thing
    0:07:45 here,” which is, “This is an important and valuable process, and I got to lay that out.”
    0:07:50 It’s actually something that Congress should be taking much more seriously than it has.
    0:07:51 And then I published that.
    0:07:56 I threw it out into the world, and discovered that not everybody agreed with me on this,
    0:08:02 in fact, a lot of the President’s ardent supporters let me know in detailed and graphic
    0:08:06 ways just how profoundly they disagreed with me about this.
    0:08:08 And some of that could be laughed off.
    0:08:14 Some of that was detailed and threatening in ways that posed a direct risk to safety.
    0:08:19 Unfortunately, our political atmosphere means that these things often move in really unpleasant
    0:08:23 directions if you’re going to make a bold claim that the backlash can be switched in
    0:08:24 fears.
    0:08:31 Even today, when you hear the candidate to run the FBI or the Attorney General is saying,
    0:08:35 “Now we’re going to hunt down all Donald Trump’s enemies,” you’re probably on that
    0:08:37 enemies list, right?
    0:08:41 So, I mean, right after they arrest Nancy Pelosi, are they going to come for you?
    0:08:44 Do you have any paranoid thoughts like that?
    0:08:47 I think everybody in my line of work has paranoid thoughts right now.
    0:08:52 It’s not a subject I like to dwell on a whole lot, because my ultimate responsibility is
    0:08:53 to our readers.
    0:08:58 And the articles we assign, the reporting that we do, it’s in the interest of pursuing
    0:08:59 the truth.
    0:09:04 And you don’t want your selection of stories to be shaped by too many thoughts about how
    0:09:06 people are going to react to it.
    0:09:10 You select the stories that are worth going after, you pursue them wherever the facts
    0:09:13 lead you, and then you owe it to your readers.
    0:09:18 I owe it to our readers to write whatever it is that I come to as a conclusion without
    0:09:21 fear of favor, without worrying about what the consequences will be.
    0:09:26 Well, maybe you’ll be roomies with Heather Cox Richardson.
    0:09:31 Think of the conversation that two of you could have at night, that would be a great
    0:09:32 conversation.
    0:09:34 I’d be a little intimidated.
    0:09:39 Heather was on my doctoral committee, and I already had the pastor judgment once and
    0:09:45 would worry about what she’d say about my latest work.
    0:09:50 Back then, when you wrote that story, I think the attitude of many people was that impeachment
    0:09:51 is going to work.
    0:09:56 It’s going to prevent the abuse of the Constitution, et cetera, et cetera.
    0:10:00 But obviously, we’ve been proven wrong twice.
    0:10:02 So what happened?
    0:10:08 Going into that, there was much more optimism coming out, two-time impeachment, and now
    0:10:09 reelected.
    0:10:11 Like, how do you explain that?
    0:10:12 It’s a great question.
    0:10:19 I think one problem that we’re all grappling with is that the founders, when they designed
    0:10:25 the Constitution, expected the branches of government to be jealous of their powers.
    0:10:30 They were balancing the branches against each other, and they just assumed that if you had
    0:10:35 an executive who was pushing the boundaries of what the executive should do, and then
    0:10:39 stepped way over the line, that the legislative branch would say, “Whoa, hold on there.
    0:10:41 We may agree with you on policy.
    0:10:45 We may like some of what you’ve done, but you’re upsetting the system.”
    0:10:49 And so it’s our job, our constitutional responsibility to push back at that.
    0:10:54 They didn’t count on the kind of toxic partisanship that has really come to predominate in this
    0:10:59 country where people tend to see things more through that partisan lens than through the
    0:11:00 constitutional one.
    0:11:05 And we’re all grappling with what that means because the basic checks and balances that
    0:11:09 were built into the Constitution, they’re not going to work in a highly partisan atmosphere.
    0:11:14 The only kind of checks right now we have is to the inauguration committee, and the only
    0:11:18 kind of balances, how much is a billionaire worth?
    0:11:21 That’s checks and balances circa 2025.
    0:11:25 And now Al Green is looking into doing this for number three, right?
    0:11:30 Trump has a higher probability of a three-peat than the Kansas City Chiefs.
    0:11:31 Wow.
    0:11:34 You know, that’s an interesting thought, right?
    0:11:38 Because the Kansas City Chiefs went out there and everybody knew what the outcome was going
    0:11:43 to be before the first kickoff, and by the end, it was not what people had expected.
    0:11:49 What can happen, and this is a lesson that politicians have repeatedly learned, is that
    0:11:54 you’re riding high, you think the public’s behind you, you feel invulnerable.
    0:11:57 And that’s precisely when people tend to overstep and overreach.
    0:12:02 The check and balance that is still there, that still operates, is the participation
    0:12:04 of the American people.
    0:12:07 And I think in this administration, when it runs up against limits, that’s where it’s
    0:12:08 going to find them.
    0:12:12 You can be Donald Trump and order your attorney general to charge somebody with a trumped
    0:12:16 up crime, but they still have to go to a grand jury and get an indictment, which means that
    0:12:22 you have to persuade a dozen ordinary Americans that there’s been at least enough evidence
    0:12:24 to charge somebody with a crime.
    0:12:27 Then you got to go in front of another jury and you got to secure the conviction.
    0:12:34 And again, that puts the ball back in the hands of ordinary Americans who tend to not
    0:12:38 like to shield what to do, who tend to like to form their judgments.
    0:12:44 I would expect that if there is a check on Donald Trump’s pushing the boundaries of executive
    0:12:46 authority, it’s not going to come from Congress.
    0:12:51 And it will only be sustained if it comes from the courts if ordinary Americans make
    0:12:55 clear their own views and their own fidelity to the Constitution.
    0:12:56 So I want to emphasize this point.
    0:13:02 So you’re saying that if the courts fail because the courts have no real way to, I mean, what’s
    0:13:04 the U.S. marshals going to do?
    0:13:06 They’re going to invade the White House, right?
    0:13:12 So if the courts fail because they don’t have much power to enforce.
    0:13:18 But you are still optimistic because ultimately it is the will of the American people that
    0:13:19 will survive.
    0:13:25 I have a lot of faith in the American people to eventually do the right thing when they’ve
    0:13:27 run out of all their options.
    0:13:32 But ultimately our democratic system does not depend on a document.
    0:13:37 It doesn’t depend on the virtues of the politicians that they put in office.
    0:13:38 Thank God for that.
    0:13:44 I imagine if our democracy rested on politicians being virtuous, it would have been over a
    0:13:45 long time ago.
    0:13:48 It really rests on the extent to which we believe in each other.
    0:13:52 And as long as Americans are committed to our common project, I tend to think that there
    0:13:57 will be elections that put people in office with whom I disagree and elections where I’m
    0:13:58 happier about the result.
    0:14:02 But that’s what will make democracy survive is the American people being thrown into that
    0:14:04 composite.
    0:14:23 Yoni, every part of my body that can be crossed is crossed right now, hoping you’re right.
    0:14:29 Recently, I got into a discussion with a history professor and I said, like right now, if you
    0:14:36 go to a history class in college or high school, they’re teaching you about Samuel Jackson
    0:14:41 or the original framers of the Constitution and they’re going back hundreds of years and
    0:14:46 trying to opine and trying to interpret what happened.
    0:14:53 But it seems to me that we may be living the most important and interesting time ever in
    0:14:54 American history.
    0:14:59 So I said, why are you constantly referring to the past?
    0:15:05 You should just be studying current events every day now because 200 years from now people
    0:15:08 are going to be looking back and saying, who was this Donald Trump?
    0:15:09 How did it happen?
    0:15:12 And the history professor said, you cannot do that.
    0:15:17 You have to use history to understand the present.
    0:15:23 So we have to teach about Clinton and Nixon and Jackson in order to understand today.
    0:15:29 So do you agree with that or can history today in such an interesting time just be the study
    0:15:31 of current events?
    0:15:36 When I was a boy, I sometimes resented that I didn’t get to live through any great momentous
    0:15:37 events.
    0:15:42 There were no wars raging, there were no, not in the Great Depression.
    0:15:47 It’s the kind of childish thing a lot of us are prone to and then all of a sudden you
    0:15:52 find yourself in the middle of very interesting events and create just a small hint of normalcy.
    0:15:56 It’s a tough moment to be living through and there’s enough to see every day that you could
    0:16:00 occupy yourself just chronically in what we see unfolding around us.
    0:16:03 But the past is actually really valuable.
    0:16:04 It’s in two ways.
    0:16:08 One is it helps us understand how we’ve gotten to where we are.
    0:16:14 But the other way that you can look at the past is as a palimpsest of possibilities.
    0:16:18 So much of what we see at present can feel for ordained.
    0:16:21 It can feel as if there’s no other option.
    0:16:22 This is the way things are.
    0:16:24 This is the way things were meant to be.
    0:16:27 And when you go back into the past, it’s a strange world.
    0:16:31 People did things really differently and you come to understand that the way we do things
    0:16:38 today is as much a result of accident of contingency as it is of inevitability.
    0:16:42 And to me, that gives me a lot of hope in this moment because it means that the things that
    0:16:47 feel like historical inevitabilities, things that feel as if they’re bound to happen, that
    0:16:51 we’re stuck on this one track and we’re barreling it toward the future.
    0:16:53 That’s not how the past is usually unfolded, right?
    0:16:58 Things happen unexpectedly, contingent events intervene.
    0:17:04 People organize themselves and decide collectively to make change in ways that nobody had anticipated.
    0:17:09 And when you look back into that kind of history, I think it’s not just about explaining how
    0:17:11 we got to this moment.
    0:17:14 It’s also a way of imagining other directions we could take.
    0:17:19 If we’re sitting here trying to imagine directions and a podcaster says to you, “So yes, you’re
    0:17:20 a historian.
    0:17:22 You understand what happened in the past.
    0:17:24 You understand what’s possible now.
    0:17:28 You’re deputy executive editor of The Atlantic.”
    0:17:36 So give me some practical tips about what can I do to help preserve the America I love?
    0:17:37 Yeah.
    0:17:42 I can’t give any simple solutions because it’s not a simple problem that we face.
    0:17:47 The first thing I’d suggest is actually get involved with your community at the local
    0:17:48 level.
    0:17:50 That’s the place to start.
    0:17:56 And by involved not tweeting or posting or clicking like on somebody else’s post, too
    0:18:02 often we become political hobbyists who follow politics as if we were following the NFL.
    0:18:07 And you’re sitting on your couch cheering for the quarterback who throws the deep strike
    0:18:12 and feeling as if you’re putting on that special game day jersey made a big difference.
    0:18:14 It’s fandom, right?
    0:18:18 That’s really different than going out there on the field yourself.
    0:18:23 And so the first way to make a difference is to stop being a fan, stop being somebody
    0:18:29 who’s a spectator who’s doing this on social media and to start be a participant, to come
    0:18:35 off the bench to say, “Okay, I’m going in and maybe I can’t fix the world, but I can
    0:18:39 make a difference with my local school board.
    0:18:43 I can make a difference with something that’s happening in my local community.
    0:18:44 I can get back.
    0:18:47 I can find a way to affect positive change in the world immediately around me.”
    0:18:51 And I think that’s tremendously empowering if it changes our whole attitudes.
    0:18:56 If you’re out there making a positive change in the world, other possibilities open up.
    0:18:59 So that’s the second thing is like to think about how to scale that change.
    0:19:04 If you have people who are really invested in the country, not as it is, but as they
    0:19:07 think it should be, as they think it could be, and they’re willing to work together in
    0:19:13 order to realize that vision, and they start to hook up with each other, they start to
    0:19:14 build.
    0:19:17 We’ve seen too many social movements in the last couple of decades that call millions
    0:19:20 of people out into the streets and they feel as if they’re going to change everything.
    0:19:23 And then everybody goes home and there’s no infrastructure there.
    0:19:26 There’s not weekly meetings where somebody’s keeping the minutes and somebody else is making
    0:19:27 a motion.
    0:19:29 That’s how Americans used to affect social change.
    0:19:32 They built this infrastructure slowly from the ground up.
    0:19:33 It was hard work.
    0:19:37 It was difficult work, but it meant that when something big happened, there was an infrastructure
    0:19:38 to activate.
    0:19:42 It meant that after everybody went home from the rally, there was follow-up and they said,
    0:19:44 “Hey, and on Tuesday, please write to your senator.”
    0:19:48 And on Wednesday, we’re looking for people to come testify to the local city council.
    0:19:51 Without that infrastructure, it’s really, really hard no matter how well-intentioned
    0:19:53 people are to affect change.
    0:19:57 So you start at the local level, you hook up with other activists, other people who are
    0:20:01 just ordinary Americans trying to make the world a little bit better, and you create
    0:20:06 that infrastructure, and then ultimately it scales to the national level where politicians
    0:20:09 are really reactive, craven creatures.
    0:20:13 When they see that people are well-organized, when they’re articulating what they want,
    0:20:17 it doesn’t actually take a majority of the population to move.
    0:20:21 It takes a large chunk of the population that makes it clear that it has a set of priorities
    0:20:25 that they will hold politicians accountable for pursuing.
    0:20:29 And politicians will respond to that incentive 10 times out of 10.
    0:20:33 I think it’s one thing that Donald Trump has done really well is he’s made it entirely
    0:20:39 clear to all Republican elected office holders that his voters will respond to him, they
    0:20:43 will show up, they will vote, and they will vote against the people who cross them.
    0:20:48 If you want to push back against that, you’ve got to show that you can be equally powerful
    0:20:51 at organizing from the bottom up.
    0:20:54 Let’s switch to your book for a second.
    0:21:01 All right, so walk me through the gist of your book stuck about how the lack of mobility
    0:21:08 is a key factor in American society today, so unstuck my mind about stuff.
    0:21:11 I started writing this book more than a decade ago.
    0:21:15 I was living in Cambridge, I was in an apartment, it was already getting a little too small
    0:21:19 for my family, and I could look out the window at the streets around me.
    0:21:23 And I knew as a historian something about the neighborhood I was living in, it was a
    0:21:24 special neighborhood.
    0:21:29 For a hundred years, it had been a neighborhood where the children of immigrants moved in
    0:21:31 and moved up.
    0:21:35 One wave after another, after another, had gotten onto that bottom rung of the American
    0:21:37 ladder of opportunity, and they’d kept climbing.
    0:21:39 They started in that neighborhood, and they kept going.
    0:21:44 And by the time I’d lived there, I could look out that window, and I mostly saw young professionals
    0:21:45 walking by.
    0:21:49 The city I was living in had lost two-thirds of its kids, families couldn’t afford to
    0:21:53 live there anymore, and I thought, “This is really weird.
    0:21:59 How was it able to accommodate all that growth for all those years and bring in so many different
    0:22:02 people seeking opportunity in America and help them find it?”
    0:22:04 And now it can’t do that anymore.
    0:22:08 Now the people I’m talking to are moving out, the pastors at the local churches were telling
    0:22:12 me that their parking lots fell on Sunday because their parishioners had all moved to
    0:22:13 other communities.
    0:22:16 They’d drive back on Sunday, but there was nobody to fill the pews.
    0:22:20 Something had gone very badly wrong in this place, and I wanted to know what it was, and
    0:22:22 I started digging.
    0:22:29 And what I landed on eventually was that we had given communities a set of tools that
    0:22:34 had broken the most powerful part of the American idea.
    0:22:40 That was that you had the opportunity as an individual to move toward opportunity and
    0:22:45 to leave the circumstances of your birth, the identities you’d inherited.
    0:22:46 You had the option.
    0:22:49 You could embrace them, or you could build your own identity.
    0:22:54 You could stay where you were, or you could move someplace new.
    0:22:58 And over and over and over again, the people who moved someplace new, they thrived, their
    0:23:02 children thrived, they were able to go toward the new opportunities that were opening up
    0:23:05 in some other part of the country and some other part of their own community.
    0:23:10 And as long as we gave people the chance to do that, this society became more equal over
    0:23:11 time.
    0:23:14 It spread rights more broadly over time.
    0:23:18 And as we’ve rolled that back over the last 50 years and really priced people out of the
    0:23:20 prosperous places, it’s broke.
    0:23:23 I mean, why can’t somebody move?
    0:23:29 Because my experience, I moved from Honolulu to why I went to undergraduate, then I moved
    0:23:34 to LA, then I moved to Orange County, then I came back and I went to San Francisco, I
    0:23:40 went to Atherton, I went to Santa Cruz, I went to Watsonville, I moved six, seven times.
    0:23:44 So what is preventing people from moving?
    0:23:45 It’s not like there’s immigration.
    0:23:49 You can’t move to Texas unless you get a resident card or something.
    0:23:53 Yeah, no, I love the way you laid out that sequence of moves.
    0:23:57 I love asking people for their stories and I bet a lot of your listeners have stories
    0:24:01 like that themselves where they moved many times in their lives.
    0:24:04 And those are very American stories.
    0:24:07 It used to be the case in this country that it was like you needed a permit.
    0:24:12 If you moved into a community in America in the colonial period, they could warn you out.
    0:24:17 Even if you owned a house, even if you’d rented property, even if you had a job, they could
    0:24:20 deliver a notice to your door that said, “We don’t want you here.”
    0:24:21 And they did it.
    0:24:22 They did it routinely.
    0:24:26 They did it often to poor people, they did it to racial minorities, they did it for
    0:24:29 people who were moving in where there was already a blacksmith in town and they didn’t
    0:24:30 want a second one.
    0:24:34 This was like European societies, it was a very closed society.
    0:24:36 You couldn’t just live where you wanted.
    0:24:38 You needed the permission of the community to accept you.
    0:24:43 And then right around 1800, we launched this legal revolution for the first time in world
    0:24:44 history.
    0:24:49 Instead of the communities choosing their people, in America we say, “People can choose
    0:24:50 their own communities.”
    0:24:56 If you can find a place to live in that community, you can establish residents in that community,
    0:24:59 not because anybody gave you permission, but just because you decided it was where you
    0:25:00 were going to live.
    0:25:03 Residents will be a matter of intent rather than acceptance.
    0:25:08 That was like a revolutionary thing, right, that communities no longer got to function
    0:25:11 like members of the clubs, but they used to.
    0:25:12 So that was what we got right.
    0:25:18 And then what we got wrong was that after 100 years of remarkable fluidity, and these
    0:25:23 are the, in the 19th century, maybe one out of three Americans was moving every year.
    0:25:25 Today it’s fallen to one out of 13.
    0:25:30 The thing that shifts is that we give communities a whole new set of tools.
    0:25:36 And it starts actually, the very first tool starts in 1885 in Modesto, California, where
    0:25:42 the town really, really doesn’t want any Chinese immigrants living in its borders.
    0:25:45 And they try all kinds of ways to get rid of the Chinese.
    0:25:47 They try arson, burning down their buildings.
    0:25:50 They try vigilante violence.
    0:25:52 They come in, they round them up, they beat them.
    0:25:56 And they can’t force them out because those Chinese residents want the same thing everybody
    0:25:57 else wants, right?
    0:25:58 They want opportunity.
    0:25:59 They want better lives with their kids.
    0:26:01 They can see that Modesto is going to give that.
    0:26:03 And then they hit on this really ingenious solution.
    0:26:07 They say, well, we can’t pass laws that discriminate against the Chinese because the courts won’t
    0:26:09 let us do that.
    0:26:13 And beating them up hasn’t worked, burning them out hasn’t worked.
    0:26:17 But we could pass a law in this town, which says that the laundries, which were the only
    0:26:22 thing that would employ the Chinese at that point, they all have to be in this one narrow
    0:26:27 part of town, China town, we’ll push them back in.
    0:26:29 And that was the first American zoning statute.
    0:26:32 It’s the first time that a municipality passes a zoning rule.
    0:26:36 It was to push the Chinese out of Modesto and back into China town.
    0:26:39 And that tool proves remarkably powerful.
    0:26:45 So after 100 years of almost unlimited mobility, America starts to roll it back.
    0:26:52 But wouldn’t somebody say that the reason why there are zoning regulations is to prevent
    0:26:58 excessive traffic or excessive population or something like that?
    0:27:00 They’re not going to say it because they’re Chinese.
    0:27:03 So how do they do it today?
    0:27:08 Yeah, the amazing thing about 1885 is they actually said it.
    0:27:11 This is a pretext, which is sort of, as a historian, it’s a wonderful thing to see somebody
    0:27:13 say the quiet part loud like that.
    0:27:17 But yeah, there’s lots of good reasons to regulate land use.
    0:27:22 Where you run into trouble is where you let people create one set of rules for really
    0:27:28 rich areas and another set of rules for the poorer areas because always those rules will
    0:27:30 be rigged against the poor.
    0:27:36 And today, the zoning rules that go into affluent areas are often very well-intentioned.
    0:27:40 They’re about protecting the environment, protecting the history of the community.
    0:27:45 They’re about worrying about traffic and light and shadow.
    0:27:47 There’s always a good reason not to build.
    0:27:51 But the way I’ve come to think of this is it’s a little bit like dropping an apple
    0:27:53 core on the sidewalk.
    0:27:58 If I drop one apple core on the sidewalk, I’m not really making the world much worse off.
    0:28:01 If everybody drops through apple core on the sidewalk, pretty soon that sidewalk gets a
    0:28:05 rat infested, smelly, disgusting, right?
    0:28:06 It’s the same thing with blocking buildings.
    0:28:11 For zoning rules, you can create rules that apply really well in any individual circumstance.
    0:28:14 And if you block one building, that’s not a big deal.
    0:28:17 If you block all the buildings, then there’s no longer a way in.
    0:28:21 And so these rules that come out of a history of discrimination get sort of laundered over
    0:28:24 time where we come up with polite ways to talk about it.
    0:28:25 You’re right.
    0:28:29 Nobody these days says, “Oh, I’m zoning this for single family homes because I don’t want
    0:28:32 any Hispanic immigrants moving into my community.”
    0:28:37 Instead they say, “I’m zoning this for single family homes because apartment buildings are
    0:28:40 not a fit for the character of this place.”
    0:28:45 But they sometimes mean that they’re more worried about the characters in those apartment
    0:28:46 buildings.
    0:28:50 There is a way in which we’ve come up with polite ways to talk about segregating ourselves
    0:28:52 economically in America.
    0:28:55 If you segregate yourself economically, it usually means segregating yourself racially
    0:28:56 too.
    0:29:00 Now, you mentioned three ways to deal with it.
    0:29:04 This is consistency, tolerance, and abundance, right?
    0:29:10 Now, if I may paraphrase those three, so consistency means that there’s not local regulations.
    0:29:14 It’s consistent for the entire state, at least, let’s say.
    0:29:19 And then tolerance is tolerance of differences and abundance means create more housing.
    0:29:24 But as I read that, I said, “Man, this guy, can you name three more impossible things
    0:29:25 to do?”
    0:29:29 You’re going to go to this progressive mafia and say, “All right, so we’re going to have
    0:29:31 no more local zoning.
    0:29:36 We’re going to have you understanding other people’s frameworks and skin colors and religions
    0:29:40 and genders and sexual orientation, and we want you to build more housing.”
    0:29:44 Man, I hope you don’t run for office on that platform.
    0:29:49 Yeah, in some ways, it’s a tough sell, but I’ll tell you this.
    0:29:54 If you walk up to somebody and say, “Do you want multi-family housing on your block?”
    0:29:56 Usually they’ll say, “No, we’re all change-a-first.
    0:29:58 We’re used to the way things are.”
    0:30:02 And if you say, “Should there be an apartment building across the street?”
    0:30:03 And most people say, “No, I don’t want to.”
    0:30:07 But that’s not the only way you can ask the question.
    0:30:11 You can ask them, “Do you think that your neighborhood should be a place where young
    0:30:13 families can still move in?
    0:30:18 Do you think that the service workers who are making your life possible, the daycare
    0:30:23 workers and the hospital nurses and the firefighters, should they get to live in the same town
    0:30:27 where they’re providing services on behalf of the people?
    0:30:31 Do you think that your community should be welcoming to people of diverse backgrounds
    0:30:33 or reserved for the rich?”
    0:30:39 If you ask the questions that way, Americans will overwhelmingly say, “No, no, I want opportunities
    0:30:40 for families.”
    0:30:44 And if the price I have to pay is that there’s an apartment building in a neighborhood of
    0:30:47 single-family homes, I’m happy to pay it.
    0:30:52 And so a lot of this depends on whether you see the problem as one isolated building where
    0:30:56 you don’t want the change, or whether you can help people zoom out and see the bigger
    0:31:01 picture and say, “This was a country that grew prosperous and diverse because it let
    0:31:03 people move toward opportunity.
    0:31:04 We’ve broken that.
    0:31:06 It’s embedded in our politics.
    0:31:11 It is the thing that, above all else, I genuinely believe, drove support for Donald Trump.
    0:31:16 It was the rage he tapped into, the sense that people had, that there were islands of
    0:31:19 prosperity that had walled themselves off from the rest of the country.
    0:31:21 And he was angry at the right people, right?
    0:31:22 He was championing their costs.
    0:31:25 People really felt stuck in their lives.
    0:31:27 And if you put it to them like that, it’d be like, “Do you want to fix America?
    0:31:29 Do you want to restore the American dream?
    0:31:33 What you have to do is let somebody build in your neighborhood so that new families
    0:31:34 can move in.
    0:31:36 The firefighters are supposed to live.”
    0:31:38 My experience with these is people say, “Yeah, I wanted to pay that price.
    0:31:39 That’s a good trade.”
    0:31:46 I mean, you must run around with different people than I do, Yoni, because if I ask people
    0:31:52 that I know, and let’s take the extreme example of Atherton, California, the most expensive
    0:31:57 zip code in the United States, if I said to them, “Don’t you want to make it so that
    0:32:02 young families can move here so your service workers don’t have as difficult a commute
    0:32:03 and blah, blah.”
    0:32:04 They would say, “Nope.
    0:32:05 Nope.
    0:32:06 I like it.
    0:32:09 I want minimum zoning of two acres, and I don’t want any affordable housing.
    0:32:10 I don’t want any more traffic.
    0:32:13 I’m already spending too much time in my G-Class.
    0:32:16 I need to get a new set of friends, Yoni.”
    0:32:19 No, it’s a good objection that you’re raising, right?
    0:32:22 And I don’t mean to sugarcoat this too much.
    0:32:26 A hundred years ago, and it’s really that reason, we gave towns a new set of tools
    0:32:28 they’d never had before.
    0:32:29 Zoning wasn’t legal.
    0:32:34 When people started passing zoning laws, they knew it was unconstitutional, that they were
    0:32:38 deliberately trying to spread it around the country so fast that by the time we got to
    0:32:41 the report, it would be too widespread to undo.
    0:32:45 The drafters of zoning rules understood that what they were undertaking was like a legal
    0:32:50 revolution and that if the courts heard about it too early, it wouldn’t take.
    0:32:51 They pulled it off.
    0:32:52 They spread it.
    0:32:55 By the time the Supreme Court hears the first zoning case, Washington, D.C. is zoned, and
    0:32:59 they’re walking to court, to their jobs, through a zoned city.
    0:33:04 And it comes to seem unimaginable that you could roll it back, but it’s a recent change.
    0:33:08 And it came from states delegating powers down to local communities.
    0:33:13 And what we’ve seen over time is that the richer those communities are, the better educated
    0:33:20 their inhabitants are, the better able they are to use these rules in order to create
    0:33:22 a members-only club back out of their community.
    0:33:26 I remember we talked about America starts as members-only clubs, these communities that
    0:33:29 could warn you out if you were poor, if you had the wrong skin color, like, we’re back
    0:33:31 to that now.
    0:33:35 Communities today have figured out how to build new walls around themselves, how to wall themselves
    0:33:36 off.
    0:33:38 But there’s no reason that they have to have that power.
    0:33:40 They didn’t historically have that power.
    0:33:44 When they got that power, everyone had initially thought it was unconstitutional.
    0:33:45 And it’s up to the states.
    0:33:49 The states have the capacity to say, most of the voters in the state don’t get to live
    0:33:50 in Atherton.
    0:33:54 And what we’re going to do is try to create a society that shares prosperity more broadly.
    0:33:59 If Atherton’s got great schools, then let’s build more housing in Atherton so that more
    0:34:01 kids get to go to those schools.
    0:34:05 And that will be good for all of us, because those kids, they’re going to grow up to be
    0:34:10 the next generation of venture capital barons out on Sand Hill Road, right?
    0:34:15 There’s a way in which, you know, rather than creating an elite that’s self-perpetuating,
    0:34:20 if you allow people to move, you can create a genuinely meritocratic society that gives
    0:34:23 new opportunities for new waves of people to move up.
    0:34:25 Up next, unremarkable people.
    0:34:30 I think this country is an amazingly resilient place.
    0:34:33 America will die if it chokes itself off.
    0:34:38 If it loses its optimism, if it loses its ability to innovate, if it loses its openness
    0:34:39 to change.
    0:34:41 We’re at some risk for that right now.
    0:34:44 That is the direction, I think, in which Donald Trump has pointed us.
    0:34:50 And so I don’t mean to suggest that America is invulnerable, but I think that fundamentally
    0:34:57 most Americans view this as a land of opportunity, think that the country is stronger because
    0:35:02 it has their neighbors in it, too, and as long as we don’t lose sight of those fundamental
    0:35:06 values, I think America will survive a heck of a lot longer than I will.
    0:35:24 Thank you to all our regular podcast listeners.
    0:35:27 It’s our pleasure and honor to make the show for you.
    0:35:33 If you find our show valuable, please do us a favor and subscribe, rate and review it.
    0:35:39 Even better, forward it to a friend, a big mahalo to you for doing this.
    0:36:06 And listening to “Remarkable People” with Guy Kawasaki.
    0:36:14 I’m going to be working at a Starbucks in Hiroshima right now.
    0:36:20 What’s the consequence of trying to prevent people from coming to America?
    0:36:24 So first you want me to advocate apartment buildings in Atherton, and now you’re asking
    0:36:26 me to go after immigration guys.
    0:36:27 Exactly.
    0:36:32 No, but it’s a good question and it’s not unrelated, right?
    0:36:37 Whatever you think our immigration policy should be, whatever the right level of immigration
    0:36:41 is, whatever the right enforcement mechanisms are, I don’t think anyone doubts for a moment
    0:36:43 that immigration is one of America’s great strengths.
    0:36:48 We have brought so many talented people to this country through the years, and I know
    0:36:53 something about the psychology that comes with mobility.
    0:37:01 People who feel stuck, who are born someplace and want to leave and can’t, they change
    0:37:02 psychologically.
    0:37:09 They grow more cynical, more pessimistic about the world, more hostile to outsiders.
    0:37:14 They tend to see the world as a zero-sum game in which anyone new coming into their community
    0:37:18 is dividing the same pie into smaller slices.
    0:37:24 And that frankly describes a good number of Trump supporters who were much more likely
    0:37:27 than Democratic voters to still live in the communities in which they were born, much
    0:37:31 more likely to report that they wanted to move than they could, and much more likely
    0:37:37 to be really resentful of immigration, to see it as diminishing their possibilities.
    0:37:44 If you let that same person move toward opportunity, they get a sense of agency in their own lives.
    0:37:48 Suddenly instead of the world being on them, they’re taking control of their own lives.
    0:37:49 They’re making their own decisions.
    0:37:50 That’s really empowering.
    0:37:55 It’s not just empowering, it makes them more optimistic and it does something else.
    0:37:57 They stop seeing the world as a zero-sum game.
    0:38:02 They start to understand that they’ve moved toward opportunity, the place where their
    0:38:05 living will thrive if others have that same chance.
    0:38:08 They start to see the pie getting bigger, and instead of somebody else taking a slice
    0:38:13 out of that pie diminishing their slice, they understand that together they can make that
    0:38:17 pie big enough that everybody gets a larger slice than they started off with.
    0:38:22 It sounds a little counterintuitive, but one of the things that has changed the American
    0:38:28 debate over immigration is that more and more Americans are stuck where they are and feel
    0:38:33 cynical about the world because they’re not getting in their country the kinds of opportunities
    0:38:34 they expect it to have.
    0:38:40 If you can restore that sense of agency, of mobility, you can restore the kind of optimism
    0:38:47 that had for a long time, you will do unique American ability to absorb new waves of immigrants
    0:38:49 and to build a cohesive country.
    0:38:51 Let me make sure I got this right.
    0:38:59 Are you saying that if Americans had a greater sense, and it was actually true of mobility,
    0:39:05 that we would be more empathetic and tolerant of immigrants moving into America?
    0:39:07 That is what the psychologists tell me.
    0:39:12 When you look at people who have moved in the last year, they feel better about the world.
    0:39:17 They are more tolerant of others, they’re more likely to reach out to others of diverse
    0:39:22 backgrounds and when you look at people who want to move and can’t, the opposite things
    0:39:23 are true.
    0:39:24 All right.
    0:39:28 So I’m going to switch gears again, don’t worry, we’ll let you plug your book at the
    0:39:29 end.
    0:39:34 Okay, so now, do you believe that the, because I caught this sentiment earlier in your writing
    0:39:45 that the Republican Party is fighting a battle they cannot win against the pure math of demographics.
    0:39:54 But it seems to me, since you made that kind of sentiment 2019-2020, it seems to me that
    0:39:59 they have disproven that, that they are not fighting a losing battle.
    0:40:03 They own all three branches, they theoretically are more popular than ever.
    0:40:07 So what happened to this demographic inevitability?
    0:40:09 Yeah, that’s a great question.
    0:40:14 And there were a lot of people out there suggesting that there was some irresistible demographic
    0:40:18 tie that’s going to sweep Republicans from power.
    0:40:24 I think the most interesting thing that Donald Trump has done is found ways to build his
    0:40:30 support, particularly among young men who don’t have the benefits of a college education.
    0:40:32 And he’s done that across racial boundaries.
    0:40:35 In some ways, we should all be happy about this.
    0:40:40 American politics was becoming increasingly racial polarized and Donald Trump has depolarized
    0:40:41 it a little bit.
    0:40:47 In other words, it’s really worrying because some of the appeal that he’s exercised is
    0:40:50 about enlarging.
    0:40:53 He did what the Republicans I thought needed to do, just not the way I was hoping they would
    0:40:54 do it.
    0:40:55 Right?
    0:40:58 He enlarged a sense of who could be a Republican.
    0:41:03 He said, “I’ll take people of all backgrounds, of all colors, we’ll build that kind of party,
    0:41:06 and we’ll do it through our hatred and resentment of them.”
    0:41:08 And so he managed to switch the us and them.
    0:41:15 He enlarged the Republican us by targeting them, progressives, liberal elites, and that
    0:41:18 was a very effective political message for Donald Trump.
    0:41:24 It still ultimately doesn’t leave the Republicans in a great spot where they have struggled
    0:41:27 when Donald Trump is not at the top of the ticket.
    0:41:31 He has fused this coalition of resentment together, but it’s not a coalition that holds
    0:41:33 in midterm elections.
    0:41:37 It’s not a coalition that holds in gubernatorial races.
    0:41:43 Where they continue to face this problem that Trump can weld these folks together, but there
    0:41:45 are other politicians who don’t seem able to do it.
    0:41:52 I need a Harvard educated brain or Harvard professor to explain to me how Donald Trump
    0:41:59 did this because from the outside looking in, I completely agree with the demographic
    0:42:05 inevitability, but then I’ve learned that young black men and young Hispanic men and
    0:42:10 young Muslim men and all that, they voted for Donald Trump.
    0:42:14 Explain that to me that this guy says that the Mexicans are rapists and drug dealers
    0:42:19 and the black people are all like criminals and the Muslims are terrorists, but their
    0:42:21 young people are voting for me, huh?
    0:42:23 I’m having an out-of-body experience here.
    0:42:27 I only went to Stanford, I didn’t go to Harvard, so explain this to me.
    0:42:32 I think this is a question a lot of people have, and there’s two ways to think about
    0:42:34 political preferences.
    0:42:38 One is shaped by a bunch of disqualification, so you look at it and you say, “Well, this
    0:42:42 candidate said this and that and the other thing, and I don’t agree with that, I’m not
    0:42:43 going to back him.”
    0:42:48 Another way to think about it is thinking about what they call negative polarization,
    0:42:54 so not what is this candidate and what’s disqualified him, but rather who does this candidate resent,
    0:42:55 who do they hate?
    0:42:57 Do they hate the same people that I hate?
    0:42:59 Are their enemies the same as my enemies?
    0:43:04 And I think for an awful lot of Americans, and you’ll forgive me for this, is one of
    0:43:07 the things I’m getting at in the book, for an awful lot of Americans, there’s a sense
    0:43:12 that something has gone wrong in their lives, particularly young men without college degrees
    0:43:16 don’t have access to the same kinds of jobs that they did a generation ago.
    0:43:19 We don’t have the same kinds of blue collar jobs in this country.
    0:43:22 Donald Trump has talked about that over and over again.
    0:43:26 We don’t offer those young men the same kinds of opportunities.
    0:43:29 60% of college matriculants are now women.
    0:43:32 Women are much less likely to be going to college than their female peers.
    0:43:34 They’re much less likely to wind up with full-time employment.
    0:43:39 They’re much less likely to be able to build the kinds of happy and productive and satisfied
    0:43:40 lives.
    0:43:46 And Trump is a genius for spotting resentment, and he channeled that anger.
    0:43:48 That doesn’t mean that he has any practical solutions.
    0:43:53 It doesn’t mean that he’s given them a vision that can turn their lives around, but it does
    0:43:59 mean that he was able to make them feel seen, and people will overlook a lot in somebody
    0:44:03 — they’ll overlook the things he said, they’ll overlook the things he’s done — if he makes
    0:44:09 them feel as if they are real, they are recognized, that somebody has looked at their pain or their
    0:44:13 suffering, understands it, blames some of the same people that they blame, gives them a
    0:44:16 narrative that explains why it’s happening to them.
    0:44:19 Those are really powerful political forces, and that is one thing I think that Donald
    0:44:23 Trump has done brilliantly that Democrats have really struggled to match.
    0:44:29 I gotta tell you alone, if I had not lived through it, I would not believe it.
    0:44:33 If this happened 200 years ago, I was — this is impossible.
    0:44:36 There’s no way that happened, but, wow.
    0:44:42 Okay, I’m gonna ask you one last heavy question, then I have some short questions.
    0:44:48 And the last heavy question is, what’s your thoughts on if and when America will die?
    0:44:53 I think this country is an amazingly resilient place.
    0:44:59 America will die if it chokes itself off, if it loses its optimism, if it loses its ability
    0:45:02 to innovate, if it loses its openness to change.
    0:45:04 We’re at some risk for that right now.
    0:45:08 That is the direction I think in which Donald Trump is pointing us, and so I don’t mean
    0:45:11 to suggest that America is invulnerable.
    0:45:17 But I think that fundamentally, most Americans view this as a land of opportunity, think
    0:45:23 that the country is stronger because it has their neighbors in it too.
    0:45:28 And as long as we don’t lose sight of those fundamental values, I think America will survive
    0:45:30 a heck of a lot longer than I will.
    0:45:35 Like I said before, every part of my body that can cross is now crossed again.
    0:45:36 Yeah, thank you.
    0:45:39 Okay, so some quickie questions for you.
    0:45:40 Okay.
    0:45:43 First, where do you get your news?
    0:45:48 I get my news from mainstream outlets, so I read as many newspapers and magazines as
    0:45:54 I can, and I like particularly to read magazines and newspapers that publish things I disagree
    0:45:55 with.
    0:46:01 Okay, so tell us, what are the things you disagree with?
    0:46:04 I love reading op-ed pages.
    0:46:09 I love reading really smart reporting that pushes me in some direction I didn’t expect
    0:46:10 to get.
    0:46:16 I already know what I think, but when I open a newspaper, I really like to read something
    0:46:18 that surprises me or tells me what’s wrong.
    0:46:23 Which newspapers are you opening when you look for these op-ed?
    0:46:27 I get The New York Times, The Washington Post, every day at my door, and I do that so I can
    0:46:31 share them with my kids so they can see me not staring at a phone, but actually opening
    0:46:33 a newspaper and reading it.
    0:46:38 I didn’t even know there were print editions.
    0:46:43 What do you think of the work of Katie Drummond and Wired?
    0:46:48 In my mind, Wired was this thing that would talk about artificial intelligence and virtual
    0:46:54 reality, and all of a sudden it’s like The New Washington Post, so what’s going on with
    0:46:55 Wired?
    0:46:59 I love the reporting they’re doing, and it’s a reminder that part of what’s happening
    0:47:06 here is a transfusion of people and values from Silicon Valley into Washington, and Wired
    0:47:12 is uniquely well positioned to cover that because they understand the Valley, they’re familiar
    0:47:17 with the players, and a lot of the outlets that are based in DC, they’re covering it
    0:47:18 like foreign correspondents.
    0:47:22 Wow, the Silicon Valley people, who are they, and what are they up to, but Wired is there
    0:47:24 to bring readers to that store.
    0:47:29 Madison, make a note that we got to go subscribe and pay a subscription to Wired.
    0:47:31 I’ve been forgetting to do that.
    0:47:34 All right, next quick question.
    0:47:39 Do you participate in social media at all, or is just a waste of time for you?
    0:47:41 More than I should.
    0:47:42 I’m on X.
    0:47:43 You’re on X.
    0:47:44 I am.
    0:47:46 You’re a collaborator.
    0:47:47 What?
    0:47:54 Well, I enjoy on X, Blue Sky, on Facebook.
    0:47:59 I enjoy being reminded that other people don’t see the world the way that I do.
    0:48:04 It’s the biggest danger I have as a journalist is sitting in a room with a bunch of other
    0:48:07 people whose views may more or less align with mine.
    0:48:10 If I want to be interesting, if I want to find good stories, I’ve got to constantly
    0:48:15 expose myself to things that might be a little enraging, but at least show me the world through
    0:48:17 a different set of eyes.
    0:48:20 For all of its flaws, that is one thing that social media does beautifully.
    0:48:24 It can give me the perspective of somebody living in a different state, somebody with
    0:48:28 a different education, somebody with a different set of values, and it reminds me that mine
    0:48:30 is not the only way to see it.
    0:48:35 I get the point of read-only access, but are you participating?
    0:48:40 Are you posting and commenting or you’re just using it as a data source?
    0:48:41 Not as much as I did.
    0:48:47 It’s really hard to have a meaningful conversation on social media than it’s just.
    0:48:54 This has been a very, very stimulating episode, and I like to give authors, because Madison
    0:48:59 and I, we’ve authored a few books too, so I just want to give you this opportunity for
    0:49:06 you to pitch stock as your book so that listeners can say, “Well, I got to go read that book.”
    0:49:11 I wrote this book because I wanted to understand what had gone wrong in America, and what was
    0:49:16 fun about it was giving the whole historical art, how we invented this idea of mobility.
    0:49:22 We set Americans loose to define their own identities, that this was the thing that created
    0:49:27 so much social and economic mobility in America, it made us able to welcome people from other
    0:49:28 countries.
    0:49:33 It gave us much of what we consider American values was this outgrowth of this historical
    0:49:38 accent that we had set people loose to define their own lives.
    0:49:42 One little thing in the book that I particularly loved was Discovering Moving Day.
    0:49:47 All the leases in a particular town or city would expire on the same day, and a quarter
    0:49:53 or third half the people would pick up and swap apartments, move houses, switch farms.
    0:49:57 It was an annual ritual that people would come over from Europe just to watch all the
    0:50:03 carts carry the goods through the city going in every direction, and getting the sense
    0:50:09 of what mobility had once meant to Americans, and then seeing how we had accidentally choked
    0:50:10 it off.
    0:50:13 It’s one of those things where it’s like breathing the air, right?
    0:50:14 Take it for granted.
    0:50:16 You take it for granted that you can decide where you want to live.
    0:50:20 It’s easy to take for granted that we have the ability to move someplace new, but when
    0:50:25 you see how quickly we’re losing it and how much is at stake, suddenly you see the world
    0:50:26 a different way.
    0:50:28 At least I did as I wrote the book, and I hope that as people read the book, they’ll
    0:50:32 see their own stories in there, and they’ll see their country in a new country on tomorrow.
    0:50:33 All right, Neon.
    0:50:34 Thank you so much.
    0:50:41 I mean, you listeners, I hope you got these main points about fostering mobility and also
    0:50:47 of remaining optimistic in the future of America, and you can’t just be optimistic.
    0:50:52 You have to actually get involved, and you only suggested rather than just post it, read
    0:50:58 and bitch, you’ve got to get involved and actually take action locally, do something.
    0:51:05 And I will say that for the fourth time, I think I hope you are right.
    0:51:13 And I would tell you, subscribe, pay the subscription for The Atlantic, and wired, and watch what
    0:51:14 he does.
    0:51:19 Maybe if you want to work at The Atlantic, you start commenting on Yoni’s articles, and
    0:51:23 he’s going to reach out to you and give you a job at The Atlantic, and that would make
    0:51:28 another great story for the Remarkable People podcast.
    0:51:29 I’m Guy Kawasaki.
    0:51:32 This has been the Remarkable People podcast.
    0:51:39 Our guest was Yoni Appelbaum, and he is the deputy executive editor of The Atlantic, one
    0:51:41 of my favorite publications.
    0:51:43 So I think he’s helped us be remarkable.
    0:51:49 And my thanks to Madison Nysmer, producer and co-author, Tessa Nysmer, researcher, and
    0:51:54 then the two sound design engineers, which is Shannon Hernandez and Jeff Sey, and we
    0:51:56 are the Remarkable Team.
    0:51:59 I hope we made you a little bit more remarkable today.
    0:52:07 Yoni, for sure, you did, so thank you very much.
    0:52:08 This is Remarkable People.

    From the halls of Harvard to the pages of The Atlantic, Yoni Appelbaum’s story defies conventional career paths. As Deputy Executive Editor and author of Stuck, Appelbaum illuminates how America’s declining mobility is transforming our social fabric and political landscape. Drawing from his unique background as both historian and journalist, he examines the intersection of housing policy, community dynamics, and democratic resilience, offering fresh perspectives on how to reinvigorate the American dream.

    Guy Kawasaki is on a mission to make you remarkable. His Remarkable People podcast features interviews with remarkable people such as Jane Goodall, Marc Benioff, Woz, Kristi Yamaguchi, and Bob Cialdini. Every episode will make you more remarkable.

    With his decades of experience in Silicon Valley as a Venture Capitalist and advisor to the top entrepreneurs in the world, Guy’s questions come from a place of curiosity and passion for technology, start-ups, entrepreneurship, and marketing. If you love society and culture, documentaries, and business podcasts, take a second to follow Remarkable People.

    Listeners of the Remarkable People podcast will learn from some of the most successful people in the world with practical tips and inspiring stories that will help you be more remarkable.

    Episodes of Remarkable People organized by topic: https://bit.ly/rptopology

    Listen to Remarkable People here: **https://podcasts.apple.com/us/podcast/guy-kawasakis-remarkable-people/id1483081827**

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  • Steve Gordon: Inside the California DMV’s Transformation

    Steve Gordon: Inside the California DMV’s Transformation

    AI transcript
    0:00:02 We didn’t make it easy and we should just realize that the
    0:00:04 comparator in the marketplace is Amazon.
    0:00:07 So I talked to my staff and I asked anybody order anything for
    0:00:10 Amazon over the holidays and every hand goes up and says, so when
    0:00:13 you’re thinking that the DMV or government should be different.
    0:00:15 I said, no, we should be good as what we’re trying to do as they
    0:00:17 are, we should make the products are on the shelf.
    0:00:20 We should know that what they want to buy, we should make it easy
    0:00:21 to put it in the car, we should make it easy to pay.
    0:00:25 And again, we have some room to go there, but that’s the
    0:00:25 direction we’re heading.
    0:00:29 Hello, everybody, it’s Guy Kawasaki.
    0:00:33 This is the Remarkable People podcast and today I have a
    0:00:38 guest that if you had told me when I first started getting
    0:00:41 driver’s license in California that someday I would have a
    0:00:46 podcast about Remarkable People and I would bring on the show,
    0:00:50 the person who ran the California State Department of Motor
    0:00:52 Vehicles, I would tell you, you are crazy.
    0:00:55 Because I spent half my life waiting at that frickin’
    0:01:00 office in Redwood City, so I am very proud that this is the
    0:01:02 Remarkable People podcast.
    0:01:04 We’re trying to make you Remarkable and I have the
    0:01:11 Remarkable Steve Gordon, who runs the California DMV and I can
    0:01:15 tell you from personal experience, I love the DMV.
    0:01:18 Not many people might say that, but if you really think about
    0:01:21 it, you’ve had recent experience, but it’s true.
    0:01:25 You’ve had recent experience at the California DMV.
    0:01:27 You would be happy, I’m telling you.
    0:01:31 I want to give a special shout out to my favorite office,
    0:01:34 which is the Capitola California DMV.
    0:01:36 They are so great there.
    0:01:39 So welcome to the show, Steve Gordon.
    0:01:41 Thank you, Guy, glad to be here.
    0:01:45 I am sincere in my praise for the California DMV.
    0:01:49 I’m telling you, I just look forward to registration time,
    0:01:51 I know what it is.
    0:01:55 I’m going to go buy more cars after registering more often.
    0:01:58 We look forward to helping you with that, so thanks.
    0:02:01 And now that I’m getting older, I have to get my license
    0:02:05 renewed more often, so it’s all good.
    0:02:06 But still, it should only be every five years.
    0:02:08 And we’ve simplified.
    0:02:10 You still have to have an eye exam, but no longer do you need
    0:02:11 a written knowledge test.
    0:02:13 So it’s simple.
    0:02:14 Wait, when did that happen?
    0:02:17 Because I know I took the test in an eye exam.
    0:02:20 Just recently, this was probably about six, five months ago,
    0:02:23 where we actually removed the requirement
    0:02:24 for a knowledge test.
    0:02:26 This was popular when we left COVID,
    0:02:29 because we had waved it during COVID.
    0:02:31 And then we brought it back, and there was outrage.
    0:02:33 And then we actually went back and looked at the data
    0:02:36 and saw that very little correlation between passing
    0:02:38 a knowledge test and safe driving.
    0:02:39 So we convinced our administration
    0:02:42 that it’s the right thing to do, and we had good controls
    0:02:44 and other ways to take care of driver safety.
    0:02:47 And we got rid of the exam.
    0:02:48 Yeah, it’s fantastic.
    0:02:52 Wait, so when you say you convinced your administration,
    0:02:53 what does that mean?
    0:02:55 You just call up Gavin as a Gavin.
    0:02:57 It doesn’t matter if people take a knowledge test
    0:03:00 and Gavin says to see, yeah, okay, fine, take it off.
    0:03:01 How does that work?
    0:03:04 No, I think the governor’s got many, many bigger things
    0:03:06 to do than worry about that.
    0:03:08 But we work as part of the administration,
    0:03:10 and we try to make sure that as we make changes,
    0:03:13 that’s very public, and we want to make sure
    0:03:17 that we work with the folks that are in our agency
    0:03:17 and so we want to make sure they’re aware
    0:03:20 of what we’re trying to do, why we’re trying to do it,
    0:03:22 and why we believe it’s the right thing to do.
    0:03:24 And just want to make sure this is,
    0:03:25 government is one of those things that they want,
    0:03:26 no surprises.
    0:03:28 So we want to make sure we socialize it the right way,
    0:03:31 share the data, share the facts, talk about the opportunity,
    0:03:34 and making sure that, of course, the skid degrees
    0:03:36 so we could roll it out and be successful.
    0:03:41 And the state attorney general doesn’t call you up
    0:03:44 and say, listen, we cannot lower the standards
    0:03:48 because somebody who didn’t have the eye exam,
    0:03:50 it is gonna run over a little old lady
    0:03:51 and they’re gonna sue the state
    0:03:56 because we removed the eye exam from the licensing process.
    0:03:57 – We didn’t actually remove the eye exam,
    0:04:00 but we took away is the knowledge test.
    0:04:01 – Oh, the knowledge test, okay.
    0:04:03 – That’s something that people struggle with,
    0:04:06 but these people who’ve written to me and I’ve met with,
    0:04:09 these are people that have been driving for 50, 60 years,
    0:04:11 so it’s nothing they’re gonna learn
    0:04:12 about driving from a knowledge test.
    0:04:13 Even though we simplified it,
    0:04:15 we actually made it more of a video
    0:04:17 so you can see how to drive safely.
    0:04:19 But so that’s the part that we removed
    0:04:21 that we actually, we’ve been studying this
    0:04:22 for many, many years.
    0:04:27 I have a bunch of R&D folks, PhDs that study driver behavior
    0:04:29 and they go back and show you the correlation
    0:04:31 between passing an exam and safe driving
    0:04:33 and there is no correlation.
    0:04:36 So there’s no sensitivity to if you don’t pass the exam,
    0:04:37 you’re gonna be a worse driver.
    0:04:40 Think about when we were 16 year old boys,
    0:04:41 we passed the knowledge exam
    0:04:44 and we were not the best drivers out of the chute.
    0:04:47 Now the iExam you mentioned is still required.
    0:04:48 It’s not actually in statute.
    0:04:49 There are different ways to do the iExam.
    0:04:51 People that are perhaps more fortunate
    0:04:53 that can go to some case lens crafters at the mall,
    0:04:55 not to promote a product or go to Kaiser,
    0:04:57 which I’m a Kaiser customer or somebody else.
    0:04:59 You can actually have that physician send in
    0:05:03 other results of the iExam and satisfy that requirement.
    0:05:05 – Okay, it’s good to know.
    0:05:06 – Yeah, don’t get me in trouble here, guy.
    0:05:08 We’re just starting this discussion.
    0:05:11 – I’ll put in a good word with Gavin for you.
    0:05:12 – Don’t worry.
    0:05:13 – Great, thanks.
    0:05:16 So I just take me back in history.
    0:05:18 So like, how did this come about?
    0:05:21 Did the state of California retain a headhunter
    0:05:24 or did Gavin personally recruit you?
    0:05:27 I don’t even understand how you become in charge of the DMV.
    0:05:28 – I didn’t either,
    0:05:31 but I was gonna semi-retired to take my wife
    0:05:32 would probably say that.
    0:05:34 And we were living in San Jose at the time
    0:05:37 and we’re local newspaper, San Jose Mercury News
    0:05:39 and Aaron Baldassari wrote an article.
    0:05:40 I’m sure it was like the editor said,
    0:05:42 hey, write something.
    0:05:44 So she put an article that I believe the headline was,
    0:05:46 hate the DMV, you could run it.
    0:05:48 And my wife was reading the Mercury News.
    0:05:50 She saw that and she read what was in the post.
    0:05:52 She says, honey, that sounds like you.
    0:05:54 And the implicit thing in there was,
    0:05:57 well, and you don’t seem very busy.
    0:05:59 And so anyway, so I read the article.
    0:06:01 I looked at the governor’s appointment page
    0:06:03 and I’d read a little bit about the DMV and said,
    0:06:04 let’s see what happens.
    0:06:06 And I did not expect anything to happen.
    0:06:07 You put it in this hopper.
    0:06:09 It was very much a government forum.
    0:06:10 There’s a lot of places to fill things in.
    0:06:13 You’re like, this is never gonna fly.
    0:06:14 And sure enough, about six weeks later,
    0:06:17 I get a phone call from area code 916,
    0:06:18 something like, who do I know in Sacramento?
    0:06:20 And sure enough, it was part of the recruiting process
    0:06:22 and I went to my first interview in Sacramento
    0:06:23 a few days later.
    0:06:25 So it was completely out of the blue.
    0:06:27 This job found me and it just so happens
    0:06:29 that given my past experience,
    0:06:31 it was not a bad fit with my background.
    0:06:32 My wife was absolutely right.
    0:06:35 And so when she complains about it’s hot in Sacramento
    0:06:37 in the summer and it can be very hot here,
    0:06:39 I remind her that she got us here.
    0:06:43 And so she should enjoy and make the best out of it.
    0:06:46 We have it, it’s Sacramento in the midtown area
    0:06:48 for dining, it is fantastic.
    0:06:50 We really enjoy the hard time in Sacramento.
    0:06:51 – And to get a job like this,
    0:06:53 is it like working at Google
    0:06:55 where you have 12 rounds of interviews and they say,
    0:06:58 so Steve, how would you count the number
    0:07:01 of manhole covers in the state of California?
    0:07:03 How does it work in this process?
    0:07:05 – I’ve been critical of the interviewing process
    0:07:06 ’cause it is a bit abstract
    0:07:10 and in government we’re trying to be super fair, very even.
    0:07:14 So sometimes the questions are just a big goofy.
    0:07:16 And it’s where my wife traveled up with me
    0:07:17 when we did these interviews.
    0:07:18 So we were just commuting up from the Bay Area
    0:07:20 and I left the first interview
    0:07:21 and I was just like shaking my head and said,
    0:07:23 okay, this is done.
    0:07:26 Because it was just such an odd interview.
    0:07:27 I assumed that they were not serious,
    0:07:29 they were just checking the boxes and okay, yeah,
    0:07:32 we interviewed some guy from the Bay Area.
    0:07:34 And sure enough, a couple weeks later, I got another call.
    0:07:38 And it’s now we’re now progressing up the leadership chain.
    0:07:41 And eventually I get to meet with the governor’s chief
    0:07:42 of staff, Ann O’Leary.
    0:07:45 If you’ve Google her, she’s a very serious woman
    0:07:47 as it has worked in the highest levels of government
    0:07:49 at the federal level.
    0:07:50 And you’re meeting with Ann O’Leary and you’re thinking,
    0:07:52 okay, this is getting serious.
    0:07:54 And as I left the interview that day with my wife again,
    0:07:57 I said, you’re gonna have to really consider like right now
    0:07:59 that do you wanna move to Sacramento?
    0:08:03 Because our next interview is gonna be with the governor.
    0:08:05 And sure enough, like five minutes later,
    0:08:06 Ann’s calling me on the phone and saying,
    0:08:08 hey, can you come back tomorrow?
    0:08:10 The governor wants to meet with you.
    0:08:11 So we had to decide, I said,
    0:08:12 are we gonna move into Sacramento?
    0:08:14 Because it’s getting serious.
    0:08:17 And I met with governor, super curious guy,
    0:08:20 very interested in trying to improve government.
    0:08:22 And I was impressed and I shared with him
    0:08:24 what he should expect getting from me.
    0:08:26 Because I have things that I’m focused on,
    0:08:28 the things that I wanna do a certain way.
    0:08:31 And I was impressed and apparently I impressed him enough.
    0:08:32 And the next thing you know,
    0:08:33 they’re trotting me out in a press conference.
    0:08:34 And as you know, right?
    0:08:36 You never wanna follow a better speaker.
    0:08:39 So here’s a governor doing his thing as he does,
    0:08:40 is an amazing speaker.
    0:08:42 Then they trot me out.
    0:08:45 And I’m like, deer in the headlights.
    0:08:46 And that was it.
    0:08:47 And then next thing you know,
    0:08:49 I’m meeting with the staff and getting to know
    0:08:52 what’s really going on inside the department.
    0:08:54 – Wait, back up for a second.
    0:08:57 So just give me an example of a question or two
    0:09:00 in the first interview that was goofy.
    0:09:01 – It’s probably unfair,
    0:09:02 but they were of the type, you know,
    0:09:04 like what’s your favorite color?
    0:09:05 And I get not being critical,
    0:09:07 but they were, I think people are trying to be fair.
    0:09:10 So they asked these very generic questions.
    0:09:11 And from that,
    0:09:13 I’m not sure what you’re supposed to take from it.
    0:09:15 But when I’ve talked to my friends,
    0:09:16 I say it’s the equivalent of that.
    0:09:18 And it’s like, what were they trying to learn from that?
    0:09:21 And I know people that of course were in that interview
    0:09:23 are gonna listen to this discussion.
    0:09:24 They’re gonna say, what do you mean?
    0:09:25 But it was very odd.
    0:09:28 And I’ve shared with folks that are in the various offices
    0:09:31 and say we had to up the game on making sure,
    0:09:33 especially at an executive level,
    0:09:35 you should be talking about what do you really want to know
    0:09:36 from that person?
    0:09:38 You can ask tough questions or reasonably tough questions
    0:09:41 to a number of people and then still be consistent.
    0:09:43 So anyway, that was, like I said,
    0:09:46 we were driving home from that as like, okay, that’s done.
    0:09:48 We’re gonna go back and gonna do something else.
    0:09:50 But it turned out that it wasn’t done.
    0:09:50 – My God.
    0:09:53 And tell me, so now you’re meeting with the governor,
    0:09:55 you get an offer and all that.
    0:09:58 And then what do your buddies at Cisco say?
    0:10:01 Like what, have you lost your mind, Steve?
    0:10:02 Why would you do this?
    0:10:04 What was their reaction?
    0:10:06 – I thought their reaction was fantastic.
    0:10:09 They’re like, thank God someone’s gonna go in there
    0:10:09 and do something.
    0:10:12 And for the people that work closely with me at Cisco,
    0:10:14 I mean, they knew that I’m an operations guy,
    0:10:15 I’m no nonsense.
    0:10:17 I’m a ton of energy to apply on things.
    0:10:19 And they were like, yeah, great.
    0:10:21 If you need anything, give me a call.
    0:10:23 I even got, of course, I got posted in the press.
    0:10:25 Some people were posting on my LinkedIn page.
    0:10:27 And the funniest comment was this guy.
    0:10:28 I was at Microsoft.
    0:10:29 He goes, you know, you ought to see if the governor
    0:10:31 will reduce your salary by $6.
    0:10:33 ‘Cause if he does reduce your salary by $6,
    0:10:35 it’ll be equal to the speed of light
    0:10:38 in miles per second or whatever.
    0:10:39 And I looked at that and said, okay,
    0:10:41 first the guy was pulling for me for success
    0:10:43 and he was having a little fun with the speed of light.
    0:10:44 It was a math question.
    0:10:45 And I thought, okay, I love that.
    0:10:47 But I think people truly were pulling for me.
    0:10:49 And I tell you, when I got into the job,
    0:10:53 there were a number of opportunities for bringing,
    0:10:54 or at least needing some context.
    0:10:55 So I reached out into my network
    0:10:57 and people were extremely generous.
    0:10:59 And are still extremely generous.
    0:11:00 When I need to understand something
    0:11:02 or how to think about this,
    0:11:04 people are very generous with their time,
    0:11:05 which is fantastic.
    0:11:06 And they want to be involved.
    0:11:08 They want to see things improved.
    0:11:10 And they’re just glad that they can give the ball
    0:11:11 to somebody unlike me.
    0:11:12 And I’m very fortunate to have those friends
    0:11:15 and acquaintances in that network to call upon.
    0:11:17 – Well, Steve, let me go on the record right now
    0:11:20 that if you ever want my advice
    0:11:24 on how to evangelize the DMV,
    0:11:26 I’m there for you, bro.
    0:11:28 I would love to help you guys.
    0:11:29 – That’s great.
    0:11:31 We’ll see about what edits we can put into this podcast
    0:11:32 and see if we take it.
    0:11:33 I’m kidding, no.
    0:11:35 No, I mean, people are extremely generous.
    0:11:37 And it’s really fantastic that people want to be
    0:11:39 that invested and they see that there’s an opportunity
    0:11:41 to make change.
    0:11:43 We can’t fix everything, but that’s our Prado charge.
    0:11:46 We’re attacking this one silo at a time.
    0:11:47 And we’ve had a lot of success,
    0:11:49 but there’s still a lot more work to do.
    0:11:51 – So just to back up a step,
    0:11:53 because people outside of California
    0:11:56 and outside of America may not be familiar
    0:11:58 with what a DMV does.
    0:12:01 So can you just explain what it is you do
    0:12:03 and what it is you don’t do?
    0:12:06 Who does the freeways or is it just licensing
    0:12:08 or where’s the dividing lines?
    0:12:10 – So all the DMVs across the nation
    0:12:11 are slightly different.
    0:12:14 California has vehicles and drivers in it.
    0:12:18 And we’re also responsible for the automobile dealer network.
    0:12:19 So we have oversight over what’s called
    0:12:22 an occupational license that are all these things
    0:12:26 that touch businesses that are selling cars, motorcycles,
    0:12:28 anything that is considered a vehicle.
    0:12:31 But by and large, the thing we do the most are vehicles.
    0:12:34 You buy a vehicle, title of vehicle, register a vehicle.
    0:12:36 There’s 36, 37, 38 million,
    0:12:39 and which number you look at of those that are in the system.
    0:12:41 We have drivers, of course, that’s you and me,
    0:12:44 that are somewhere 27, 28 million unique driver’s license.
    0:12:46 So that’s the right of passage for many people.
    0:12:48 So that’s another important thing that we do.
    0:12:50 And then everything else past that
    0:12:52 is really administering those two things.
    0:12:54 There are some, like I said, dribs and drabs,
    0:12:55 and I don’t mean to be disrespectful,
    0:12:58 but we have oversight of the automotive industry.
    0:12:59 So that’s an occupational license,
    0:13:00 and there are lots of dealers.
    0:13:02 We want to take that very seriously.
    0:13:05 There are the things that happen to vehicles, lean sales.
    0:13:06 I have an investigations unit.
    0:13:08 I didn’t know when I got hired
    0:13:10 that I have a small law enforcement team.
    0:13:13 And they’re very focused on enforcing the laws
    0:13:16 that are sort of our narrow lane in the vehicle code.
    0:13:18 And so it’s been a great learning curve for me.
    0:13:20 When I showed up, I thought it was just vehicles
    0:13:21 and driver’s license.
    0:13:23 And it turns out that it’s a whole bunch more.
    0:13:24 And these are very serious matters.
    0:13:26 And we want to take them seriously
    0:13:28 and want to do as much good as humanly possible
    0:13:29 for the consumer.
    0:13:31 We want to make sure businesses can do their thing
    0:13:33 and be efficient and effective.
    0:13:35 And that means we have to sit in a lot of different chairs
    0:13:37 and understand what’s the most important thing we can do
    0:13:38 and what’s the best solution,
    0:13:41 best path to a solution for this problem or that problem.
    0:13:44 – And does your data interface anything
    0:13:47 with voter registration or jury duty
    0:13:48 or anything like that?
    0:13:49 – No jury duty.
    0:13:52 I have jury duty, I need to call in for on Monday.
    0:13:53 So thanks for the reminder.
    0:13:55 But California is a motor voter state.
    0:13:57 And all that merely means is that when you come in
    0:14:00 to do something for the motor side, DMV sort of stuff,
    0:14:03 we pop up a form as part of the application process
    0:14:05 from the secretary of state.
    0:14:06 And the secretary of state’s form will ask you
    0:14:08 if you want to register to vote
    0:14:11 or if you want to change your voter registration criteria.
    0:14:13 When I arrived that that motor voter system
    0:14:15 was in a bit of disarray.
    0:14:17 So there was a few crises when I showed up.
    0:14:20 I got to meet the secretary of state now, Senator Padilla,
    0:14:21 very imposing man.
    0:14:24 And we had a good chance to chat about
    0:14:27 the motor voter process, what we’re going to do,
    0:14:28 how we’re going to govern it.
    0:14:30 And we worked closely with the secretary of state’s office
    0:14:34 to get it so that that process worked and was improved.
    0:14:36 And now I think is highly functional.
    0:14:37 And that’s where you want it to be.
    0:14:39 And got it off the radar of everyone as a problematic system,
    0:14:42 got it to stable and now we just maintain.
    0:14:44 – And do you have any interaction
    0:14:48 with the federal department of transportation
    0:14:52 or NHTSA or anything like that?
    0:14:55 – Yeah, so we work with NHTSA on many things.
    0:14:57 And we also work with the federal highway administration.
    0:14:59 So those two have different jurisdictional roles.
    0:15:01 And I’m still new enough,
    0:15:03 five and a half years into the thing.
    0:15:05 I’m still not sure exactly what each one does,
    0:15:06 but I know that they play a role.
    0:15:08 And one is responsible for funding
    0:15:10 and keeping the highway system going.
    0:15:12 The other one is responsible for the vehicle side of it.
    0:15:13 So if there’s a vehicle recall,
    0:15:15 you’ll see through that department of transportation,
    0:15:18 the NHTSA arm will be coordinating those efforts.
    0:15:21 And then we’ll have responsibility to make sure that those,
    0:15:22 let’s say it’s an emissions recall,
    0:15:24 which really may be not from NHTSA,
    0:15:26 but we have responsibility of working with them
    0:15:29 and making sure that regulations that they promulgate
    0:15:33 are as they’re applicable to us are applied in the state.
    0:15:35 So we do work with federal agencies.
    0:15:37 – So when you first got there,
    0:15:40 describe the situation you inherited?
    0:15:43 – I had spent 18, 19 years at Cisco Systems
    0:15:46 and my last sort of five, 10 years there,
    0:15:48 I did a lot of acquisition integration.
    0:15:49 If there was a services business,
    0:15:52 I would be responsible to get it to tuck in and so on.
    0:15:54 So when I showed up at the department,
    0:15:55 it was very similar.
    0:15:57 There were these different groups.
    0:15:58 We call them divisions.
    0:16:00 Initially you might call them tribes
    0:16:02 where they were these vertically integrated things
    0:16:05 and they were independent and driving the ship.
    0:16:07 So I had a chance to work with all of the deputies,
    0:16:09 trying to understand what we were trying to do,
    0:16:11 but understanding that we were on the clock, right?
    0:16:12 When my days at Cisco, you had some time
    0:16:14 to figure out what we just bought
    0:16:16 and where it might fit and how to get the best out of it.
    0:16:18 But we were on the clock in the government
    0:16:21 because this real ID, the first real ID deadline was looming
    0:16:23 and we had to get our act together very, very quickly.
    0:16:24 So I gathered the deputies around,
    0:16:26 we figured out what the initiatives were,
    0:16:28 we tried to figure out who’s who in the zoo, so to speak
    0:16:30 and try to make sure that we were focused on
    0:16:32 the right things with the right people,
    0:16:34 with the right resources, the right metrics.
    0:16:36 And we just started to attack
    0:16:38 as you would do in any particular business,
    0:16:40 making sure that the first things first,
    0:16:42 next thing, next thing, next thing.
    0:16:43 And there were some really good people.
    0:16:45 There still are some really good people here.
    0:16:47 Many of those people that I met on day one,
    0:16:49 they’re still here, they want to win.
    0:16:51 Sometimes they just didn’t know how to prioritize
    0:16:54 or how to settle disputes between the tribes.
    0:16:56 And we set up a different governance structure
    0:16:58 and made sure that in fact we could resolve this issue
    0:17:00 so we can actually do the most important thing
    0:17:02 for our constituents.
    0:17:04 – But do you have some statistics for us
    0:17:07 that when you started, the average waiting time
    0:17:11 was two hours or whatever, what were service levels like
    0:17:12 when you came into this?
    0:17:15 – Yeah, government and measurements are not
    0:17:17 as strong a partner, should you like to think.
    0:17:20 But one simple measure we had, we,
    0:17:23 before I started, the governor had asked,
    0:17:25 I think this was Governor Brown had asked McKinsey
    0:17:29 to come in and work with the government operations group.
    0:17:30 They did some really nice work.
    0:17:32 And one of the things that I often joke
    0:17:34 with the McKinsey partner, we still have a relationship,
    0:17:36 the one really great thing they left us
    0:17:37 is a value stream map.
    0:17:41 And it showed for a real ID, the number of steps,
    0:17:44 many of these were just self-imposed policy steps
    0:17:46 that we added to the real ID process.
    0:17:47 And a value stream map, the way you use it,
    0:17:49 you start looking at each step, you challenge each step
    0:17:51 and you’re looking for things that are called waste.
    0:17:53 And those waste are things you don’t really need to do
    0:17:54 but you’re doing, they’re in the way.
    0:17:57 And that process at the time was somewhere
    0:17:58 around 28 minutes.
    0:18:00 And that’s just based on the value stream map
    0:18:01 and that’s being generous.
    0:18:04 It was actually probably a little longer than that.
    0:18:05 So we attacked that with vigor.
    0:18:07 We took it from 28 minutes to 10 minutes
    0:18:09 and this now runs around routinely around eight minutes,
    0:18:12 still four minutes longer than what it needs to do.
    0:18:15 But with our current systems, that’s how it works.
    0:18:17 So that’s one measure, it was like 28 to 10.
    0:18:20 We had wait times that were in the press there.
    0:18:22 Four hours, sometimes two and a half hours,
    0:18:23 sometimes longer.
    0:18:25 I don’t know if any of that was really well measured.
    0:18:27 And then on top of that, just one last thing,
    0:18:29 that there was also an internal audit
    0:18:31 that was ongoing before I arrived.
    0:18:34 It was called the OSE audit office of something.
    0:18:36 Anyway, some state auditor looking at performance measure.
    0:18:39 So they were in there helping to try to figure out
    0:18:41 what else was going on in the department.
    0:18:42 So all that stuff was, when I arrived,
    0:18:45 was just coming to fruition.
    0:18:47 So I can actually immediately take a look at that,
    0:18:49 figure out which of those things I need to incorporate
    0:18:52 into my plan and be able to attack based on that.
    0:18:54 ‘Cause you do need baselines and we had a couple,
    0:18:56 but they were really not as robust as you’d see
    0:18:57 in private industry.
    0:19:00 (upbeat music)
    0:19:13 – Some people may be wondering what exactly
    0:19:15 are they talking about with Real ID?
    0:19:17 So can you explain Real ID for the listener?
    0:19:20 – Sure, Real ID is actually a spin out, if you will,
    0:19:22 of a federal requirement from 9/11.
    0:19:25 This was back in the day where we were concerned
    0:19:27 about people accessing an airport, getting on a flight,
    0:19:29 and we really didn’t know who they were.
    0:19:33 ‘Cause each state’s requirements for identification
    0:19:36 were different and they still are different to some degree,
    0:19:39 but if you wanna access this federal entity, an airport,
    0:19:42 there was a law passed, the Real ID Act,
    0:19:45 and that tried to standardize what the requirements were
    0:19:47 to make sure that identity documents
    0:19:49 were the same across the nation.
    0:19:51 Residency documents were the same across the nation
    0:19:53 so that when you have a Real ID
    0:19:57 and you show up at an airport, show up at a TSA stop,
    0:19:59 as you’re trying to get into the airport,
    0:20:01 they’ll have a high degree of confidence
    0:20:03 that you will actually be who you say you are.
    0:20:04 And that’s something we’ve been implementing now
    0:20:06 for many, many years as are many other states.
    0:20:08 And there are states like California
    0:20:11 where the Real ID is not a required credentials,
    0:20:12 you’re not a must have state.
    0:20:14 There are some states that you can only have a Real ID,
    0:20:16 but California allows a federally non-compliant card,
    0:20:17 as do many other states.
    0:20:19 We have a Real ID option.
    0:20:22 We have 18, 19 million people that have the Real ID.
    0:20:26 So almost majority of people that want to travel,
    0:20:28 access federal facilities, have a Real ID.
    0:20:31 And that’s gonna be a requirement come up later this summer
    0:20:33 to make sure that people get into the airport
    0:20:34 with the right credentials.
    0:20:36 So TSA, Department of Homeland Security,
    0:20:39 is making sure that window of time gets narrowed
    0:20:41 so we can actually get everyone who needs to access
    0:20:44 an airport or a federal facility has the right credential.
    0:20:47 Of course, you can still use a passport, a military ID.
    0:20:48 There’s a bunch of other ways to do this,
    0:20:51 but a Real ID is certainly something that is easier
    0:20:53 because we almost always travel not only with our phone,
    0:20:55 but also with our driver’s license.
    0:20:58 – So if people in California are listening to this
    0:21:01 and they don’t know if they have a Real ID,
    0:21:02 don’t you just look at your license
    0:21:05 and see if there’s a golden bear on it or not?
    0:21:08 – That’s exactly right, very good, very good.
    0:21:09 There’s a star for you there.
    0:21:11 There’s a bear and a star in the upper right
    0:21:12 of the driver’s license.
    0:21:14 It’s pretty evident when you just look at the card.
    0:21:16 – Okay, I know that now.
    0:21:18 So it’s okay, so now you walk in this,
    0:21:22 these service levels, 28 minutes to get Real ID,
    0:21:23 and you have these internal audits.
    0:21:27 Now, what are the phases of when you went through
    0:21:29 to improve the situation?
    0:21:31 How did you do this?
    0:21:33 – I hate to minimize it,
    0:21:35 but it was pretty much back to fundamentals, right?
    0:21:38 We had to figure out what are our staff doing?
    0:21:40 Which tasks are they completing?
    0:21:42 Are those tasks we care about?
    0:21:43 And we just worked our way down.
    0:21:45 You can imagine, created these large Pareto charts
    0:21:47 of things that have high volume.
    0:21:49 And we looked to figure out how we were attacking those.
    0:21:52 You know, the old Boston consultant, two by two grids.
    0:21:53 We looked at the volume.
    0:21:55 We looked at the ability to execute.
    0:21:56 And then we attacked things
    0:21:58 that were impediments to success.
    0:22:03 For example, having attestations signatures on paper
    0:22:05 and printing those copies.
    0:22:07 So at the window, you used to walk into the DMV.
    0:22:10 We would print your application for you.
    0:22:11 We’d slide the application.
    0:22:14 There’d be six pages on what’s called now a half sheet.
    0:22:16 And it was slide across the counter.
    0:22:17 The customer would review them.
    0:22:19 They would sign it with a pen, what signature.
    0:22:21 They’d slide it back across the counter.
    0:22:23 We would then take those at the end of the day.
    0:22:25 We’d put those all in an envelope.
    0:22:27 We would send them on a journey to Sacramento,
    0:22:30 where we would scan them, and then we would dispose them.
    0:22:31 It was nuts.
    0:22:33 But it was one step in the process.
    0:22:35 And we had these tablets that were at the window
    0:22:37 that somebody a few years before that had thought,
    0:22:40 we’re going to use these for something.
    0:22:41 But they never got used.
    0:22:43 So my chief digital transformation officer,
    0:22:46 a guy that is just an amazing talent,
    0:22:48 a Jay Gupta said, why don’t we actually
    0:22:50 have the attestation on the tablet?
    0:22:51 And people were like, we can’t do that.
    0:22:51 Can’t do that.
    0:22:53 So we looked at the statute, looked at regulations,
    0:22:56 looked at our policy, and found out we actually could do that.
    0:22:56 And we did.
    0:22:57 We lit those up.
    0:22:59 All of a sudden, that paper, those six sheets,
    0:23:01 we’d just slide across the counter and bring back,
    0:23:05 send to Sacramento, scan, dispose of.
    0:23:06 That went to zero.
    0:23:07 And because we could.
    0:23:09 So we have people that attest online.
    0:23:10 And it’s really a thing of beauty.
    0:23:11 I don’t know if you’ve seen this guy.
    0:23:13 People that have never used a touchscreen before.
    0:23:17 And you see them, they’re just like slowly dragging.
    0:23:18 But they get it.
    0:23:18 They get it.
    0:23:19 And it’s a joy.
    0:23:20 I don’t want to malign people.
    0:23:22 But if people get a little older,
    0:23:25 haven’t used as much technology, perhaps as you and I have,
    0:23:26 that’s the first time they’ve used a touchscreen.
    0:23:28 They’re saying, oh, that’s what that’s about.
    0:23:31 And they sign in completely paperless.
    0:23:36 And so we’ve gone from tons of paper a week to zero,
    0:23:39 no more trips across California to get the headquarters
    0:23:41 to be scanned, and so on.
    0:23:42 So we’ve reduced our footprint.
    0:23:44 We’ve speeded up the process.
    0:23:45 We’ve actually made the process better
    0:23:48 because it’s digital from day one.
    0:23:49 So it’s things like that.
    0:23:51 And there’s 1,000 of those.
    0:23:53 And that’s just one that you saw at every window
    0:23:56 in every driver’s license transaction.
    0:23:58 I read a report.
    0:24:00 I think it was in the Harvard Business Review
    0:24:03 about management by driving around.
    0:24:05 So I want to hear about that.
    0:24:08 In my days working at Cisco, our CEO at the time
    0:24:09 was a guy named John Chambers.
    0:24:11 And John Chambers–
    0:24:13 I mean, at that level, you’ve got to be a master storyteller.
    0:24:15 So he would go off, and he’d be visiting a customer,
    0:24:17 he’d come back with a story.
    0:24:18 I’d be doing this, and I saw this.
    0:24:20 This is what they’re working on.
    0:24:22 And he kind of put things in context.
    0:24:24 So you’re always taking notes, right?
    0:24:26 As you’re rising to your career, so what things
    0:24:28 do I need to bring into my portfolio?
    0:24:31 So if I ever get to that level so that I will be able to communicate
    0:24:34 effectively– and one of the things I pulled from John Chambers
    0:24:37 is that he was really good about getting out,
    0:24:39 and it was really good about bringing back what he saw
    0:24:40 when he was out.
    0:24:42 So I made that one of the things I wanted to do,
    0:24:44 a deliverable I wanted to do.
    0:24:47 Because sometimes when you’re doing the number of changes
    0:24:49 we were doing at the time when I first joined,
    0:24:51 your staff needs a break from you.
    0:24:53 And sometimes you need a break from your staff.
    0:24:54 So I would go out on the road.
    0:24:56 I would just say, OK, this week I’m going here.
    0:24:57 And I would just start driving.
    0:25:00 And we have 220-plus offices, 180 field offices,
    0:25:02 and a bunch of other offices.
    0:25:03 And I would just go hit a reach.
    0:25:04 And I did a lot of driving.
    0:25:06 My wife came with me.
    0:25:08 And I was doing it for two things.
    0:25:11 One is I wanted to make sure that I had first-hand knowledge
    0:25:12 of what was going on.
    0:25:14 I mean, look, you’re not going to have representative view
    0:25:16 by spending 15 minutes or 30 minutes in a field office.
    0:25:18 But you started building simple relationships.
    0:25:20 You started showing that you care.
    0:25:22 Many times this was the first time
    0:25:26 the staff had ever seen the DMV director, ever.
    0:25:29 And then in some cases, when I started to visit him twice,
    0:25:30 three times, four times, you’re like, well,
    0:25:31 we’ve never seen the director twice.
    0:25:33 You start building these little small relationships.
    0:25:36 And when you do that, you start seeing things
    0:25:37 that you wouldn’t normally see.
    0:25:39 And the staff sees you in a different light.
    0:25:42 And our call was down in one of the offices in the LA area.
    0:25:44 And this woman brought to me this lean release.
    0:25:48 So she financed her car, as many people do, JP Morgan.
    0:25:49 They’re going through their process.
    0:25:51 And she was trying to sell her car to her neighbor,
    0:25:52 but couldn’t get the lean release.
    0:25:53 It’s just a mess.
    0:25:55 It was just those things take time.
    0:25:57 But I gave her my card.
    0:25:58 I took copies of her material.
    0:26:01 I said, look, I’ll be happy to help you and send me an email.
    0:26:02 Let’s work on this together.
    0:26:04 So I can actually learn more about the lean process.
    0:26:06 And the staff got to see that, oh, he’s not
    0:26:08 afraid to talk with a customer.
    0:26:10 He’s not afraid to reach across the counter.
    0:26:11 He’s not afraid to take on work.
    0:26:14 And it also encouraged them to say, you can lean in a little bit
    0:26:15 more.
    0:26:16 We can’t solve all of the problems,
    0:26:19 but we can actually help the customer if we lean in
    0:26:20 and try to understand stuff.
    0:26:21 And I’ve subsequently had discussions
    0:26:24 with the large financials, including JPMC,
    0:26:26 to understand what is the lean release process?
    0:26:29 What can we do to improve it so we can simplify?
    0:26:31 Because cars used to be homes where
    0:26:33 the number one asset people had.
    0:26:35 Nowadays, cars are the number one asset people have.
    0:26:38 And so when you make that illiquid because a lean release
    0:26:41 takes too long or we’re administratively slow,
    0:26:43 whatever it might be, those are opportunities for us
    0:26:44 to learn and grow and improve.
    0:26:46 And the only way you do that is you
    0:26:49 start seeing and feeling the pain that people have when
    0:26:54 they’re stuck between immovable forces, government, large bank.
    0:26:56 And we want to make sure that, in fact, we can improve things.
    0:26:58 And the only way you get to see those things
    0:27:00 is you just happen to be in the field office when somebody
    0:27:01 brings in that issue.
    0:27:03 So that’s what I did.
    0:27:03 I went out and drove around.
    0:27:05 COVID interrupted it.
    0:27:07 Because you don’t want to go out and start driving around
    0:27:08 during COVID when people are afraid.
    0:27:10 But it was great.
    0:27:11 It was great to get out.
    0:27:13 And this is a beautiful state, just as a side note.
    0:27:15 I love to travel.
    0:27:17 I’ve had some good fortune traveling the globe.
    0:27:19 And now, all of a sudden, I get to be in all 58 counties first.
    0:27:22 I didn’t know there were 58 counties when I started this job.
    0:27:23 But I do now.
    0:27:24 And I’ve been to all of our offices.
    0:27:25 I’ve been to all these places.
    0:27:29 And there are some remarkable people all across the state
    0:27:30 and some wonderful people.
    0:27:32 The people we hire in these communities
    0:27:33 are from those communities.
    0:27:36 So you get a sense for what the ethic is there,
    0:27:37 what the local customs are, our cultures.
    0:27:39 And they’re just some wonderful people.
    0:27:41 So it’s a win, win, win, win, win for me
    0:27:42 to be able to be out in these communities.
    0:27:43 It’s fun to have a road trip.
    0:27:45 My wife loves to travel with me.
    0:27:45 It’s fun stuff.
    0:27:52 There should be a reality TV show about your life.
    0:27:56 And I can just see this is like Ken Kiesinger, you know?
    0:27:57 Oh, my god.
    0:27:58 I’m a serious guy, guy.
    0:28:00 I like to get out and have fun.
    0:28:02 But look, these are people trying to do their jobs.
    0:28:04 And I want to show that I respect what they’re doing.
    0:28:07 But I want to show that I also care about improving the process,
    0:28:08 care about them.
    0:28:12 And there’s no reality show.
    0:28:13 Well, when I first started, the team was like, OK,
    0:28:15 we want to get this entourage.
    0:28:17 I was like, no, I travel light.
    0:28:18 I travel either by myself.
    0:28:19 I travel with my wife.
    0:28:21 That’s the extent.
    0:28:22 I don’t need any coordination.
    0:28:24 I don’t need anybody traveling with me.
    0:28:26 I don’t need any advanced staff.
    0:28:27 I just show up.
    0:28:28 And when I first started, I was polite.
    0:28:30 I asked for permission from my field staff.
    0:28:31 Hey, I’d like to be over here.
    0:28:33 Yeah, OK, that’d be a good time to show up.
    0:28:35 Now I just tell people, I’m going out.
    0:28:37 I’m going to be in the high desert next week.
    0:28:40 Or I’m going to be around the Salton Sea the week after that.
    0:28:42 Or I’m going to be in Alturas after that.
    0:28:44 I just tell them generally where I’m going to go.
    0:28:45 And then, not that I want to surprise anyone,
    0:28:48 but I don’t want people to over engineer.
    0:28:52 What is really going to be a 15, 20 minute meet and greet
    0:28:54 and move on to the next site?
    0:28:57 Because it shouldn’t be any more difficult.
    0:28:58 Just like your neighbor stopping by, right?
    0:29:00 And that’s how it should be.
    0:29:03 So just to make this perfectly clear to people,
    0:29:07 this wasn’t like a TV series where the CEO goes in
    0:29:11 as a customer and disguises as a mystery DMV user.
    0:29:13 You went in as a director.
    0:29:14 Yeah.
    0:29:17 One thing I found early on is that my photo is in every DMV.
    0:29:18 I did not know that.
    0:29:22 One of my cousins that lived in the Reading area–
    0:29:24 I was like three weeks, four weeks, five weeks, whatever it was.
    0:29:25 Whatever it takes to get photos out there.
    0:29:27 She sends me a photo of my photo on the watch.
    0:29:29 She goes, essentially, WTF.
    0:29:31 And I was like, so what is that?
    0:29:34 She goes, that’s your photo on the field office out in Reading.
    0:29:37 I was like, I had no idea.
    0:29:38 But so yeah, now I go in.
    0:29:39 I go in the front door.
    0:29:41 And I talk with the staff.
    0:29:42 I talk with the customers.
    0:29:43 I go behind the counter.
    0:29:44 Of course, they know who I am.
    0:29:47 I show them my badge, and she should authenticate everyone.
    0:29:50 And yeah, I go in and try to see what’s happening.
    0:29:51 And I meet everyone.
    0:29:53 I try to say hello to everyone who’s there.
    0:29:57 And yeah, no surprise customer, no mystery shop.
    0:29:58 Now looking at that a different way,
    0:30:00 I do use all of the different channels for our services.
    0:30:02 And so I renew my registration.
    0:30:04 We have this feature in our IVR.
    0:30:05 And so I’ll give that a try.
    0:30:07 And in some cases, I’ll record the session,
    0:30:10 because I want to give feedback back to my staff about here’s
    0:30:10 how it sounds.
    0:30:12 Here’s where it’s maybe too fast.
    0:30:13 Here’s where it’s too slow.
    0:30:14 Here’s where I got in this loop.
    0:30:16 It’s all process improvement stuff.
    0:30:17 But I try to use every channel we have.
    0:30:19 And I try to encourage my senior staff and all
    0:30:22 of you, even our line staff, use these services.
    0:30:24 Feel how they feel.
    0:30:28 Give us feedback so we can actually improve them and so on.
    0:30:30 But the only way you do that is you get out and you use them.
    0:30:33 And the only way you get to see what’s happening,
    0:30:34 if you will, in the wild with our customers,
    0:30:36 is you stand in a field office.
    0:30:38 You talk with people.
    0:30:42 The next time you go to Watsonville or Capitola,
    0:30:43 I want you to tell me.
    0:30:44 I want to go in with you.
    0:30:47 I want to see you do this.
    0:30:48 That would be so fun.
    0:30:50 Yeah, no, I’m happy to do it.
    0:30:51 But it’s less exciting than you think.
    0:30:52 I’m there and I’m in and out.
    0:30:54 Well, it’s only 20 minutes.
    0:30:55 Right, I’m in and out.
    0:30:55 15, 20 minutes.
    0:30:58 I make sure I make a point of saying hello to everyone,
    0:31:00 including like there are examiners that are doing drive tests.
    0:31:02 I try to catch them in between drive tests,
    0:31:03 because they’re on the road.
    0:31:05 They rarely get a chance to see anyone.
    0:31:08 And I just want to make sure I don’t make a big deal out of it.
    0:31:09 But at the same time, I want to make sure
    0:31:11 I have a chance to meet everyone.
    0:31:13 And that way, you know, encourage them.
    0:31:14 If they see something and there are
    0:31:17 a few that take me up on this offer, they’ll send me an email
    0:31:19 and they’ll say, hey, I saw this or I saw that.
    0:31:21 And then we’ll go through a discussion about how do you
    0:31:22 collect data?
    0:31:27 There was one in Reedley, which is this town outside of Fresno.
    0:31:30 She was this manager, wonderful, very curious,
    0:31:32 was writing me about, oh, we see a lot of this.
    0:31:34 And I’m in and I hear a lot.
    0:31:36 I say, well, quantify a lot.
    0:31:38 And so I said, here’s how you might quantify it.
    0:31:40 So I taught her how to quantify.
    0:31:41 I grabbed some data on the back end
    0:31:42 that maybe she wouldn’t have asked to.
    0:31:43 I shared with her.
    0:31:46 Here’s what I think is happening across the state.
    0:31:48 And sure enough, she validated that her allot
    0:31:50 was maybe two items a week.
    0:31:52 I said, so instead of us focusing on those, important.
    0:31:54 But let’s focus on something that’s bigger.
    0:31:55 So I gave her some examples.
    0:31:58 And but it’s how you teach people.
    0:32:01 First, I taught her to reach out to me, taught her to engage,
    0:32:02 taught her about how we’re thinking about data,
    0:32:05 caused me to think about something I wasn’t thinking about.
    0:32:07 And now she’s better at doing analysis.
    0:32:08 And that’s up and down.
    0:32:10 There’s a data entry clerk here.
    0:32:12 Her name is Catherine.
    0:32:14 Took me up on this offer months ago.
    0:32:17 And she is in this repetitive job
    0:32:20 where she sees all these same form over and over again.
    0:32:22 Her job is to do error correction
    0:32:24 and finish the data entry.
    0:32:26 And so she wrote me and she had this long story
    0:32:30 about this address and not populating correctly.
    0:32:32 And I said, I’ll come right down.
    0:32:34 I thought, OK, there’s no way she’s
    0:32:36 going to have any data on the thing.
    0:32:39 I show up and she’s like this serious woman.
    0:32:41 And she’s seeing thousands of these things.
    0:32:43 She pulls up her examples.
    0:32:44 She walked me through a current.
    0:32:46 She saved one of them for me.
    0:32:49 She walked me through, this is where the problem is.
    0:32:51 And when you do this and sure enough, she was spot on.
    0:32:55 And she says, the management team would not fix this.
    0:32:57 I said, I’ll get that fixed.
    0:32:58 But she had evidence.
    0:33:00 She was waiting for this moment.
    0:33:01 It doesn’t get any better than that
    0:33:03 because she was prepared.
    0:33:07 She had data and she had a real problem and she was stuck.
    0:33:09 So that was fantastic.
    0:33:11 So when Catherine writes me now, I pop right down and say,
    0:33:13 show me that again and we get it fixed.
    0:33:15 And matter of fact, her team is now much more responsive
    0:33:18 because Catherine brings facts.
    0:33:20 Doesn’t get any better than that.
    0:33:21 What office is this?
    0:33:22 This is a headquarters.
    0:33:24 This is a person who does data entry at headquarters.
    0:33:27 We process a lot of mail and she’s
    0:33:29 the choke point for certain forms.
    0:33:33 And she is the expert because she sees thousands of them
    0:33:35 and she’s attentive.
    0:33:38 So coming from Cisco, now, I wouldn’t
    0:33:41 put Cisco in that same class of companies
    0:33:45 as like Facebook and Meta and PayPal, Mafia, et cetera,
    0:33:45 et cetera.
    0:33:51 But what’s the similarities and differences in management
    0:33:54 in this kind of Silicon Valley tech company
    0:33:59 and then going to a public service company, State
    0:33:59 of California?
    0:34:01 Like, what’s the differences?
    0:34:03 What’s the transition like for you?
    0:34:05 First, I was on the services side of Cisco.
    0:34:07 So even though I’m trained as an accountant,
    0:34:10 I was in technology support.
    0:34:12 I learned TCP/IP protocol.
    0:34:13 I learned how all that stuff works.
    0:34:15 I was surrounded by a bunch of people
    0:34:17 who are MSCEs and BSEs.
    0:34:20 Our COO, a guy who’s our chief deputy at Swanson,
    0:34:23 has got a couple degrees, a graduate degree
    0:34:24 in electrical engineering from Stanford.
    0:34:26 So these are people that actually
    0:34:27 know what electricity does.
    0:34:29 I know electricity does something.
    0:34:30 I can’t tell you why it does it,
    0:34:31 but I understood protocols and so on.
    0:34:33 So anyway, most of my experience from Cisco
    0:34:35 was on the services side.
    0:34:37 And then I had this acquisition tuck-in role later
    0:34:38 on in my career.
    0:34:40 So it was kind of business-driven.
    0:34:43 And in those roles, you became very focused on operations
    0:34:45 and you had to figure out what’s the right order of things.
    0:34:47 I developed some great relationships.
    0:34:49 A guy named Mike Zill, who’s still a good friend of mine.
    0:34:52 He’s a big thinker, but he’s also a manufacturing process guy.
    0:34:54 So he taught me about the whole basics
    0:34:57 of how do we make sure we get cost-quality cycle time
    0:35:01 and get things into the hopper and through the system,
    0:35:04 first-pass yields and first-time that sort of stuff.
    0:35:07 And so I had a number of people that were helping me understand
    0:35:09 the impact that a product could have on a customer.
    0:35:11 A guy who wrote to me last week– he
    0:35:14 was in one of our DMVs down in San Jose, Maliki Moynihan, who
    0:35:16 was our chief of engineering at Linksys
    0:35:20 when Cisco acquired Linksys, was stuck trying to register a car
    0:35:22 when our field offices, our systems were having a glitch.
    0:35:24 So he was tech to be like, what’s going on?
    0:35:25 Should I wait? Should I go?
    0:35:26 But he’s another guy who taught me
    0:35:29 how to think about when a product had a defect,
    0:35:32 the downstream impact, the impact on a customer,
    0:35:34 the impact on the channel it was in.
    0:35:36 And so all of those things played a role
    0:35:38 in helping you think about the business you’re in,
    0:35:41 thinking about the quality of the product you’re producing,
    0:35:43 making sure people can get through that process
    0:35:44 in the first pass.
    0:35:46 So regardless of whether you’re at Facebook, you’re at Cisco,
    0:35:49 wherever you are in that technology lifecycle,
    0:35:51 there’s a lot of that that’s the same.
    0:35:53 And you’re just using best practices.
    0:35:56 I was fortunate to be surrounded by people with advanced
    0:36:00 degrees, good universities, good colleges, good thinkers,
    0:36:01 good experience.
    0:36:03 And I pulled from all of those people.
    0:36:04 And they’ve been very generous with their time
    0:36:07 to help us improve my skills and help us now apply those
    0:36:09 to the state of California.
    0:36:11 Now, it seems to me that, yeah, you
    0:36:13 can say there’s a lot of similarity,
    0:36:16 but correct me if I’m wrong.
    0:36:20 But it seems like your ability to motivate people
    0:36:23 with raises and RSOs or stock options,
    0:36:26 that’s not on the table at the California DMV, right?
    0:36:29 So what do you do to motivate people?
    0:36:30 Yeah.
    0:36:33 Because the Silicon Valley way is always about stock options.
    0:36:34 Yeah, it’s tricky.
    0:36:36 I’m sure some of your other guests
    0:36:37 might be better skilled here academically
    0:36:39 about which buttons to push.
    0:36:42 I’ve never been strictly a financially motivated guy.
    0:36:45 Some of my peers were like, they were focused on the RSO,
    0:36:48 or they’re focused on when their options were going to invest.
    0:36:50 Never was my particular focus.
    0:36:51 Obviously, you want to be well compensated.
    0:36:54 At the same time, you want to make sure you’re on a mission.
    0:36:55 That’s the highest level thing, right?
    0:36:56 You’re on this mission.
    0:36:57 You feel you can make an impact.
    0:37:00 And by and large, I think the people that are on my staff
    0:37:03 have the front line to the top line.
    0:37:05 They think they’re making a difference.
    0:37:06 And they are making a difference.
    0:37:08 I was out in Palm Springs last week.
    0:37:11 And there is a woman in Palm Springs named Tamika.
    0:37:12 I forgot Tamika’s last name.
    0:37:13 Sorry, Tamika.
    0:37:15 But she had been a recent recipient
    0:37:18 at this agency that were part of the Transportation Agency.
    0:37:20 Within the state, we recognized her across the state
    0:37:23 as someone who really was making a difference in people’s lives.
    0:37:23 You meet her.
    0:37:25 She just lights up the room.
    0:37:29 And she’s doing the intake at the field office in Palm Springs.
    0:37:31 She’s your first point of contact.
    0:37:32 And she’s on that mission.
    0:37:34 And she’s making people’s lives better.
    0:37:37 One customer at a time, getting them the right feedback,
    0:37:39 a smile on her face, a can-do attitude.
    0:37:42 And that raises– that office performs better
    0:37:44 than it’s adjacent office.
    0:37:46 And I attribute some of that to Tamika
    0:37:48 because that one person can make a difference.
    0:37:51 So anyway, you talked about stock options and compensation.
    0:37:53 We do not have those levers here in government.
    0:37:54 But we are mission-driven.
    0:37:57 And I think having people like a Tamika or even people
    0:37:59 like some of my senior staff who are on this mission
    0:38:01 are trying to remove roadblocks, things
    0:38:03 that we’ve all been taught to do in Silicon Valley,
    0:38:06 taking obstacles out of the way.
    0:38:08 I think people see that, in fact, we understand that.
    0:38:09 And we’re willing to do that.
    0:38:11 We’re willing to invest political capital behind that.
    0:38:13 And we’re making their job simpler.
    0:38:16 We’re making the customer’s journey easier.
    0:38:19 And that’s good for everyone, even if you’re not
    0:38:22 doing it because of a direct financial motivation.
    0:38:26 And if I were to see Tamika or call Tamika and say,
    0:38:29 “Tamika, what is your mission at the DMV?
    0:38:30 What would she say?
    0:38:32 What’s the mission?”
    0:38:32 That’s a great question.
    0:38:34 I don’t know what Tamika would say.
    0:38:35 But I certainly suspect she would say
    0:38:39 that she’s there because she loves helping people.
    0:38:41 And I think about when we think about the mission of the DMV,
    0:38:43 that gets a little muddy.
    0:38:45 We are a tax-collecting organization.
    0:38:47 But we should be the best.
    0:38:50 And I try to remind my staff that when
    0:38:53 we’re buying an online service or even a retail service,
    0:38:55 we should be thinking about the best of the best.
    0:38:57 We should not be benchmarked within,
    0:38:58 as they call it, the tallest pygmy.
    0:39:01 We should not segment ourselves into a small little group
    0:39:03 and be the best government agency
    0:39:04 with a left-handed leader.
    0:39:05 No, that’s crazy.
    0:39:07 We should be looking at what does an Amazon do?
    0:39:10 JPMC, when you have the highest credit card,
    0:39:12 when you’re about to lose that credit business,
    0:39:13 you should be thinking about what
    0:39:15 do they do to lean in to make sure they don’t lose you
    0:39:15 as customers?
    0:39:17 We have to aspire to that level.
    0:39:19 That means our services have to work.
    0:39:20 They have to be easy.
    0:39:22 They have to be intuitive.
    0:39:23 And when people want to pay us money,
    0:39:25 we should help them pay us money.
    0:39:27 We should not make it hard for them.
    0:39:28 And sometimes we do.
    0:39:29 So we have a lot of room to grow there.
    0:39:31 But I think that’s the mission we’re on.
    0:39:34 It’s just making sure that participating in society
    0:39:36 in California, getting your driver’s license,
    0:39:38 registering your vehicle, trying to be compliant.
    0:39:39 That should be easy.
    0:39:42 We should assume that people are trying to help themselves
    0:39:43 and trying to help us.
    0:39:44 And we need to make it easy.
    0:39:46 And we should just realize that the comparator
    0:39:48 in the marketplace is Amazon.
    0:39:49 So I talked to my staff and I asked
    0:39:52 what anybody ordered anything from Amazon over the holidays.
    0:39:54 And every hand goes up and says, so when you’re thinking
    0:39:57 that the DMV or government should be different,
    0:39:59 I said, no, we should be good as what we’re trying to do
    0:39:59 as they are.
    0:40:01 We should make the products are on the shelf.
    0:40:02 We should know what they want to buy.
    0:40:04 We should make it easy to put it in the car.
    0:40:05 We should make it easy to pay.
    0:40:08 And again, we have some room to go there.
    0:40:09 But that’s the direction we’re headed.
    0:40:11 Up next on Remarkable People.
    0:40:14 These are federal roads that they allow California
    0:40:18 and other states to give certain privileges to ATOVs.
    0:40:20 So we have to go and have the federal administration,
    0:40:22 I’m not sure if it’s federal highways
    0:40:23 or I think it’s federal highways.
    0:40:25 This is their program that they allow California
    0:40:27 to allow people into the ATOV lane.
    0:40:29 We give a sticker as a result of that
    0:40:30 so we can identify those vehicles
    0:40:34 and make sure they qualify for emissions and so on.
    0:40:36 So the reason that it only is good to September,
    0:40:38 that is the end of the federal fiscal year.
    0:40:39 So we’re waiting right now to find out
    0:40:42 if the federal government is going to continue to extend
    0:40:45 that for the next year or the years past that.
    0:40:48 But at this point, September 30th of this calendar year
    0:40:50 is the last time you’ll be able to use an ATOV sticker
    0:40:51 in California.
    0:41:05 – Thank you to all our regular podcast listeners.
    0:41:08 It’s our pleasure and honor to make the show for you.
    0:41:10 If you find our show valuable,
    0:41:12 please do us a favor and subscribe,
    0:41:13 rate and review it.
    0:41:16 Even better, forward it to a friend,
    0:41:18 a big mahalo to you for doing this.
    0:41:22 – You’re listening to “Remarkable People”
    0:41:23 with Guy Kawasaki.
    0:41:26 – I gotta say,
    0:41:29 I am just having the time of my life in this interview
    0:41:31 and I don’t say that quite often.
    0:41:33 Madison can attest to that.
    0:41:37 The innovation that I discovered with the DMV
    0:41:39 that when I first saw it,
    0:41:42 I said, man, like what made them do this?
    0:41:44 This is so interesting.
    0:41:48 It’s this thing that you can get your number
    0:41:52 for your appointment before you get to the DMV.
    0:41:54 So you can get that number in advance.
    0:41:56 So when you get to the DMV,
    0:41:59 there’s already been progress in the queue.
    0:42:03 So I wanna know, how did that idea come to be?
    0:42:05 – It’s like calling up Baskin Robbins and say,
    0:42:07 all right, give me your ticket now
    0:42:09 and I’m gonna drive down there in 15 minutes
    0:42:12 and I’ll be served 30 seconds later.
    0:42:14 – I think some of us came from just our experiences
    0:42:16 outside of the office.
    0:42:18 Yelp allows you to do that like one of the local restaurants
    0:42:21 where it’s a Thai place by my place in San Jose
    0:42:23 and they would allow you to put yourself in line.
    0:42:25 So part of what’s just that lived experience that I had,
    0:42:27 but wasn’t my idea.
    0:42:28 We went to our vendor,
    0:42:29 this company called QMatic and I said,
    0:42:31 hey, so how does this work?
    0:42:32 They said, oh yeah, we have this feature.
    0:42:34 You guys didn’t wanna use it.
    0:42:35 I said, so how does it work?
    0:42:37 I said, they told me yet, just give your email address,
    0:42:39 put your phone in there, get your name
    0:42:41 and we’ll drop you online.
    0:42:43 So many of these companies have these features.
    0:42:46 We just didn’t understand exactly how to use them
    0:42:47 and the role they would play.
    0:42:49 And that’s actually an underutilized feature today,
    0:42:51 the get in line feature.
    0:42:52 I love it too.
    0:42:53 The first time I used it, by the time I got there,
    0:42:56 I was late and I was just doing it from the office
    0:42:58 and our nearest office is like a mile of the road.
    0:43:00 But it’s a really great way to allow customers
    0:43:03 to remove the long wait in the parking lot
    0:43:05 and just know that they’ve got a place.
    0:43:06 They can see the number being called,
    0:43:08 as it tells you where you are in line.
    0:43:09 I think it’s a great feature.
    0:43:11 And it was already in the product,
    0:43:14 but the idea I saw it being used was at Yelp.
    0:43:16 We actually contacted Yelp
    0:43:18 and the advantage of being the director of the DMV.
    0:43:19 When you contact people, they’re saying,
    0:43:21 oh my God, I did something wrong, my driver’s license.
    0:43:22 People call you back.
    0:43:24 You go through the investor relations door, right?
    0:43:25 That’s that door.
    0:43:26 People are responsive when you come in
    0:43:27 through the investor relations.
    0:43:30 And you get a lot of feedback from these other industries
    0:43:31 about what they’re doing, how they’re doing it.
    0:43:32 So we incorporated that.
    0:43:33 It was in the product already,
    0:43:36 so I don’t get any credit for inventing it.
    0:43:38 But I just recognize I’ve been using that product
    0:43:40 via Yelp for this local type place
    0:43:41 because it was this easier to get in line
    0:43:44 as I walked over there from my house in San Jose.
    0:43:45 – And wait, I’m just curious,
    0:43:47 not that I’ve never done this,
    0:43:49 but what happens if you get there
    0:43:50 and your number’s been called?
    0:43:53 – The team will then put you at the top of the list.
    0:43:55 – Okay.
    0:43:56 So there’s no downside.
    0:43:58 – There’s very little downside.
    0:44:00 – Okay, it’s good to know.
    0:44:01 I got a lot of questions.
    0:44:04 I’m fascinated by your business, okay?
    0:44:05 I’m sorry.
    0:44:06 – You gotta come volunteer some time here.
    0:44:09 We could use some guy in the business.
    0:44:09 – Sign me up.
    0:44:11 I’ll go get training from Tamika
    0:44:15 and Madison and I will staff the Capitola office.
    0:44:16 – We would probably just be happy
    0:44:18 if you help us think about some of our bigger problems.
    0:44:20 But if you wanna work at retail,
    0:44:21 we’re happy to put you at a window.
    0:44:25 – So I wanna know,
    0:44:30 why does the DMV register every car every year?
    0:44:32 Like I know there are 10 states
    0:44:34 that do every two years.
    0:44:37 I know Delaware is a permanent registration.
    0:44:40 Like I have six people in my family.
    0:44:43 That means at some point I own four cars or something.
    0:44:45 And I’m always filling out forms.
    0:44:48 I’m always worried that I missed the deadline,
    0:44:49 that I’m get the penalty.
    0:44:51 Can’t I register for a longer time?
    0:44:53 – Yeah, so I think there’s two issues there.
    0:44:57 One is that we’ve just launched a few months ago
    0:44:58 the concept of a garage.
    0:45:00 So you can put your vehicles in the garage.
    0:45:02 Now we’ve launched, you can cash your credit card.
    0:45:04 So again, these are just commercial services
    0:45:06 that all of us see at Amazon
    0:45:08 or wherever we might shop online.
    0:45:10 And then the next thing would be is to set them up
    0:45:11 for auto payment.
    0:45:13 So you will never be late again.
    0:45:16 But California’s law is that we do it on an annual basis.
    0:45:18 I’m not sure if that’s a budgetary thing,
    0:45:19 a cash flow thing,
    0:45:21 but I agree with you that if you did them
    0:45:22 two years at a time or whatever,
    0:45:26 I think the concern I hear and this is anecdotal
    0:45:27 that well, if you register for two years,
    0:45:28 you should sell your car.
    0:45:29 Now you have to deal with the,
    0:45:31 I’ve got to unwind that transaction.
    0:45:33 They didn’t drive it for the second year.
    0:45:35 I’ve got to give refunds and give me money back refunds.
    0:45:37 It’s just a convoluted process.
    0:45:39 There’s a lot of controls around that.
    0:45:41 So it’s fixed at one year.
    0:45:42 But we want to make that one year
    0:45:45 so that it’s easy so you can just put it on auto pay
    0:45:46 and like everything else in life.
    0:45:47 Got to remember to take things off auto pay
    0:45:49 when you don’t want them anymore.
    0:45:51 But that’s where we’re going.
    0:45:53 I tried.
    0:45:54 Sorry.
    0:45:58 Okay, now another question I’m curious about is,
    0:46:01 ’cause I can’t remember is donating your organs,
    0:46:03 is it opt in or opt out?
    0:46:05 It is opt in.
    0:46:08 Why can’t you make it opt out?
    0:46:09 Good question.
    0:46:11 That’s a statutory issue.
    0:46:13 I’m on the administration side of that.
    0:46:16 If the legislature wants it to be opt out,
    0:46:18 they can certainly write a bill
    0:46:20 and we will then adhere to that bill.
    0:46:23 We don’t make the rules, we just operate within them.
    0:46:27 But I think social psychology has proven
    0:46:32 that if it’s opt out, you’ll get like 90% opting
    0:46:35 or not opting in because you can’t opt in.
    0:46:38 But 90% of people would donate their organs
    0:46:39 if it was opt out, right?
    0:46:41 I’m sure donate life in California
    0:46:43 would be happy to have that.
    0:46:45 I’m sure they’re probably working on some legislation
    0:46:47 in that area, but it’s not there today.
    0:46:51 – Okay, what’s the relationship with business partners
    0:46:54 like AAA and I understood the AAA business partner,
    0:46:59 but then I saw that there’s insurance brokers and stuff.
    0:47:00 Did AAA come to you and say,
    0:47:03 please let us do some of this or did you go to AAA
    0:47:06 and say, take some of the load off of us?
    0:47:09 – No, it predates me, but what I’ve heard
    0:47:13 and I believe this is true that AAA back in the day,
    0:47:16 a hundred and some years ago, used to be the DMV.
    0:47:19 And then the state said,
    0:47:21 actually we wanna take over that responsibility,
    0:47:24 but AAA is then because of that past relationship.
    0:47:25 And again, you have to Google this,
    0:47:28 but we’ve been in business for 115, 117 years.
    0:47:30 And so before that AAA,
    0:47:32 the automobile association was the place
    0:47:33 you had vehicles registered.
    0:47:35 Now, we should check this.
    0:47:37 I’m sure your audience is gonna fact this,
    0:47:38 but I believe that to be true.
    0:47:41 And so they have a special relationship with us.
    0:47:43 And so we extend our systems into AAA.
    0:47:45 So they have a special relationship
    0:47:48 that they are part of us and they can do transactions
    0:47:52 in a unique way and there’s no uplift on what they charge.
    0:47:54 At some point over the past number of years,
    0:47:57 there’s this business partner program
    0:47:59 that has grown inside of California.
    0:48:00 And there’s a couple of levels,
    0:48:02 but at the retail level,
    0:48:05 which are talking about insurance companies, small shops,
    0:48:06 you see them around every corner.
    0:48:09 And there’s 6,000 plus retail sites.
    0:48:13 There’s a belief that having those services in the community
    0:48:14 is a good thing.
    0:48:16 People are more likely to consume a service
    0:48:17 if it’s within their community.
    0:48:20 And there’s some evidence to say that’s true.
    0:48:21 By and large though,
    0:48:24 that the people that are probably doing the most with this
    0:48:25 are some of the online retailers.
    0:48:29 And that’s a bit tricky because they charge an uplift
    0:48:31 for the service in this business partner program.
    0:48:33 And if you’re not careful for the same service,
    0:48:37 you can get at retail price, no uplift from us,
    0:48:41 vehicle registration, you’re paying that same fee
    0:48:44 and then you’re paying a $39 uplift.
    0:48:45 And that infuriates some folks
    0:48:48 ’cause they’re listed as a partner.
    0:48:49 The people missed the point
    0:48:51 that they didn’t need to go down that road to get that done.
    0:48:54 But anyway, there’s 6,000 plus of those across the state.
    0:48:56 There’s a few large online retailers.
    0:48:57 And then on top of that,
    0:48:59 there’s this first line service providers.
    0:49:01 Think about it as a two tier distribution model.
    0:49:03 The first line partners, there are five of them.
    0:49:06 And those people actually then license all the people
    0:49:07 that are underneath them.
    0:49:09 And California is unique in the sense that
    0:49:11 the people that are actually in that channel,
    0:49:13 dealers are part of that channel.
    0:49:15 If you’re a franchise new car dealer in California,
    0:49:18 you are required to do an e-report of sale,
    0:49:19 electronic report of sale.
    0:49:20 And you’re required to use
    0:49:23 one of those first line service providers to do it.
    0:49:25 And ’cause we wanna make sure the forms come into us,
    0:49:27 they come in right and so on.
    0:49:30 And so you see those fees listed out when you buy a car.
    0:49:33 And at the next level, if you’re a used car dealer,
    0:49:36 but you’re also required to participate in those systems,
    0:49:37 but in a different way.
    0:49:40 We want all those documents coming to us electronically.
    0:49:42 So that distribution model works
    0:49:44 and it’s cut a lot of different facets to it.
    0:49:46 But at the retail level, the insurance shop,
    0:49:47 the smog shops and so on.
    0:49:50 Yeah, that’s just brick and mortar additional services
    0:49:53 that have been enabled across the state
    0:49:54 and are used in local communities.
    0:49:56 ‘Cause sometimes that’s where you can speak
    0:49:59 a certain language, although we support 36 languages.
    0:50:01 It’s a complicated world guy.
    0:50:04 – Okay, Steve, now, if you thought I was being tactical
    0:50:06 before, I’m gonna get a really tactical,
    0:50:08 ’cause I am very curious.
    0:50:09 – Look at the time.
    0:50:10 No, no.
    0:50:11 (laughs)
    0:50:14 Okay, these are gonna be quick and easy questions, okay?
    0:50:16 But stuff I’m wondering about.
    0:50:18 And I bet a lot of people are, okay?
    0:50:21 So I want to know if you understand
    0:50:26 how the HOV FastPass pricing on Highway 101
    0:50:29 in San Mateo County works.
    0:50:32 Because I have been in that lane
    0:50:36 and that lane says HOV two or more.
    0:50:38 FastPass required.
    0:50:42 FastPass is from three to six p.m.
    0:50:45 Except if you have an HOV or something.
    0:50:48 I am driving along at, of course, I’m going speed limit,
    0:50:51 but I am driving along in my plug-in hybrid car.
    0:50:54 And for the life of me, I cannot figure
    0:50:57 if I’m gonna be pulled over or not.
    0:50:58 Do you know how that works?
    0:51:01 – No, I read those signs too and say, I have no idea.
    0:51:02 So I look for the next signposts
    0:51:03 and see if I can figure it out piece by piece.
    0:51:07 But I’m like you, it’s unclear what’s categorized
    0:51:08 in the three or plus, two plus,
    0:51:10 spend of where you are in the state as well.
    0:51:12 So unfortunately, I’ll kick that over to our friends
    0:51:15 at Caltrans and to the State Transportation Commission.
    0:51:17 – Okay, fair enough, fair enough.
    0:51:18 All right, I can’t figure that out.
    0:51:18 Sorry.
    0:51:21 – Okay, see you are honest.
    0:51:26 All right, so now I have a plug-in hybrid
    0:51:28 and I found out to my surprise
    0:51:30 that I can get an HOV sticker,
    0:51:32 but it expires in September.
    0:51:37 So why are there short-term HOV stickers for some models?
    0:51:38 – Well, they’re not short-term.
    0:51:40 They mirror the federal fiscal year.
    0:51:42 That’s why they end at September 30th.
    0:51:44 And it’s a federal law.
    0:51:47 These are federal roads that they allow California
    0:51:50 and other states to give certain privileges to HOVs.
    0:51:53 So we have to go and have the federal administration,
    0:51:54 I’m not sure if it’s federal highways or NITS,
    0:51:56 I think it’s federal highways.
    0:51:58 This is their program that they allow California
    0:52:00 to allow people into the HOV lane.
    0:52:01 We give a sticker as a result of that
    0:52:02 so we can identify those vehicles
    0:52:06 and make sure they qualify for emissions and so on.
    0:52:08 So the reason that it only is good to September,
    0:52:10 that is the end of the federal fiscal year.
    0:52:12 So we’re waiting right now to find out
    0:52:13 if the federal government is going to continue
    0:52:17 to extend that for the next year or the years past that.
    0:52:20 But at this point, September 30th of this calendar year
    0:52:23 is the last time you’ll be able to use an HOV sticker
    0:52:25 in California at all without–
    0:52:25 – Any car.
    0:52:28 – Without federal, without a change in federal rules.
    0:52:29 Yes.
    0:52:31 – Wow.
    0:52:34 I’m sure there’s some 19-year-old undergraduate
    0:52:35 who’s looking into that for us.
    0:52:40 So next question is I have the app wallet MDL
    0:52:45 and I don’t quite understand.
    0:52:47 If I get pulled over by the CHEP
    0:52:49 and I don’t have my physical license,
    0:52:51 can I just show my phone?
    0:52:52 Is it good enough for that?
    0:52:55 – Yeah, law enforcement has not updated processes
    0:52:58 to consume the MDL and a lot of places haven’t.
    0:53:00 So I’ve been working with my counterpart,
    0:53:01 the commissioner of the CHP,
    0:53:03 and I think he’s looking to figure out
    0:53:05 how do we make vehicle stops more efficient,
    0:53:08 more effective, safer for the officer
    0:53:10 and for the passengers and the vehicle.
    0:53:12 And, but this sort of change takes time.
    0:53:15 So we’re just getting TSA to be able to take
    0:53:16 the MDL at the airport.
    0:53:18 I was just at Sacramento Airport just last week.
    0:53:20 They’re announcing the next tranche of airports
    0:53:23 that will take a mobile driver’s license.
    0:53:24 California is the only state
    0:53:26 that also uses a different technology.
    0:53:28 So we have the ISO standard,
    0:53:30 which is what you’ll see in the MDL at the airports.
    0:53:33 And there’s a verifyable credential W3C standard
    0:53:35 that allows us to be able to have something
    0:53:37 that could be used, not only on websites
    0:53:39 for web purchases, but also in retail.
    0:53:41 And so we’re working with a company called TrueAge,
    0:53:44 which represents these convenience stores
    0:53:46 and to be able to consume the mobile driver’s license
    0:53:47 at convenience stores.
    0:53:49 So it’s an emerging technology guy
    0:53:51 and law enforcement is going to get there.
    0:53:53 And we’re working with law enforcement.
    0:53:54 I have a chance.
    0:53:55 I get to know the commissioner
    0:53:57 of the California Habitorial, Sean Dury,
    0:54:00 marvelous guy and he wants to modernize this thing.
    0:54:01 And we’re working with him to do that.
    0:54:03 So you can actually have the engagement.
    0:54:04 They can have a safe transaction.
    0:54:07 They can pre-fill some forms if you’re going to get a citation.
    0:54:09 So that day is coming, but it’s not coming today.
    0:54:12 – Okay, so the bottom line is carry your physical license.
    0:54:14 – You need to carry your physical license.
    0:54:15 Yes. – Okay.
    0:54:19 Now this question, I only have two more.
    0:54:24 This question I’m asking for a friend, all right?
    0:54:29 So I know that if you flunk the driving test twice,
    0:54:30 and if you flunk it again,
    0:54:33 you got to start all over with the permit process.
    0:54:36 At least, I think that’s still true, right?
    0:54:40 What happens if my friend takes his kid
    0:54:45 and they go to the DMV and they watch the route
    0:54:48 that the test goes on, they follow a test driver
    0:54:50 and they say, okay, so now we know exactly
    0:54:52 which route that person is taking.
    0:54:55 So when you go for your driver’s test,
    0:54:57 we’re going to practice on that route.
    0:54:58 Is that legal?
    0:55:02 – I’m sure this friend has been to one of the driving schools
    0:55:04 so that’s one of the requirements for first-time drivers.
    0:55:07 Those driving schools know the routes the DMV takes,
    0:55:09 but that doesn’t mean you’re going to pass the test.
    0:55:10 So I think it’s, yeah, it’s certainly legal to do that.
    0:55:11 I wouldn’t encourage you to do that,
    0:55:13 drive safely at the right distance.
    0:55:15 But the net of it is you still have to drive.
    0:55:18 My son, we were living in San Jose at the time,
    0:55:21 he took his at the Las Gatos office
    0:55:22 and he pulls out the parking lot
    0:55:25 and there’s a truck that is unloading
    0:55:27 in the middle of the street.
    0:55:29 Even if he knew the route, which he did not,
    0:55:30 you have to be able to handle this obstacle
    0:55:32 that was in the middle of the road that,
    0:55:35 do I go to the right, do I go to the left, do I wait?
    0:55:37 So there are those things.
    0:55:39 And that’s why people, I think, they’re challenged.
    0:55:41 You have to be able to know how to stop, how to navigate.
    0:55:43 Even if you know the route, it doesn’t really matter.
    0:55:46 You still have to know how to get around the block
    0:55:47 and down the street.
    0:55:52 – All right, because this friend used this story in a book
    0:55:57 to illustrate the concept that there’s always a way
    0:55:59 to prepare for tests.
    0:56:01 And if you can figure out a way to prepare for tests,
    0:56:03 you can do better on the test.
    0:56:07 And when this friend wrote this story in his book,
    0:56:10 some people read that and said, in New York,
    0:56:15 it’s illegal to follow an exam to learn the routes.
    0:56:19 So I’m just asking for this friend who lives in California,
    0:56:20 if it’s illegal here.
    0:56:22 – Yeah, I don’t think it’s illegal.
    0:56:23 I don’t know if it’s wise to do that.
    0:56:24 Focus on the fundamentals.
    0:56:25 That’s what I did with my son,
    0:56:28 make sure he had enough reps and enough things.
    0:56:29 That’s where you should spend your time.
    0:56:32 – Okay, this is my last question.
    0:56:35 My last question is,
    0:56:38 I applied for personalized play three months ago.
    0:56:40 Can you check if it’s done yet?
    0:56:41 – Sure.
    0:56:43 (laughing)
    0:56:46 – I’m gonna call up Tamika and say,
    0:56:48 “Tamika, can you please help me?”
    0:56:51 – She would love that phone call, by the way.
    0:56:53 Personalized Plates is a couple of things, right?
    0:56:55 So we’ve changed the way we do personalized plates,
    0:56:56 where we have an AI agent now
    0:57:00 that helps us validate if the plate’s gonna be offensive.
    0:57:02 And there’s no shortage of things that are offensive,
    0:57:05 that are clear, edge cases.
    0:57:06 And then from there, there’s a manufacturing process,
    0:57:09 ’cause each one of these things requires a special stamping,
    0:57:10 and that takes some time,
    0:57:12 but it shouldn’t take any longer than that 90 days.
    0:57:16 So off the air, you can outsource to Madison
    0:57:18 and shoot me the VIN,
    0:57:20 and then I’ll take a look at where it is.
    0:57:21 – Wait, are you telling me
    0:57:25 that it’s not somebody in Soledad who’s making my plates?
    0:57:27 It’s not a prison thing, that’s a myth.
    0:57:29 – No, no, no, no, it’s not Soledad, but it’s in Folsom,
    0:57:30 and it is not a myth.
    0:57:33 There are stamping machines, and there’s-
    0:57:34 – In Folsom Prison.
    0:57:35 – Yeah, I’ve been there.
    0:57:36 It’s prisons, by the way,
    0:57:37 if you’ve never been inside of a prison,
    0:57:40 they’re pretty depressing, so let’s start there.
    0:57:43 But there’s a team of folks that are part of the production
    0:57:44 line that actually stamp plates,
    0:57:46 and they do a great job,
    0:57:47 and it just still takes a little while.
    0:57:49 Plates are stamped in California,
    0:57:52 and it’s a very sophisticated process,
    0:57:54 but it’s also done inside the prison,
    0:57:58 so if there’s a problem, your supply chain could be disrupted.
    0:58:02 – I have visited San Quentin twice, and I gotta tell you,
    0:58:04 I’ve been scared a few times in my life,
    0:58:08 but man, just walking through the prison,
    0:58:12 it’s truly a myth, just like the wire, man.
    0:58:15 I was scared shitless the whole time.
    0:58:17 – Yeah, yeah, I would encourage you to stay out of prison.
    0:58:19 But again, off the air,
    0:58:21 shoot me the vehicle identification number, the VIN,
    0:58:23 and we’ll take a look, tell you where it is.
    0:58:25 90 days is probably right in the window,
    0:58:27 because it just takes time to get that into queue.
    0:58:28 It’s a special one-off process.
    0:58:30 We got our sequential plates that are cranking through,
    0:58:32 so they gotta stop that line to do,
    0:58:34 oh, this is Guy Kawasaki’s plate.
    0:58:37 I mean, with reverence, there’s probably some incense,
    0:58:38 or whatever we do.
    0:58:39 No, I’m kidding.
    0:58:40 There’s no incense.
    0:58:43 – Well, Steve Gordon,
    0:58:46 this has been a most enjoyable episode, and thank you.
    0:58:47 Besides all the humor,
    0:58:49 there’s some very important lessons
    0:58:52 about the professionalism of your organization,
    0:58:55 how you manage by driving around,
    0:58:58 and how these people have a mission,
    0:59:00 they are proud of what they do,
    0:59:04 and like for the 15th time, just let me tell you,
    0:59:06 I really love the California DMV.
    0:59:07 – Great, Guy, thanks for having me on,
    0:59:09 and thanks for helping promote our services,
    0:59:11 we really appreciate it.
    0:59:12 – All right, and I’m serious.
    0:59:16 If you ever want evangelism advice, I’m here for you.
    0:59:17 – I’m gonna take you up on it.
    0:59:18 Next time I’m down in the Capitola era,
    0:59:19 I’m gonna call you up as well.
    0:59:21 We’re gonna see if you’ll show up.
    0:59:22 – We’ll see.
    0:59:26 – I’ll greet you at the DMV.
    0:59:27 – That would be great, I look forward to that.
    0:59:30 – So, this was Steve Gordon, California DMV,
    0:59:33 and I hope you enjoyed this episode,
    0:59:36 listening to it as much as I enjoyed recording it
    0:59:37 and doing it.
    0:59:40 So this is Guy Kawasaki, it’s a remarkable people.
    0:59:43 I hope we made you a little bit more remarkable today.
    0:59:46 Thanks to Madison Nizmer, producer, co-author,
    0:59:51 Tessa Nizmer, researcher, and Jeff C. and Shannon Hernandez.
    0:59:53 We are the Remarkable People team,
    0:59:55 and we’re trying to make you remarkable
    0:59:59 and get a remarkable car registration experience.
    1:00:01 Thank you everybody.
    1:00:08 – This is Remarkable People.

    Guy Kawasaki sits down with Steve Gordon, Director of the California Department of Motor Vehicles (DMV). Gordon, a former Cisco Systems executive, shares how he transformed one of the state’s most crucial yet historically frustrating agencies into a customer-focused operation. From implementing digital signatures to managing a network of 220+ offices, Gordon reveals the innovative approaches that revolutionized the DMV experience. His leadership philosophy of “management by driving around” and commitment to operational excellence offers valuable lessons for any organization seeking to improve public service.

    Guy Kawasaki is on a mission to make you remarkable. His Remarkable People podcast features interviews with remarkable people such as Jane Goodall, Marc Benioff, Woz, Kristi Yamaguchi, and Bob Cialdini. Every episode will make you more remarkable.

    With his decades of experience in Silicon Valley as a Venture Capitalist and advisor to the top entrepreneurs in the world, Guy’s questions come from a place of curiosity and passion for technology, start-ups, entrepreneurship, and marketing. If you love society and culture, documentaries, and business podcasts, take a second to follow Remarkable People.

    Listeners of the Remarkable People podcast will learn from some of the most successful people in the world with practical tips and inspiring stories that will help you be more remarkable.

    Episodes of Remarkable People organized by topic: https://bit.ly/rptopology

    Listen to Remarkable People here: **https://podcasts.apple.com/us/podcast/guy-kawasakis-remarkable-people/id1483081827**

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  • Kurt Gray: Understanding Outrage to Heal America

    Kurt Gray: Understanding Outrage to Heal America

    AI transcript
    0:00:05 it takes a fifth of a second for your flight or flight response to be activated and 20 minutes
    0:00:12 for it to calm down. And so part of, I think, managing outrage is just taking some time and space
    0:00:19 away. It’s okay. It’s okay to walk away from the situation and say you need a little bit of time
    0:00:24 to calm down when you think about it. And it’s okay to schedule it for a different time when
    0:00:29 you’re not feeling any like don’t send emails in anger. Try not to talk about politics when you’re
    0:00:34 filled with rage. But I think what I try to do, and to get to the, you know, your point about
    0:00:42 thinking about the minds of others, is to think about like how these folks that I disagree with
    0:00:48 might feel victimized and the harms that they see. Because once you see that the harms that someone
    0:00:53 else is worried about or how they feel like they’ve been victimized, even if I don’t agree
    0:00:58 with their position, I can at least see them as a little more human. And that goes a long way.
    0:01:06 I’m Guy Kawasaki. This is “Remarkable People.” We’re on a mission to make you remarkable,
    0:01:12 so we bring in remarkable guests so that they can pass on their knowledge and wisdom and tactics
    0:01:22 and strategies. Today’s remarkable guest is Kurt Gray. He earned his PhD in psychology at Harvard.
    0:01:28 He’s currently a professor of psychology and neuroscience at the University of North Carolina
    0:01:33 Chapel Hill. Is that where Michael Jordan went to school? You bet, you bet.
    0:01:40 He’s the second most famous graduate of the University of North Carolina Chapel Hill.
    0:01:48 And he’s the director of, I have never heard of academic labs named like this, but he’s the
    0:01:54 director. I got to read this to make sure I got it right. He’s the director of the Deepest Beliefs Lab
    0:02:00 and the Center for the Science of Moral Understanding. That’s quite a mouthful.
    0:02:08 Yeah, we rebranded. I thought we study everyone’s deepest beliefs, politics, religion, morality,
    0:02:16 and why not name the lab what we do? Yeah. It couldn’t just be the University of North Carolina
    0:02:26 Neurosciences Lab, are we? Okay, so let’s just ease into this interview, all right? And I’m inspired
    0:02:31 by something at the very end of your book where you discuss the work of John Saroof. I hope I
    0:02:37 pronounced that right. And so you asked him a very easy question, which I’m going to now ask you,
    0:02:45 which is, what are the three easy steps to heal America? Could you just get to that in like 60
    0:02:52 seconds or so? First, he laughed and he said no. He’s like, it’s too hard, but then he tried to kind
    0:02:59 of lay it out. And so I figured the best three steps from what I could, and they are how to have
    0:03:06 better conversations with each other. And so those three steps are connect in conversations, invite
    0:03:12 in conversations, and then validate. So those are the three steps. It’s a way of having conversations
    0:03:18 about politics that we frequently, well, we don’t have. I’m happy to go through those steps.
    0:03:24 Yeah, because there were lots of things in those steps which I found counterintuitive.
    0:03:31 For example, you talk about it’s better to ask too many questions than too few. So can you just
    0:03:37 tell us like, connect? What’s the power tips for connect? Totally. And all this is against a backdrop
    0:03:42 of like, you’re trying to have conversations across differences. It’s hard. You want to do it. You
    0:03:46 want to talk to your uncle that you haven’t talked to him while you’re a co-worker who disagrees with
    0:03:52 you sometimes. And so the CIV is the SIV, the beginning of more civil conversations. So that’s
    0:03:57 where the kind of term comes from. So connect. The first thing you want to do before you talk
    0:04:02 about anything contentious is connect with someone as a person. There’s so many things that you could
    0:04:07 talk about that aren’t like politics or what you disagree about, right? Food, music, family,
    0:04:13 jobs, whatever, you know, weather. I mean, weather is boring, right? And let’s get away from the
    0:04:19 weather and let’s ask deep questions. So it turns out that people really like when you ask them
    0:04:25 questions, especially surprisingly, deep questions, right? When we think of someone who’s a good
    0:04:30 conversationalist, we think of someone who talks a lot. But what we really like is someone who asks
    0:04:35 us deep questions. So think about conversations as more like a date. Like if you went on a date with
    0:04:40 someone and they just talked at you forever, you’d think, oh my goodness, like what a windbag.
    0:04:45 But when someone asks you questions, follow up questions and, you know, about you,
    0:04:49 where’d you grow up? Oh, what was it like growing up to? How did that shape you? How did it make you
    0:04:54 who you are today? What hopes and dreams do you have about the future? When’s the last time you
    0:04:59 cried? These questions might seem crazy to ask someone, but people really appreciate connecting
    0:05:08 deeply in conversations. And what about the quantity of questions? Yeah, more than you think. It’s
    0:05:12 more than you think is better, especially follow up questions, right? So you can imagine having
    0:05:18 conversation with someone and lots of research to back this up. Someone says, here’s this heartfelt
    0:05:25 story of me. And once my kid’s fish just died, very tragic. We had to bury my daughter’s fish
    0:05:30 out back and imagine I told you this story of my fish dying. And then instead of you saying, wow,
    0:05:34 that must have been really hard. I’m sorry for your fish loss. You know, you’re just like, oh,
    0:05:38 yeah, yeah. Anyways, I went fishing the other day and that this is what reminded me of fish.
    0:05:44 You know, like that’d be terrible. And so you want to ask follow quite right how your daughter’s
    0:05:50 dealing with it. Did you have a special ceremony for the fish? And it’s a funny example, but follow
    0:05:56 up questions, show that you’re listening. And so I think that is an important thing for connecting.
    0:06:04 We had a guest about a week ago who she cited many studies about speed dating. And she gave us
    0:06:10 all these speed dating tips. And she basically said exactly what you said. Maybe you guys are
    0:06:16 both talking about the same studies. But she said, in speed dating, you got to ask a lot of questions
    0:06:22 and you got to go deep really fast to stand out from other speed daters. Yeah, just human nature,
    0:06:28 right? It’s what humans want. Yeah. Because if you’re just like, hey, pretty hot out, isn’t it?
    0:06:36 Okay, sure. You’re not connecting with that. All right. Okay, so that’s connect now. Invite.
    0:06:44 Invite. So invite, if you want to talk about some like deep issues, the invitation is something
    0:06:50 that people appreciate. And an invitation means that something where someone can say no, right?
    0:06:55 So if I’m inviting you into a party, you can say no. But if I’m demanding you to go to a party,
    0:06:59 that’d be kind of a jerk move, right? I’m having this party and you better come or else.
    0:07:04 And I think when we talk about politics and we talk about moral questions, we often do demand.
    0:07:09 How could you vote for this person? How do you believe this? Explain to me, right? Like,
    0:07:13 justify yourself. No one needs to feel like they’re justifying who they are, what they believe.
    0:07:19 And so an invitation is really focused on understanding and the intention there is learning.
    0:07:27 So please, I’d love to learn what you think about immigration. And I know maybe we disagree,
    0:07:31 but I’m just like, I’m trying to understand and I want to understand where you’re coming from
    0:07:35 and what experiences might be of lead there. So I just really appreciate hearing kind of your views,
    0:07:39 even if they’re different from what I think. How about if you say to the person,
    0:07:46 can I ask you a question about immigration? That’s good. Yeah, that’s a great place to start.
    0:07:55 And a question before the question, that’s perfect. Yeah. Okay, now can I ask you about validation?
    0:08:02 Thanks for the invitation. I’m happy to share. See, like it worked. It just worked for us right
    0:08:07 now. So you know, you invite someone to share something that is going to be hard for them to
    0:08:13 share invitation. You’re like putting in kind of a little like grace, I like to say, you know,
    0:08:17 I talked to a lot of churches. So you’re like putting in some grace, like I’m inviting you.
    0:08:21 And I know it’s going to be hard for you to share this thing. And you’re probably going to say
    0:08:24 something offensive. You don’t need to say that to someone, but like, come up with a mindset that
    0:08:30 someone might say something offensive to you. And then they’ll say something. And then maybe your
    0:08:35 first reaction is to say, I don’t think that or what about this? Here’s this other thing you
    0:08:40 are considering. You want to say no right away, you want to like fire back something, but you should
    0:08:45 resist that impulse and instead validate. It doesn’t mean agree. It does mean, thanks so much for
    0:08:50 sharing that I understand it’s hard to share. If I’m listening correctly, I think you mean this,
    0:08:56 and I’m going to rephrase it in a way that’s very charitable. And then that’s going to make you feel
    0:09:00 heard. It’s going to make you feel seen. And it’s going to allow us to have a better conversation
    0:09:07 after that. And it’s not part of CIV, but you also make a very big deal about showing that
    0:09:14 you’re vulnerable. So how does vulnerability play into this? Yeah, I guess taking a step back,
    0:09:20 the goal for all these conversations is to see the humanity in each other, right? To recognize
    0:09:26 that we’re all good people. We’re all trying to figure out our lives and our world. And oftentimes
    0:09:32 when we’re disagreeing with someone, we and this is John Saroo’s turn, we flatten them. We see them
    0:09:37 as two dimensional. And so all this is a way of seeing someone in their rich, three dimensionality.
    0:09:44 You want to connect, you want to invite, you want to validate, and you want to let them see you as
    0:09:51 well as someone who is human. And a big part of that is vulnerability. So I’m going to share the
    0:09:55 stories after you shared with me. I feel comfortable with you now because we’ve had a connection.
    0:10:01 And so I’m going to share the stories of suffering, of harm, my concerns. And so you can see
    0:10:07 that I’m really basing my moral judgments, my concerns in questions about harm, because that’s
    0:10:13 where our minds are rooted when it comes to morality and politics and concerns about protection.
    0:10:21 So the name of your book is Outrage. And I have to ask a very simple question, which is what causes
    0:10:30 people to get outraged? It’s a great question. It’s a pretty simple answer. And the answer is we
    0:10:40 get outraged when someone rejects or challenges or defies our understanding of what is harmful
    0:10:47 and who is vulnerable to harm. So we get morally outraged when we see someone causing harm
    0:10:52 or rejecting our understanding of who or what is harmful.
    0:11:02 And would you say that being outraged is highly correlated with justifiable reasons to be outraged?
    0:11:08 If you stepped aside, would it be irrational to be outraged?
    0:11:16 Here’s the thing. So outrage evolves as a way of protecting ourselves. So if in our community,
    0:11:22 someone did something that we thought was harmful, we would all band together in anger,
    0:11:27 we’d grab our pitchforks, our torches, and we would kick that person out of the community,
    0:11:34 or we would punish them or censor them somehow. Except today, we’re no longer faced as much with
    0:11:39 kind of things that we all agree are harmful. Instead, we disagree, immigration, abortion,
    0:11:45 taxes, different people on the left and right disagree about what’s harmful and what’s worthy
    0:11:52 of outrage. And so going back to your question, it’s really hard to know what’s the rational
    0:11:58 right thing to be upset about because there are so many people on each side of an issue
    0:12:03 who have a legitimate point often. And so I think it’s hard to say what’s rational and what’s not.
    0:12:16 We can all agree on some things, but other things we’re very far apart on.
    0:12:30 As I was reading your book, this section about outrage, a moral outrage, I just thought, would
    0:12:38 you say that the United States reaction to 9/11 was the mother of all examples of moral outrage?
    0:12:44 I mean, it’s certainly, there’s a case to be made. So we were harmed. We were harmed by
    0:12:53 someone we thought is a true villain, in this case, Bin Laden, and like foreign folks doing harm on
    0:12:58 our soil, attacking our institutions. And certainly we were collectively outraged enough, we came
    0:13:04 together and then tried to punish the folks who caused that harm. I think that’s a good example.
    0:13:11 But isn’t the point of your book that we should look at it from the other perspective and see
    0:13:19 what drove them to do 9/11? Or is that a stretch? I think the point of the book is to understand
    0:13:25 how everyone has the same moral mind and we’re all driven by outrage. And so I think it’s
    0:13:32 justifiable that many Americans were outraged at that act. But I do think that failing to appreciate
    0:13:37 the kind of mindset of, let’s say, folks in Afghanistan, folks in Iraq, other folks in the
    0:13:43 Middle East is like, you know, America goes in there and causes a lot of harm. I think we maybe
    0:13:49 needed to think about how they might feel outraged at America in return, right? There’s always two
    0:13:54 sides of any issue. And there’s always people who take the other side. So at least we should have
    0:13:57 had a better understanding of what they’re thinking and what they’re feeling.
    0:14:05 So do you have a practical tip that when you’re feeling moral outrage, you know,
    0:14:11 before you react, you should take these steps or do you just start launching B-52s?
    0:14:17 Well, you know, John Sirouf has this other quote that I really like when he’s working with
    0:14:24 divided communities. And he says, “It takes a fifth of a second for your flight or flight response
    0:14:32 to be activated and 20 minutes for it to calm down.” And so part of, I think, managing outrage is
    0:14:39 just taking some time and space away. It’s okay. It’s okay to walk away from the situation and
    0:14:45 say you need a little bit of time to calm down when you think about it. And it’s okay to schedule it
    0:14:49 for a different time when you’re not feeling anger. Like, don’t send emails in anger. Try not to
    0:14:54 talk about politics when you’re filled with rage. But I think what I try to do, and to get to your
    0:15:02 point about thinking about the minds of others, is to think about, like, how these folks that I
    0:15:08 disagree with might feel victimized and the harms that they see. Because once you see that the harms
    0:15:12 that someone else is worried about or how they feel like they’ve been victimized,
    0:15:18 even if I don’t agree with their position, I can at least see them as a little more human. And that
    0:15:25 goes a long way. Author to author. I’d like to ask you this question or maybe I should pose it as
    0:15:35 author to author. May I ask you a question? Yes, you bet. So did you consider titles for your book
    0:15:42 that were not quite violent or negative? Instead of outraged, it would be like harmless or something
    0:15:49 like that, the flip side of outraged. I did consider harm less. I thought that would be nice.
    0:15:55 The original title, the kind of secret working title was The Victim Within, which is a negative
    0:16:03 but maybe less violent. It turns out no publisher wanted that book. You’re a victim and no one
    0:16:07 wants to walk through the bookstore and be like, you know what, I am a victim, even if we might
    0:16:12 all feel like it at some times. But I think we thought that the one word title, you know, with
    0:16:18 a bright orange cover and the aggressive question or exclamation mark rather, maybe a question mark
    0:16:25 would have been better, right? Outraged. But I think we wanted people to resonate and many people
    0:16:30 are feeling outraged today and we wanted to help them make sense of that. Okay, fair enough. And
    0:16:38 now I’m going to ask you one more author to author question that I noticed. And you may find this
    0:16:46 really bizarre, but on page 190 of your book, I have a question. And let me read a quote. So on
    0:16:54 page 190, it says, “Most conservatives generally want to protect black men and most liberals
    0:17:00 generally want to protect the police.” Is that an error? Is that a typo? Was it transposed?
    0:17:09 No, no, because it is the case that when we think of progressive folks and conservative folks,
    0:17:13 we generally think of conservative folks being more concerned about the police. Progressive
    0:17:20 folks being more concerned about protecting black men, black lives. But it is the case that most
    0:17:26 progressives do think that police officers are good and want to protect them. Oh, okay, I get it
    0:17:33 now. Okay, so you were like busting two myths there. Exactly, exactly. And where the disagreement
    0:17:38 comes is like the relative concern when those two groups, those two interests are kind of
    0:17:45 pit against each other. But most people want to protect most other people. I read that sentence
    0:17:52 about four times and I said, is this an error? What is he trying to say? So I stand corrected.
    0:17:56 I stand corrected. Thank you very much for clarifying. But you’re right. We have these
    0:18:02 myths that the other side is so stuck in their political positions that they don’t care about
    0:18:08 the other side or other interests. But most people do generally care for others and want a world where
    0:18:14 people are protected. Just these disagreements come down to these trade-offs. The foundation of your
    0:18:20 book is something that I never considered, which is I’ve had many social psychologists on this
    0:18:25 podcast and there are many explanations for this divide in the United States. But
    0:18:33 none of whom have ever said something like harm is the key variable and the master key to explain
    0:18:40 human morality. So can you explain why harm is such a big deal? Because I never considered it. I
    0:18:47 never thought of it like that. I think the reason that harm is the master key of morality is because
    0:18:54 we as a species and as individuals, we’re really concerned with protecting ourselves
    0:19:01 and we evolve through time as being threatened. If you go out, I make the argument that we’re
    0:19:06 a lot more prey than predator. If you go out into the forest and you strip down to your underwear
    0:19:11 and you wait for nighttime and you hear a twig snap behind you, you’re not going to think, oh
    0:19:16 good, I hope it’s an animal that I can eat. You’re going to think, oh my goodness, right? Something’s
    0:19:22 coming to eat me. Something’s coming to kill me. And if you walk through a dark alley and you hear
    0:19:26 some shuffling in the darkness, you’re going to think, oh no, there’s something there. There’s
    0:19:32 something trying to get me. So we are so attuned to threats because the revolution that people who
    0:19:37 were not attuned to threats, they died. If you were like, oh look, there’s like something lurking
    0:19:41 in the darkness. I’m going to go try to hug it. You got eaten. And so we’re attuned to threats and
    0:19:47 in the past, those threats were clear. The predators are people who might kill us.
    0:19:53 But today, those threats are a little more ambiguous, right? Are immigrants a source of
    0:19:59 income for America? Or are they threats? Are taxes going up? Or is that bad? Is that good? So today,
    0:20:03 we’re divided by what’s the most threatening. But at the heart of all our moral judgments,
    0:20:08 is this concerned about protecting ourselves from harm? And that’s why it’s the master key.
    0:20:16 And if someone from 100 years ago took a time machine and came to America today
    0:20:23 and saw what we considered harmful threats, would that person just be scratching their
    0:20:30 head and saying, listen, you guys, you got to have more serious things to worry about than,
    0:20:34 I don’t know, not being able to get into Harvard. That’s not the biggest threat in the world.
    0:20:42 I think you’re exactly right. I often think, going back in time, if you went to a parent
    0:20:48 in the Industrial Revolution, and their kids were working in a factory, it’s dark, it’s hot,
    0:20:53 there’s spinning machinery that could catch your hand and cut it off. And they’re thinking every
    0:20:58 day, I hope my child’s going to come home. And then, as you say, you tell them, you’re like,
    0:21:04 maybe your kid’s not going to get into this elite school, or maybe your kid is going to
    0:21:06 look at the screen too much. They didn’t have a screen, maybe you don’t understand, right?
    0:21:10 But if they look at the screen too much and not feel fulfilled, the parent will be like,
    0:21:16 I just hope they come home with their hands. And so, it’s not saying that these harms we’re
    0:21:22 worried about today aren’t real to us and don’t cause concern, but it’s certainly a stretch from
    0:21:28 days of your. So let me ask you something so that if you are dealing with someone who you
    0:21:36 disagree with, should you be so transparent and ask them what harm they are seeing or what harm
    0:21:41 they’re trying to avoid? Can you just be that blunt and ask, what’s threatening you?
    0:21:49 I think you can. I think I probably wouldn’t start with that. Going back to the CIV, I would
    0:21:55 probably get into the conversation a little more obliquely, talking to them as a person.
    0:22:00 But I think it’s totally reasonable, once you’re actually talking about politics, about morality,
    0:22:06 to say, what are you most worried about? What do you think the harm is of this policy? People
    0:22:12 will tell you, people have a gut feeling that the things they’re against are harmful. And so,
    0:22:16 I think they’re very happy to tell you as long as you don’t throw back in the face, as long as you
    0:22:24 don’t deny the kind of victims that they see. Okay, so I’m a hardcore liberal and probably most of my
    0:22:29 audience is liberal, too. Maybe I have two or three conservatives listening to this podcast. So,
    0:22:35 I gotta tell you, a lot of the book was just eye-opening to me that there is another argument to
    0:22:44 be said about abortion or vaccination or guns. So, can you just quickly explain to us, what’s the
    0:22:53 other side of you guy? What harm do they see with too much abortion or vaccination or gun control?
    0:23:02 Yeah, good question. And I want to preface this with this idea of, look, there are like statistical
    0:23:09 truths of who or what is more likely to be harmed in some situations. And so, I think vaccination,
    0:23:15 you know, as a scientist, I think vaccination, it’s a good. It’s a clear good. I’m a scientist.
    0:23:22 There’s lots of evidence to support that. But I think that statistics don’t always resonate.
    0:23:29 In our minds, and in fact, they seldom do. And what does resonate are kind of stories about harm.
    0:23:34 And so, even if we are all concerned about protecting the vulnerable from harm, especially kids,
    0:23:42 that you can have powerful stories, visions of what’s harmful that contradict any kind of
    0:23:47 statistics. So, let’s say your kid gets a vaccine and falls terribly ill, that’s going to be a
    0:23:54 personal experience that overwhelms how many scientists tell you that vaccines are okay.
    0:23:59 Or if you hear a story of a friend, I think guns are the same way, right? If you have experience
    0:24:04 and you’ve used a gun to defend yourself, that’s really powerful. And guns is also an interesting
    0:24:09 case because we could argue about what’s most relevant to the gun debate. If you’re like,
    0:24:14 look, the real problem is his mental illness, or it’s not like taking care of your gun or putting
    0:24:18 them in safes, then we shouldn’t be worried about how many guns are there. We should be worried
    0:24:23 about responsible gun ownership. And if someone comes to your family, if the zombie apocalypse
    0:24:28 comes, you want to have a handgun. And so, you see those threats and you see guns as a way of
    0:24:33 protecting yourself against those threats. So, it just always comes down to this kind of this
    0:24:41 worldview about what best protects us and our family. Would you say that it’s accurate that
    0:24:49 conservatives and liberals would almost completely agree on the desirability of protecting kids?
    0:24:55 Yes. I think we agree on the desirability of protecting most people. We just make different
    0:25:02 assumptions about what protects them. So, a liberal would make the argument that vaccination
    0:25:07 protects kids, and a conservative might make the argument that vaccination is going to cause
    0:25:14 autism. So, they’re both trying to protect kids. That’s exactly right. Wow. But let me ask you,
    0:25:20 Kurt, is there a point too far? I understand seeing the other sides, but are you telling me
    0:25:27 I’m supposed to see the other side for Hitler and Putin and Musk and Trump? I mean, RFK says,
    0:25:31 don’t get vaccinated. Is there a point where you just say, I don’t think so?
    0:25:39 I think there is a point. There is a point where you say this is a step too far. But I do want to
    0:25:46 separate the morality and humanity of everyday people from maybe political elites. So, this book
    0:25:51 is not written as like being an apologist for Putin. In fact, in one chapter, I say like,
    0:25:57 Putin thinks he’s a victim, and obviously he’s not. That idea is crazy. But I do think that many
    0:26:03 people in America have so many kind of different assumptions about who’s vulnerable to harm from
    0:26:08 social media, from cable news. And I think most people left or right just want to protect their
    0:26:14 family and want to have a better world to live in. And maybe some folks make assumptions or
    0:26:19 misunderstand the science. Questions of vaccination are probably more complex than most people realize,
    0:26:26 even if they’re uniformly, I think, a good thing for society. And so, I think we should just
    0:26:34 see the humanity on the other side, even if we want to argue against them. But that understanding
    0:26:39 of humanity doesn’t have to extend to Elon Musk if you don’t want it. This is about reconnecting
    0:26:43 with your friends and family and coworkers. And if people don’t want to have a reasoned conversation
    0:26:50 with Kanye or Elon or Donald Trump, I think that’s okay. This is about healing our kind of
    0:26:56 everyday fractures. Although, I do want to say there are people who think that you can extend
    0:27:02 the bridge even further. So, Daryl Davis is a black blues musician. Talk about him in the book.
    0:27:07 He devotes his life to befriending KKK members and getting them to hang up their robes. So,
    0:27:13 should we require a black man to talk to a KKK member? No. But the fact that he did it,
    0:27:19 I think, makes society better because he deradicalizes them and brings them towards the middle. So,
    0:27:24 those conversations are good. But I think a very subtle and important point is that
    0:27:32 where do you draw the line between communication and understanding and empathy and vulnerability
    0:27:38 and crossover into persuasion? Because once you cross into persuasion,
    0:27:45 it changes the CIV, right? Right. And so, in general, when you have these conversations,
    0:27:49 for them to go, “Well, you should be trying to understand and not win.” Because if you try to
    0:27:55 win, say you’ve already lost. But you can persuade someone through understanding, which I think is
    0:28:00 actually the only way to do it. Because if I come at you and I say, “Look, your positions are wrong.
    0:28:05 I heard some statistics on Fox News and here’s how, like, you’re following the wrong party
    0:28:09 and you’re a sheep and let me tell you the right statistics,” that’s not going to persuade. That’s
    0:28:13 going to send you in the other direction, right? You’re going to get angry. You’re an idiot. Like,
    0:28:17 you don’t know the right facts. And this is why facts don’t work to persuade because people have
    0:28:23 different facts. But if instead I say, “Look, here’s why I believe what I believe. It’s because of how
    0:28:28 I was raised. This really formative thing happened to me as a child. I felt very vulnerable and I
    0:28:34 got assaulted by a migrant or like I used a gun to defend my right. These positions on the right,
    0:28:40 I think you’ll think, “Oh, okay. Like, I see where you’re coming from and now you can generalize my
    0:28:45 own stories and feelings of harm maybe to other folks on the side. And that could be persuasion,
    0:28:49 but not because I’m trying to persuade. Because I’m trying to just show you who I am.”
    0:28:59 But isn’t there an inherent flaw in using stories this way? Because stories are not necessarily
    0:29:05 statistically or scientifically valid, right? You could say, “Yeah, my uncle smokes cigarettes
    0:29:12 every day for 70 years. He never got lung cancer. So cigarettes, according to my story, are safe.”
    0:29:17 Yeah. No, that’s a good point. And I teach my students in psychology and science that
    0:29:26 stories, just anecdotes, are not data. And the point is very apt. But our minds do not
    0:29:33 work well around statistics. And they should work better. And I teach my students to think about
    0:29:39 statistics, right? But in a political conversation, it doesn’t work. I wish that it worked. Then we
    0:29:44 could agree on like a common set of statistics or facts, but we don’t. Because each side has
    0:29:51 statistics and they disagree about which statistics are most relevant. So there’s a statistic that
    0:29:57 somewhere between 100,000 and 1.2 million times every year, guns are used in self-defense.
    0:30:05 And there’s a broader set of statistics, even more times in America each year. Guns harm people,
    0:30:09 not in self-defense. But I could say, look, as a conservative, like those other statistics,
    0:30:13 they’re not relevant because they’re not using guns correctly. They’re not well-trained. It’s not
    0:30:18 the right kind of guns. And there’s always a way to, I think of like Neo and the Matrix,
    0:30:22 you dodge around which facts are real. And so at the end of the day, if you want to understand
    0:30:27 someone, you need to put statistics aside, at least at first, at first connect with someone
    0:30:33 as a person, and then you can talk about statistics. So do you basically tell your students that
    0:30:40 stories are very powerful way to communicate and persuade, but you should also be understanding
    0:30:50 that when you run the side of the recipient of the story, you have to ask, is this valid in general?
    0:30:57 I think people already do that. I think if I tell you a story, as I have, so here’s how a gun
    0:31:03 writes out of a kit, why they would be pro-gun because of they used a handgun to defend themselves,
    0:31:09 or your kid got sick and you thought it was because of the vaccine. That’s a story you would
    0:31:14 spontaneously say, that’s not valid. That’s not a right story. That’s not generalizable. People
    0:31:18 already do that. And so I think the step we’re missing is to say, wow, that must have been hard.
    0:31:24 Thanks for sharing that. I can understand where you’re coming from. And then you can talk about
    0:31:29 some broader statistics. I think once you’ve shared your own story, so the person knows where
    0:31:34 you’re coming from. And there’s lots of programs actually to bring lawmakers together across the
    0:31:41 country. And those programs, they allow storytelling initially, and then afterwards, they have lawmakers
    0:31:46 think about statistics and policies and affecting the most good. I’m kind of narrow range of issues
    0:31:52 typically, but statistics are still part of it, but they don’t happen first, if that makes sense.
    0:32:00 In Silicon Valley, one of the most common stories is that you don’t need a college education because
    0:32:06 Bill Gates, Steve Jobs, and Mark Zuckerberg don’t have an undergraduate college degree,
    0:32:14 so they don’t need it. You don’t need it. Drop out of college. And that is statistically a very,
    0:32:20 very misleading story, right? Right. I think about in terms of the stock market too, right?
    0:32:26 Yeah. Sometimes there’s big crashes, but statistically speaking, it just makes sense
    0:32:32 to invest your money in a stock market because it goes up. But morality is not, it’s not like
    0:32:39 other facts. It’s not like other statistics. If you have a deep moral conviction and I say,
    0:32:43 “Hey, there’s a statistic out there,” and it suggests that your moral conviction is wrong,
    0:32:47 it’s not that you’re not going to be like, “Oh, you know what? You’re right. I guess I’ll just
    0:32:52 give up my view,” because that’s not how we’re built, right? Our moral convictions, they tie
    0:32:56 communities together. They make us feel like we’re good people. And so maybe you can have
    0:33:00 moral change over time and people do. People shift left to right or right to left. But like,
    0:33:05 it’s not the same kind of thing of what’s the most reliable car you can buy. It’s not the same
    0:33:09 kind of thing as what should you believe about abortion. Okay, so now I’m kind of reversing
    0:33:16 my direction on stories. Can you tell us how to optimize the use of stories? So let’s say I’m
    0:33:23 sold. I’ve seen the light. I love stories versus facts. So how do I use stories most effectively?
    0:33:28 Before we get there, I think one thing that’s useful to note is that political operatives,
    0:33:32 the people that I’m saying you don’t need to have quite as much empathy for as everyday people,
    0:33:37 they understand the power of storytelling and fears and harms. These are the things that motivate
    0:33:42 the base that get out donations, that get out the vote. These people are out there,
    0:33:47 they’re coming for you, they’re coming for America. So I think stories do work.
    0:33:52 And the other side uses them, whether you’re on the left or the right, the other side is always
    0:33:58 using them to almost for evil to drive division, especially during elections. And so I think it’s
    0:34:05 useful for us to know that they work. And I think even drawing from those kind of like the success
    0:34:11 of fear and threat, the stories that work best for bridging divides are, as we mentioned a
    0:34:17 little bit earlier, stories that kind of reveal your vulnerability and reveal that you’re a good
    0:34:24 person. If I tell you the story and I talk about my family. And so here’s a story of like why I
    0:34:31 want to bridge divides and see the humanity in the other side. And even though I like hang out
    0:34:38 mostly with progressives, I have family in Nebraska and they very clearly love me and they
    0:34:43 love me as a kid. I was a stepchild. I was a foreigner. I came down when I was like seven and
    0:34:49 10. And they opened their arms to me and accepted me as part of the family, despite these facts.
    0:34:56 And even as I got older and I realized I disagreed on issues, I couldn’t write them off and say that
    0:35:02 they’re just, you know, stupid or evil because I know that’s not true. And so it’s my personal
    0:35:08 experience of like feeling loved and having them kind of sacrifice for me, drive across the country
    0:35:15 to see me get married. These are the things that make me feel connected. And so my own story for
    0:35:18 why I’m a pluralist and why I think we should bridge divides is like grounded in my personal
    0:35:23 experience and my feelings of love and openness. So I think those are the stories that are optimized
    0:35:30 in a sense, like bearing yourself and showing who you are personally up next on remarkable people.
    0:35:34 And so I think we’re exhausted about fighting about what the best way to do it is and we’re
    0:35:39 exhausted about the kind of loudest voices on social media and on cable news. Even though I
    0:35:44 think we’re kind of like there’s like terrible addiction to kind of social media and cable news
    0:35:50 like we would be happier if we put it aside for a little bit, took some time, rested, slept and
    0:36:00 connected with people on a human basis. And that might make us feel less exhausted.
    0:36:09 Thank you to all our regular podcast listeners. It’s our pleasure and honor to make the show for
    0:36:15 you. If you find our show valuable, please do us a favor and subscribe, rate and review it.
    0:36:20 Even better, forward it to a friend, a big mahalo to you for doing this.
    0:36:25 Welcome back to remarkable people with Guy Kawasaki.
    0:36:30 You brought it up so I gotta ask, did you ever get baptized?
    0:36:39 I never got baptized, despite as the story in the book goes, in a Sunday school in Nebraska
    0:36:45 and the lessons on baptism. And I was like a seven-year-old or 10-year-old or something sitting
    0:36:49 in the basement. And the teacher says, can anyone tell me what happens to people who aren’t baptized?
    0:36:55 I’m the only kid obviously who’s not baptized. And some kids put it in his hand and the teacher says,
    0:37:03 yes. And the kid says, they go to hell. And that’s what everyone believed. But I felt like it was
    0:37:09 a bit of a setup, like you’re just like telling me I’m going to hell. And I was a little offended
    0:37:14 initially. But then I took some time. I was like hot on it for a little bit. But I took some time
    0:37:20 to think about it. I went away a little bit. And I realized kind of what harms do they see? Well,
    0:37:26 they see me going to hell. And they love me. And they don’t want me burning in a pit of fire for
    0:37:33 eternity. That’s dad. That’s a harm. And now that I see this concern, which is a little offensive,
    0:37:38 actually as a way of trying to protect me and reach out to me. And so I see it in a new light.
    0:37:42 And I’m still not baptized. I don’t think I’m going to hell. But I do appreciate their concern
    0:37:45 for me, even if I disagree with their assumptions about the world.
    0:37:55 I got to tell you, I love that story. I was baptized. I was probably 40 years old or something.
    0:38:03 It’s never too late. I got baptized at 40. I took up hockey at 44. I took up surfing at 60.
    0:38:08 You, Kurt, take your time. You got a lot of times. There you go. I’ve already had a couple
    0:38:15 concussions. So I don’t know about hockey, but definitely surfing. You put together two words
    0:38:23 that I have never seen put together in my life. And I want you to explain the concept of moral
    0:38:30 humility. What do those two words have to do with each other? So there has been a big
    0:38:37 trend, a movement towards intellectual humility, which is this idea of maybe I don’t know how the
    0:38:44 world works. And so you can make people feel intellectually humble very easily if I say,
    0:38:48 imagine a helicopter. You know how it works. And you’re like, yeah, I got it. There’s like
    0:38:53 two rotors. It’s cool. And then I say, could you please draw out a helicopter in sufficient
    0:38:58 detail that you could like explain how it works? And then you like get your pen and paper and you
    0:39:02 start drawing the helicopter and you’re like, I don’t know. I have no idea. That creates some
    0:39:08 humility or even like how does the toilet work, whatever that creates humility because you realize
    0:39:13 intellectually, you don’t know everything that you thought you knew. Moral humility is that
    0:39:20 understanding about a moral issue. And it’s harder one, I think, but I think you can still have it.
    0:39:25 And I think it’s still important if you acknowledge that like, well, maybe there’s someone on the other
    0:39:34 side of an issue about guns or abortion or taxes, that maybe has a bit of knowledge or a bit of
    0:39:40 opinions that I might learn from that really changes the conversation, right? Because now they’re
    0:39:45 not evil. They just they think differently. And even if I don’t agree with it, like I could still
    0:39:50 learn a little bit from them. And every time I’ve had commerce, like I had an Uber ride with a
    0:39:55 Christian nationalist, I don’t agree with Christian nationalism. But at the end of this 20 minute
    0:40:00 conversation I had where I asked him a lot of questions, I connected, I invited, I validated.
    0:40:05 I learned a lot about his position and I still don’t agree with it. But I still learned about
    0:40:09 what he’s thinking about. And I appreciated that learning. So I think humility can help.
    0:40:16 Okay, Kurt, you opened another door here. Tell me, what did you learn from a Christian nationalist?
    0:40:21 I want to hear this. I want to be morally humble and learn this.
    0:40:27 So a Christian nationalist was an Uber driver. He had his own business. He has his family.
    0:40:31 And he was describing to me like what he thought about the state, what he thought about the church.
    0:40:40 And I was surprised in a sense how tolerant he actually was of other faiths. He thought that
    0:40:44 like Christianity should be the kind of national religion. It’s definitional in the idea of a
    0:40:48 Christian nationalist. But he’s like, you can be Muslim. Maybe it’s not as prominent as being
    0:40:54 Christian. And I didn’t realize that he would be supportive of that idea. And he also had like more
    0:40:59 nuanced beliefs on the economy than I thought. He’s like, oh, I’m kind of libertarian, but not in
    0:41:05 the following ways. And so I think I learned about the kind of economic and social complexity
    0:41:10 in this view that I didn’t appreciate. And that made me kind of reflect on like, well,
    0:41:15 what do I think of the connection between the state and the church? And there’s lots of tax
    0:41:20 breaks for churches. And do I think that’s reasonable? I’m not sure. But he’s advancing
    0:41:24 arguments for like why that’s meaningful to him and like the connection between the church and
    0:41:28 supporting his family. So just make me think of there’s nuance around these issues. And it didn’t
    0:41:34 change my core convictions. But it did make me realize that there’s unanswered questions you
    0:41:41 could have about these topics. And did you give them five stars and a tip? I did give them five
    0:41:46 stars. And here’s why. Here’s why. Okay. So we had a 20 minute conversation by Christian National.
    0:41:52 I asked questions. I invited, I validated. And then as we’re driving up the ramp to the airport,
    0:41:55 we start talking about abortion. And abortion really comes down to your like assumptions
    0:41:59 about when life begins. And this may be a whole other conversation. But interestingly,
    0:42:03 evangelical Christians used to think that life started at birth, not at conception,
    0:42:08 which is like a whole turnaround in the 70s. But I digress. So we’re having conversation about
    0:42:14 abortion. He’s very pro life. And he starts saying that anyone who’s pro choice is kind
    0:42:19 of aligned with the Nazis. What? Yeah. And you mentioned it as well, it doesn’t take long for
    0:42:25 someone to connect a moral position they disagree with to the Nazis, right? It’s so easy in discourse
    0:42:31 today. It’s like natural, even because they’re like the paradigm of evil. And I teach a class
    0:42:35 on this, I teach undergrads to have reasonable conversations about contentious issues. And I
    0:42:42 say, Listen, we can’t have this conversation. If you’re going to compare half of America to the
    0:42:46 Nazis, it’s just not acceptable, right? That’s not fair. We can’t have a good faith conversation
    0:42:54 about about morality if this is going to happen. And he pauses. And he says, you know what, you’re
    0:43:00 right. I’m sorry. I’m going to take that back. All I was trying to say around giving us some grace
    0:43:06 here to explain his views, like the invitations and validation is that I’m worried that people
    0:43:11 who don’t respect the sanctity of fetal life will slide down a slippery slope is kind of my words,
    0:43:16 but like, you know, and other areas will neglect life. And that’s going to be bad for everyone in
    0:43:21 society, especially kids are the vulnerable. And the idea of a slippery slope is a reasonable
    0:43:28 philosophical argument that people on both sides have. And I could understand where that was coming
    0:43:35 from. And five stars, he took it back. He had some moral humility himself, because he’s like,
    0:43:39 that’s wrong. I’m sorry. But that only happened because I tried to understand and ask questions.
    0:43:44 And so I think it’s a good example of how these things can, if not change people, at least allow
    0:43:48 them to have respect for the other side in a way that probably didn’t happen for him.
    0:43:54 I’m a college professor, he probably thinks I’m like the indoctrinating enemy. But now I think
    0:44:01 there’s some respect that hopefully persists over time. And why didn’t this story make the book?
    0:44:07 It happened after the book was written. Oh, bummer. But I have a sub stack on it if folks
    0:44:12 want to see the sub stack. But it’s one of my favorite stories, because I took all the book
    0:44:18 and I put it into practice. Yeah, it encapsulates the whole book, right? Yeah, exactly, exactly.
    0:44:24 You never know what happens in an Uber. That’s another important lesson here. My last section
    0:44:33 of questions is I want to explore the concept of being mentally exhausted. So what causes mental
    0:44:41 exhaustion? Well, am I asking questions that are too easy? So in the book, I talk about this idea
    0:44:48 of the exhausted majority. When it comes to politics, and then most people are, like you say,
    0:44:53 mentally exhausted, we’re tired of the shouting, we’re tired of all the anger, we’re tired of the
    0:45:01 division. And even if it’s a gut reflex, we just want to live our lives. And we just want to feel
    0:45:08 like the country is working for us by us. And we disagree about that, obviously, about who’s the
    0:45:13 most effective leader. But most people want cheaper gas prices, want cheaper milk prices,
    0:45:18 want schools that flourish, want healthcare that helps them. And so I think we’re exhausted about
    0:45:22 fighting about what the best way to do it is and we’re exhausted about the kind of loudest voices
    0:45:27 on social media and on cable news. Even though I think we’re kind of like there’s like terrible
    0:45:32 addiction to kind of social media and cable news, like we would be happier if we put it aside for
    0:45:38 a little bit, took some time, rested, slept and connected with people on a human basis. And that
    0:45:44 might make us feel less exhausted. So your recommendation is put social media aside, don’t
    0:45:52 doom scroll and try to interact on a personal basis using CIV. Exactly. Exactly. And even if you use
    0:45:58 social media, we have some research on this, that if you unfollow the most divisive accounts,
    0:46:04 like that’s going to make you feel better. Just those like 10 people that are conflict
    0:46:09 entrepreneurs is a nice word from Amanda Ripley, that people are making money by making you angry.
    0:46:16 Put it aside and actually have conversations with your Uber driver, someone who bowls with you,
    0:46:20 the guy who like runs the whole landscaping operation around here. He’s certainly more
    0:46:26 conservative than I am. We talk about kids and we talk about how he’s doing, talk about like his house
    0:46:30 and he’s planting trees. There’s so many things that we’ve in common that’s not about politics.
    0:46:34 And then if we get to politics, we can like tiptoe around a little respectfully,
    0:46:38 but those in-person conversations are much better than screaming into platforms.
    0:46:43 You made the argument that you should unfollow the 10 most disruptive people.
    0:46:50 I could make the case you should unfollow the 10 people that you most agree with, right? Because
    0:46:58 put you outside the echo chamber. Yeah, I think that’s not a bad idea either. I think, again,
    0:47:02 you should be striving, maybe this is a mindset for life, right? You should be striving to learn
    0:47:07 in general. And if you’re just hearing anything that you already believe parroted back,
    0:47:12 it’s not a way to learn. But with social media, I mean, the algorithm is so fine-tuned to induce
    0:47:16 outrage. Like, I don’t even know if social media is the right place to learn. You can read reports
    0:47:20 by think tanks. I think that’s probably boring for most people. But I think if you’re going to use
    0:47:26 social media, follow like the US parks, cat memes, I don’t know, anything’s better than politics on
    0:47:31 social media. In fact, I’m going to study the shows that people who follow politics on social
    0:47:36 media and pay attention to virality metrics, like how many retweets, how many shares,
    0:47:40 they have symptoms of PTSD that are above clinical threshold often.
    0:47:47 Crazy. Like, that’s how bad it is to like politics and care about virality on social media. Don’t
    0:47:53 do it. The guy who just time traveled 100 years, he’s going to be saying, yeah, 100 years ago,
    0:47:59 we were worried about being killed. And now you’re worried about PTSD from reading posts on social
    0:48:06 media. True. Although, you know, 100, I don’t know how many 150 years ago, right, sale and witch
    0:48:11 trials, like all sorts of panic about witches. And they didn’t have social media, right? But they
    0:48:15 had the Bible and they had like preachers saying that like Satan’s coming for them and things are
    0:48:20 terrible. So they still had a kind of panic. It didn’t happen as fast as social media. But I think
    0:48:26 it’s still a kind of like deeply human thing to be terrified of threats and to band together and
    0:48:34 get outraged. Okay, this is my last question. And this last question may not go over well with your
    0:48:41 relatives in Nebraska, but let’s just pretend that you become the chairman of the Democratic
    0:48:47 National Committee. What would you do? I would tell stories of harm because I know that’s effective,
    0:48:57 I suppose. I mean, I think deep in my heart, I think that the best way to run America is how it
    0:49:03 was founded, which is as a pluralistic democracy. And it’s totally fair to have convictions. But I
    0:49:08 think some of the best bills that were passed are bipartisan bills, like overhauling the criminal
    0:49:15 justice system, to be kinder, to be less punitive, to be less racially biased, but also just give
    0:49:21 individuals a second chance, no matter what their race is. And so I would try, I think, to build
    0:49:26 broad-scale support. This is why I would never be elected, by the way, or chosen as the DNC
    0:49:32 chairman, because I’m not like motivating the base enough. But I think big social movements pass.
    0:49:40 Civil rights, women’s suffrage, right? Because there is bipartisan support. There’s understanding
    0:49:45 on both sides. There’s allies that see, same with gay rights. It’s like John McCain’s daughter
    0:49:50 is gay, and he could see the humanity in those folks, and then there’s this widespread support.
    0:49:55 I think for moral progress to happen, I think it needs to be a more united effort than what we’re
    0:50:04 seeing today. And as you said, and I misunderstood, quote, “Most conservatives generally want to protect
    0:50:11 black men, and most liberals generally want to protect the police.” And right? So we’re probably
    0:50:20 more similar than we are different, if we could just stop being outraged. Exactly. We are so
    0:50:26 similar. If you take a law book and you flip to a random page, we probably agree on 99.99 percent
    0:50:32 of those pages of law. And even when it comes to contentious issues, we generally do agree.
    0:50:36 What pushes us apart is our partisan filters and what the media tells us. So if we just go
    0:50:40 within ourselves and think about our own minds and our own concerns about harm and other people’s
    0:50:45 concerns about harm, it brings us a lot closer together. All right. Kirk, thank you so much.
    0:50:51 This has been such an interesting episode, and I learned a lot reading your book. I would love
    0:51:00 to see all your theories and concepts get into practice so that we do have a more civil CIV
    0:51:08 in-caps society. So thank you very much, Kurt. I appreciate this very much. And you are a remarkable
    0:51:15 person. So we will be in touch, okay? Sounds good and appreciated. All right. So I’m Guy Kawasaki.
    0:51:22 This has been the Remarkable People Podcast with the Remarkable Kurt Gray. And I hope you learned
    0:51:29 some very tactical and practical ways to bring society together. I certainly did. And remember
    0:51:34 his book is called Outraged, even though I think it should be called Harmless.
    0:51:41 But don’t worry about that because he had to get the book published. And if publishers
    0:51:48 want to call it outraged, so be it. And focus on the big issues, right? That’s right. Outrage cells.
    0:51:56 Outrage cells. All right. Thank you very much. Have a great week, everybody. Mahalo and Aloha.
    0:52:02 Thank you for my crew, Madison, Nismar, Shannon Hernandez, and Jeff C. That’s the
    0:52:08 Remarkable People team behind me, Kurt. And we’re all trying to help people be remarkable.
    0:52:15 This is Remarkable People.

    Step into the fascinating world of moral psychology with Kurt Gray, professor of psychology and neuroscience at UNC Chapel Hill, who explores the psychology of outrage and moral understanding. As director of the Deepest Beliefs Lab and the Center for the Science of Moral Understanding, Kurt unveils how we can bridge America’s deepest divides through his groundbreaking CIV approach – Connect, Invite, and Validate. His new book ‘Outrage’ challenges us to understand both sides of moral conflicts and find common ground in our shared humanity.

    Guy Kawasaki is on a mission to make you remarkable. His Remarkable People podcast features interviews with remarkable people such as Jane Goodall, Marc Benioff, Woz, Kristi Yamaguchi, and Bob Cialdini. Every episode will make you more remarkable.

    With his decades of experience in Silicon Valley as a Venture Capitalist and advisor to the top entrepreneurs in the world, Guy’s questions come from a place of curiosity and passion for technology, start-ups, entrepreneurship, and marketing. If you love society and culture, documentaries, and business podcasts, take a second to follow Remarkable People.

    Listeners of the Remarkable People podcast will learn from some of the most successful people in the world with practical tips and inspiring stories that will help you be more remarkable.

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  • Sandra Matz: The Personal Data Privacy Crisis

    Sandra Matz: The Personal Data Privacy Crisis

    AI transcript
    0:00:02 (upbeat music)
    0:00:10 – Hi, I’m Guy Kawasaki.
    0:00:12 This is the Remarkable People Podcast.
    0:00:14 And as you well know,
    0:00:16 we’re on a mission to make you remarkable.
    0:00:20 And the way we do that is we bring you remarkable guests
    0:00:23 who explain why they’re remarkable
    0:00:25 and how they’re remarkable and their remarkable work.
    0:00:28 And today’s special guest is Sandra Mott.
    0:00:31 – She’s a professor at the Columbia Business School
    0:00:35 and she’s gonna talk to us about psychological targeting
    0:00:37 and changing mindset.
    0:00:39 Congratulations.
    0:00:43 Shipping a book is a big, big accomplishment.
    0:00:45 Trust me, I know this firsthand, so.
    0:00:48 – I know, it feels good when it’s out.
    0:00:50 Even though I had a great time writing it.
    0:00:52 So I think I probably enjoyed it a lot more
    0:00:55 than what I was told by other authors.
    0:00:57 So I already enjoyed the process.
    0:00:59 – I have written 17 books
    0:01:02 and I have told people 16 times
    0:01:04 that I am not writing another book.
    0:01:06 – Good luck with that one.
    0:01:07 – Yeah, exactly.
    0:01:08 – I’m just waiting for,
    0:01:11 what would he be placing the order for number 18,
    0:01:12 if that’s the case?
    0:01:19 – Alrighty, so first of all, if you don’t mind,
    0:01:21 let me just tell you something kind of off the wall
    0:01:25 that your story about how you met your husband
    0:01:27 at that speaking event,
    0:01:29 that was the closest thing to porn
    0:01:32 in a business book that I have ever read.
    0:01:35 – And I spared you the details.
    0:01:37 It’s actually a lot more to the story.
    0:01:39 It’s a good one.
    0:01:40 – I was reading that.
    0:01:44 I said like, man, where is this going?
    0:01:47 Like, is she gonna have this great lesson about how to,
    0:01:50 you know, tell men to stick it and get out of my face?
    0:01:52 And then I keep reading and it says,
    0:01:56 oh, and the night went very, very well.
    0:01:57 – What?
    0:02:02 – It’s such a fun anecdote in my life,
    0:02:02 how I met him.
    0:02:05 So it was just like conference.
    0:02:07 He was late for the people who have read the book
    0:02:08 and I was like, what a jerk.
    0:02:10 And I kind of had written him off.
    0:02:12 And then as the night progressed
    0:02:15 and I learned more about him by spying on him
    0:02:18 as part of, in his place.
    0:02:20 I was like, interesting guy.
    0:02:22 I think I’m gonna give him a second chance.
    0:02:23 And we’re married.
    0:02:25 We have a kid now who’s one year old.
    0:02:27 So it all worked out.
    0:02:30 – And is he still meticulously neat?
    0:02:32 Or, you know, was that just a demo?
    0:02:34 And this is the real thing now.
    0:02:35 – No, no, no.
    0:02:36 So yeah, as part of the story,
    0:02:39 it’s like, one of the first things I learned about him
    0:02:41 is that I think he’s borderline OCD
    0:02:43 ’cause he just sorts everything.
    0:02:47 It’s like the person who sorts his socks by color.
    0:02:48 We just moved apartments,
    0:02:50 which is with a one year old,
    0:02:52 not the most fun thing to do in the world.
    0:02:54 And they were like boxes everywhere.
    0:02:56 You could barely walk around the apartment
    0:02:58 and I just opened one of the drawers
    0:03:01 and he had put the cutlery, like perfection.
    0:03:05 I’m like, there’s a hundred thousand boxes in this place.
    0:03:08 I can barely find anything for the baby,
    0:03:11 but I’m really glad that you spent at least an hour
    0:03:14 perfecting the organization of the cutlery.
    0:03:16 So it’s, he’s still.
    0:03:18 – I hope your new place has a dishwasher
    0:03:22 so he can load the utensils in the tray.
    0:03:23 – Tell me about it.
    0:03:24 – That’s exactly what happens.
    0:03:27 Yeah, I’m not allowed to touch the dishwasher anymore
    0:03:28 ’cause I don’t do it perfectly.
    0:03:30 So you’re spot on, yeah.
    0:03:33 (laughing)
    0:03:35 – So you listeners out there, basically,
    0:03:39 we have an expert in psychological targeting
    0:03:43 and now she’s explaining how she had absolutely no targeting
    0:03:46 in meeting her future husband, right?
    0:03:48 – I think I nailed it from the beginning
    0:03:51 and that his place, I looked at his,
    0:03:54 him being put together and it gave me a pretty good
    0:03:56 understanding I think of who he was.
    0:03:58 I feel like I know what I signed up for.
    0:04:02 – Okay, so this is proof that her theories work.
    0:04:06 So I’ve already, you know, said this word,
    0:04:08 psychological targeting twice.
    0:04:10 So I would really like,
    0:04:13 this is an easy question to start you off,
    0:04:16 not that we got past the porn part of this podcast,
    0:04:21 which is from a psychological targeting perspective.
    0:04:25 What’s your analysis of the 2024 election?
    0:04:26 – It’s a, I mean, interesting one.
    0:04:30 So psychological targeting typically looks at individuals.
    0:04:32 So it’s trying to see what can we learn
    0:04:34 about the psychological makeup of people,
    0:04:36 not by asking them questions,
    0:04:38 but really observing what they do, right?
    0:04:40 You can imagine in the analog world,
    0:04:43 I might look at how someone treats other people,
    0:04:46 whether they’re organized as my husband is.
    0:04:48 And I think you can learn a lot by making these observations.
    0:04:49 That’s true in the offline world.
    0:04:51 That’s also true in the online world.
    0:04:54 And I think if you just look at them,
    0:04:57 presidential candidates, the way that they talk,
    0:05:00 if Trump writes in all caps all the time
    0:05:04 and doesn’t necessarily give it a second thought
    0:05:06 before something comes out on Twitter,
    0:05:08 I think that is an interesting glimpse
    0:05:11 into what might be going on behind the scenes.
    0:05:14 – And do you think that his campaign
    0:05:18 did like really great psychological targeting
    0:05:20 of the undecided in the middle?
    0:05:24 Or, you know, like from an academic perspective,
    0:05:29 as a case study, how would you say his campaign was run?
    0:05:31 – I talk a lot about psychological targeting
    0:05:33 ’cause for me, it’s interesting to understand
    0:05:35 how the data translates into something
    0:05:37 that we can make sense of as humans, right?
    0:05:41 So if I get access to all of your social media data,
    0:05:43 an algorithm might be very good at understanding
    0:05:45 your preferences and motivations
    0:05:46 and then play into these preferences.
    0:05:48 But I, as a user, as a human,
    0:05:51 can’t really make sense of a million data points
    0:05:52 at the same time.
    0:05:54 If I translate it into something
    0:05:55 that tells me whether you’re more impulsive
    0:05:58 or more neurotic or more open-minded,
    0:06:00 that just kind of goes a long way in saying,
    0:06:03 okay, now I know which topics you might be interested in
    0:06:04 in the context of an election
    0:06:08 or how I might talk to you in a way that most resonates.
    0:06:11 Now, politics is an interesting case, right?
    0:06:15 ‘Cause ideally a politician would go knock on every door,
    0:06:16 have a conversation with you
    0:06:18 about the stuff that you care about,
    0:06:19 and obviously they don’t have the time.
    0:06:23 So there’s, I think, a lot of potential
    0:06:26 of using some of these tools to make politics better,
    0:06:29 but obviously, I think the way that some of these tools
    0:06:32 were introduced in the context of the 2016 election,
    0:06:35 which really shows that the more dark side,
    0:06:37 and I don’t know if they’re using
    0:06:39 any of these tools on the campaign trail.
    0:06:41 I think there are many ways in which you can use data
    0:06:46 to drive engagement that’s not necessarily based
    0:06:49 on predictions of your psychology at the individual level,
    0:06:52 but certainly this idea that the more we know about people
    0:06:54 and their motivations, their preferences,
    0:06:57 dreams, fears, hopes, aspirations, you name it,
    0:07:00 the easier it is for us to manipulate them.
    0:07:03 – Well, in politics, as well as marketing,
    0:07:06 which you bring up in your book,
    0:07:09 I kind of got the feeling that what you’re saying is that,
    0:07:13 you know, you psychologically target people
    0:07:18 with different messages, but you could have the same product.
    0:07:21 So in a sense, you’re saying that, you know,
    0:07:22 yes, with the same product,
    0:07:26 whether it’s Donald Trump or an iPhone or, you know,
    0:07:30 whatever, a Prius, you can change your messaging
    0:07:34 to make diverse people buy the product.
    0:07:36 So did I get that right?
    0:07:39 Or am I like imagining something
    0:07:42 that’s kind of nefarious, actually?
    0:07:44 – I think it depends on how you think about this, right?
    0:07:48 ‘Cause the fact that we talk to people
    0:07:49 in different ways all the time.
    0:07:52 So imagine a kid who wants the same thing.
    0:07:54 The kid wants candy.
    0:07:58 The kid knows exactly that they should talk to their mom
    0:08:01 in one way and that they should talk to their dad
    0:08:02 in a different way, right?
    0:08:03 So the goal is exactly the same.
    0:08:05 The goal is to get the candy,
    0:08:08 but we’re so good as humans,
    0:08:10 making sense of who’s on the other side,
    0:08:12 understanding what makes them tick,
    0:08:14 how do I best persuade them to buy something?
    0:08:17 And the same is true, I think, in politics and marketing.
    0:08:19 The more that we understand where someone is coming from
    0:08:21 and where they want to be in the end,
    0:08:23 the easier it is for us to sell a product, right?
    0:08:28 So products have the benefit that it’s not just what you buy,
    0:08:28 right?
    0:08:30 A lot of the times we buy products
    0:08:32 because they have like this meaning to us.
    0:08:33 They help us express ourselves.
    0:08:35 They serve a certain purpose.
    0:08:38 And if we can figure out what’s the purpose of a camera
    0:08:40 for a certain person, what’s the purpose of the iPhone
    0:08:43 for a camera, why do people care about immigration?
    0:08:46 A certain take, why do people care about climate change?
    0:08:48 Is it because they’re concerned about their kids?
    0:08:51 Is it because they’re concerned about their property?
    0:08:54 Then I think we just have a much easier way
    0:08:55 of tapping into some of these needs.
    0:08:57 And whether that’s offline,
    0:09:00 when we, again, talk to our three-year-old,
    0:09:02 not in the same way that we talk to our boss and our spouse,
    0:09:05 or whether that’s market is doing that at scale,
    0:09:07 it’s really the more you understand about someone,
    0:09:11 the more power you have over their behavior.
    0:09:14 – So are you saying that at an extreme,
    0:09:16 you could say to like a Republican person,
    0:09:20 you know, the reason why we have to control the border
    0:09:22 is because of physical security,
    0:09:25 where to a liberal, you might say, you know,
    0:09:27 there’s a different message,
    0:09:32 but in both cases, you want to secure the border,
    0:09:37 one for maybe job displacement, another for security.
    0:09:38 I mean, it would be different,
    0:09:41 but the same product in a sense.
    0:09:42 – Yeah, or the same, yeah.
    0:09:44 So a hundred percent, there’s all of this research,
    0:09:46 and this is actually is not my own.
    0:09:48 It’s very similar to psychological targeting.
    0:09:52 And in that space, it’s usually called moral reframing
    0:09:53 or moral framing.
    0:09:56 So the idea that once I understand
    0:09:58 your set of moral values, right?
    0:10:00 So there’s a framework that kind of describes
    0:10:02 these five moral values.
    0:10:04 The way that we think about what’s right or wrong
    0:10:06 in the world, that’s how I think about it myself.
    0:10:10 And some of it is loyalty, fairness, care, purity,
    0:10:11 and authority.
    0:10:14 And what we know is that across the political spectrum,
    0:10:15 so from liberal to conservative,
    0:10:18 people place different emphasis on some of these values.
    0:10:20 So if you take a liberal,
    0:10:22 typically they care about care and fairness.
    0:10:24 So if you make an argument about immigration again,
    0:10:27 that’s, or climate change does matter,
    0:10:29 that’s tapping into these values,
    0:10:32 you’re more likely to convince someone who’s liberal.
    0:10:34 Now, if you take something like loyalty,
    0:10:35 authority, or purity, you’re more likely
    0:10:37 to convince someone who’s more conservative.
    0:10:39 And for me, the interesting part is that,
    0:10:42 as humans, we’re so stuck with our own perspective, right?
    0:10:46 If I as a liberal try to convince a conservative
    0:10:48 that immigration might be a good thing,
    0:10:51 I typically make that argument from my own perspective.
    0:10:55 So I might be very much focused on fairness and care,
    0:10:56 and it’s just not resonating with the other side,
    0:10:58 ’cause it’s not what they’re coming from.
    0:11:00 And algorithms, because they don’t have an incentive,
    0:11:03 they don’t necessarily have their own perspective
    0:11:05 on the world that’s driven by ideology.
    0:11:07 It’s oftentimes much easier for them to say,
    0:11:11 I try and figure out what makes you care about the world,
    0:11:13 what makes you think about what’s right or wrong in the world.
    0:11:16 And now I’m gonna craft that argument along those lines.
    0:11:19 And what’s interesting for me is that,
    0:11:20 depending on how you construe it,
    0:11:22 it can either be seen as manipulation.
    0:11:24 So I’m trying to convince you of something
    0:11:25 that you might not otherwise believe,
    0:11:27 but it could also be construed as,
    0:11:29 I’m really trying to understand
    0:11:30 how you think about the world.
    0:11:32 But I’m really trying to understand and engage with you
    0:11:35 in a way that doesn’t necessarily come from my point of view,
    0:11:37 but is trying to take your point of view.
    0:11:41 So it really has, for me, these two sides.
    0:11:46 – So I could say to a Republican is the reason why
    0:11:51 you wanna support the H1B visa program
    0:11:53 is because those immigrants have a history
    0:11:55 of creating large companies
    0:11:58 which will create more jobs for all of us,
    0:12:01 which is a very different pitch.
    0:12:03 – Yeah, and so in addition to the fact
    0:12:05 that we can just tap into people’s psychology,
    0:12:07 there’s also this research that I love.
    0:12:08 I think it’s mostly done,
    0:12:10 I think in the context of climate change,
    0:12:12 but it’s looking at what do people think
    0:12:14 the solutions to problems are,
    0:12:17 and how does that relate to what they believe in anyway?
    0:12:20 If I tell you, well, solving climate change
    0:12:23 means reducing government influence,
    0:12:25 it means reducing taxes.
    0:12:26 Then suddenly Republicans are like,
    0:12:28 “Oh my God, climate change is a big problem
    0:12:30 “because the solutions are very much aligned
    0:12:32 “with what I believe in anyway.”
    0:12:33 If you tell that to Democrats,
    0:12:35 they’re like, “Actually, it’s not such a big deal
    0:12:37 “’cause I don’t really believe in the solution.”
    0:12:41 So the way I think that we play with people’s psychology
    0:12:43 and how they think about the world
    0:12:45 and show up in the world just means
    0:12:47 that oftentimes it gives us a lot of power
    0:12:50 over how they think, feel, and behave.
    0:12:54 – Another point that I hope I interpreted correctly
    0:12:57 is like, you know, I’ve been trained so long
    0:12:58 to understand the difference
    0:13:01 between correlation and causation, right?
    0:13:05 So like, if you wear a black mock turtleneck,
    0:13:06 so did Steve Jobs.
    0:13:08 So you should wear a black mock turtleneck
    0:13:10 because you’ll be the next Steve Jobs.
    0:13:13 Well, didn’t quite work out that way for Elizabeth Holmes,
    0:13:16 but I think you take a different direction.
    0:13:17 I just want to verify this.
    0:13:21 So you don’t really discuss correlation versus causation.
    0:13:24 In a sense, what you’re saying is that
    0:13:29 there doesn’t need to be a causative relationship
    0:13:34 if there is a predictive relationship that you can harness.
    0:13:37 So I don’t know, if for some reason people,
    0:13:40 we noticed a lot of people with iPhones by German cars,
    0:13:41 well, that’s predictive.
    0:13:44 I don’t have to understand why that’s true.
    0:13:45 – Yeah, no, totally.
    0:13:48 And I’ll give you an example that I think is interesting.
    0:13:52 So one of the relationships that I still find fascinating
    0:13:54 that we observe in the data that I don’t think
    0:13:57 I would have intuited even as a psychologist
    0:13:59 is the use of first person pronouns,
    0:14:01 like people post on social media
    0:14:02 about what’s going on in their life.
    0:14:05 And I remember being at this conference,
    0:14:07 it’s like a room full of psychologists
    0:14:09 and this guy who was really like a leading figure,
    0:14:12 Jamie Panner Baker in the space of natural language processing,
    0:14:14 he comes up and he just asks the audience,
    0:14:17 what do you think the use of first person pronouns?
    0:14:21 So just using I, me, myself more often than other people,
    0:14:23 what do you think this is related to?
    0:14:25 And I remember all of us sitting at the table
    0:14:27 and we’re like, oh, it’s gotta be narcissism.
    0:14:30 If someone talks about themself constantly,
    0:14:33 that’s probably a sign that someone is a bit more narcissistic
    0:14:35 and self-centered than other people.
    0:14:38 Turns out that it’s actually a sign of emotional distress.
    0:14:40 So if you talk a lot about yourself,
    0:14:43 that makes it more likely that you suffer
    0:14:45 from something like depression, for example.
    0:14:49 And now taking a step back, it actually makes sense, right?
    0:14:50 If you think back to the last time
    0:14:53 that you felt blue or sad or down,
    0:14:54 you probably were not thinking about
    0:14:56 how to fix the Southern border
    0:14:58 or how to solve climate change.
    0:14:59 What you were thinking about is like,
    0:15:00 why am I feeling so bad?
    0:15:02 Am I ever gonna get better?
    0:15:03 What can I do to get better?
    0:15:05 And this inner monologue that we have with ourselves
    0:15:07 just creeps into the language that we use
    0:15:10 as we express ourselves on these social platforms.
    0:15:14 Now, the causal link is not entirely clear, right?
    0:15:16 It could be that I’m just using
    0:15:18 a lot more first person pronouns
    0:15:19 because I have this inner monologue.
    0:15:21 What you see in the language of people
    0:15:23 who are suffering from emotional distress
    0:15:25 is all of these physical symptoms.
    0:15:28 So just being sick, having body aches.
    0:15:30 And again, it’s not entirely clear
    0:15:32 if maybe you’re having a hard time mentally
    0:15:33 because you’re physically sick,
    0:15:35 but also maybe you’re physically sick
    0:15:37 ’cause you’re having like a hard time
    0:15:39 with the problems that you’re dealing with.
    0:15:43 So on some level, I don’t even care that much, right?
    0:15:45 If I’m just trying to understand and say,
    0:15:47 is there someone who might be suffering
    0:15:49 from something like depression
    0:15:50 who’s currently having a hard time
    0:15:52 regulating their emotions?
    0:15:54 I don’t necessarily care if it’s going from
    0:15:57 physical symptoms to mental health problems
    0:15:58 or the other way.
    0:16:01 What I care about is if I see these words popping up
    0:16:03 or if I see some of these topics popping up,
    0:16:06 that’s an increase in the likelihood
    0:16:08 that someone is actually having a hard time right now.
    0:16:11 Now, I think what is interesting is that
    0:16:13 the more causal these explanations get
    0:16:14 and these relationships get,
    0:16:17 oftentimes they’re a lot more stable.
    0:16:20 So it could be that if it’s like a causal mechanism,
    0:16:22 and first of all, it allows us to understand
    0:16:23 something about interventions,
    0:16:26 like how do we actually then help people get better?
    0:16:30 And they’re also oftentimes the ones that last for longer
    0:16:32 because it’s not something just the fluke and the data
    0:16:34 that maybe goes this direction or the other,
    0:16:36 but it’s something that is really driving it
    0:16:37 on a more fundamental level.
    0:16:39 So you’re absolutely right in that,
    0:16:41 oftentimes when we think of prediction,
    0:16:44 we don’t need to understand which direction it goes in.
    0:16:49 It’s still helpful to know if you think of interventions.
    0:16:51 – So at a very simplistic level,
    0:16:54 could you make the case to a pharmaceutical company?
    0:16:57 You know, look at a person’s social media
    0:16:59 and if the person is saying aye a lot,
    0:17:04 sell them some lorazeprame or some anti-anxiety drugs,
    0:17:08 is it that simple?
    0:17:10 – I personally probably not go to the pharma companies
    0:17:13 and make that proposition, but it is that simple.
    0:17:15 And again, one of the points that I make in the book
    0:17:17 that is super important to me
    0:17:20 is that those are all predictions with a lot of error, right?
    0:17:24 So it means that on average, if you use these words more,
    0:17:28 you’re more likely to suffer from emotional distress.
    0:17:30 That doesn’t mean that it’s terministic.
    0:17:32 There’s a lot of error at the individual level.
    0:17:36 So if I’m a pharma company and I wanna sell these products,
    0:17:38 yeah, on average, I might do better
    0:17:39 by targeting these people,
    0:17:42 but it still means that we’re not always going to get it right.
    0:17:44 And then on the other side, what is interesting for me
    0:17:46 is if you think about it,
    0:17:48 not from the perspective of a pharma company,
    0:17:50 but from the perspective of an individual,
    0:17:52 I think there’s ways in which we can acknowledge
    0:17:54 the fact that it’s not always perfect, right?
    0:17:56 You could have this early warning system
    0:17:58 for people who know, for example,
    0:18:00 that they have a history of mental health conditions
    0:18:02 and they know that it’s really difficult
    0:18:05 once they’re at this valley of depression to get out.
    0:18:07 So they could have something on their phone
    0:18:08 that just tracks their GPS record,
    0:18:11 sees that they’re not leaving the house as much anymore,
    0:18:15 less physical activity, more user first person pronouns.
    0:18:17 And it almost has this early warning system.
    0:18:20 It just puts a flag out and says, “It might be nothing.
    0:18:22 It’s not a diagnostic tool. There’s a lot of error,
    0:18:25 but we see that there’s some deviations from your baseline.
    0:18:26 Why don’t you look into this?”
    0:18:29 And for me, those are the interesting use cases
    0:18:31 where we involve the individual,
    0:18:33 acknowledging that there’s mistakes that we make
    0:18:35 and the predictions,
    0:18:36 but we’re using it to just help them
    0:18:39 accomplish some of the goals that they have for themselves.
    0:18:48 So speaking of interesting use cases,
    0:18:50 would you do the audience a favor
    0:18:53 and explain how you help the hotel chain
    0:18:57 optimize their offering? ‘Cause I love that example.
    0:19:00 – It was one of the first projects
    0:19:01 and industry collaborations that we did
    0:19:04 when I was still doing my PhD.
    0:19:06 And there’s many reasons for why I actually liked the example.
    0:19:09 But the idea was that we were approached by Hilton
    0:19:11 and we worked with a PR company.
    0:19:13 And the idea of Hilton was,
    0:19:16 can we use something like psychological targeting?
    0:19:19 So really tapping into people’s psychological motivations,
    0:19:21 what makes them tick,
    0:19:23 what makes them care about vacations and so on
    0:19:25 to make their campaigns more engaging
    0:19:28 and then also sell vacations
    0:19:30 that really resonated with people.
    0:19:33 And what I like about the example is that Hilton didn’t say,
    0:19:36 well, we’re just gonna run a campaign on Facebook and Google
    0:19:39 where we just passively predict people’s psychology
    0:19:42 and then we try to sell them more stuff.
    0:19:46 They turned it into this mutual two-way conversation
    0:19:47 where they said, hey,
    0:19:49 we wanna understand your traveler profile.
    0:19:51 And for us to be able to do that,
    0:19:53 if you connect with your social media profile,
    0:19:55 we can run it through this algorithm
    0:19:57 that actually we don’t control.
    0:19:59 It’s the University of Cambridge is doing it.
    0:20:01 We don’t even get to see the data.
    0:20:05 But what we can do is we can spit out this traveler profile
    0:20:07 and then make recommendations
    0:20:09 that really tap into that profile.
    0:20:11 So it was this campaign.
    0:20:15 And you can imagine that doing that increased like engagement.
    0:20:18 People were excited about sharing it with friends.
    0:20:21 It was essentially good for the business bottom line.
    0:20:24 But it also gave, I think, users the feeling
    0:20:27 that it’s a genuine value proposition.
    0:20:30 So there was a company that operated first of all
    0:20:32 with consent ’cause it was all,
    0:20:35 it’s up to you whether you wanna share the data or not.
    0:20:37 Here’s like, how does this works behind the scenes?
    0:20:39 Here’s what we give you in return.
    0:20:42 So it was very transparent with the entire process.
    0:20:44 And it was also transparent in terms of
    0:20:46 here’s what we have to offer, right?
    0:20:48 It’s by understanding your traveler profile.
    0:20:50 We can just make your vacation a lot better.
    0:20:53 So that’s one of the reasons why I like this example a lot.
    0:20:59 – Now, just as a point of clarification,
    0:21:01 you said the University of Cambridge, right?
    0:21:02 – Yeah.
    0:21:05 – Which has nothing to do with Facebook
    0:21:08 and Cambridge associates, right?
    0:21:10 – With Cambridge Analytica has nothing to do at all.
    0:21:13 It was funny ’cause I get mixed up with them all the time.
    0:21:16 Not surprising ’cause I got my PhD there on the same topic.
    0:21:20 And there was like, I mean, the idea originated there, right?
    0:21:23 The idea that we could take someone’s social media profile,
    0:21:25 predict things about their psychology,
    0:21:29 originated at Cambridge and that’s where it was taken from.
    0:21:31 But we were involved and for me,
    0:21:33 it’s almost like a point of pride
    0:21:36 and like a point that made me think about the ethics a lot
    0:21:39 is we helped the journalists break the story.
    0:21:41 So when the journalists in, first in Switzerland,
    0:21:43 were working on trying to see what happened
    0:21:45 behind the scenes of Cambridge Analytica,
    0:21:47 we just helped them understand the science.
    0:21:49 How can you get all of the data?
    0:21:51 How do you translate it into profile?
    0:21:55 So yeah, not related to Cambridge Analytica in any way,
    0:21:57 other than trying to take them down.
    0:21:59 – Okay, so I misspoke.
    0:22:02 I said Cambridge associates, not Analytica.
    0:22:04 So if you were for Cambridge associates,
    0:22:07 if there’s such a thing out there, I’d correct myself.
    0:22:08 (laughing)
    0:22:09 – I’m not sure.
    0:22:13 – So listen, in the United States,
    0:22:15 this is a very broad question,
    0:22:19 but in the United States, who owns my data?
    0:22:21 Me or the companies?
    0:22:23 – Well, as you might have imagined,
    0:22:24 it’s typically not you.
    0:22:27 So the US is an interesting case
    0:22:29 ’cause it very much depends on the state that you live in.
    0:22:32 So Europe, I would say has the strictest
    0:22:34 data protection regulations.
    0:22:37 So they very much try to operate on these principles
    0:22:39 of transparency and control
    0:22:42 and giving you at least the ability to request your own data
    0:22:44 to delete it and so on and so forth.
    0:22:46 In the US, California is the closest.
    0:22:48 So California’s CCPA,
    0:22:51 which is the Consumer Protection Act,
    0:22:53 I can’t remember the exact name,
    0:22:57 but this is like very close to the European Union principles
    0:23:00 where you as a producer of data
    0:23:03 and even though companies also can hold a copy,
    0:23:04 you at least get to request your own data.
    0:23:05 In most parts of the US,
    0:23:07 the data that you generate,
    0:23:09 you don’t even have a shot at getting it
    0:23:10 because it sits with the companies
    0:23:12 and you don’t even have the right to request it.
    0:23:16 So I think we’re a very long way from this idea
    0:23:18 that you’re not just the owner of the data,
    0:23:23 but it’s also you can limit who else has control to add.
    0:23:25 – So I live in California.
    0:23:28 So you’re telling me there’s a way that I could go to Meta
    0:23:31 or Apple or Google and say, I want my data
    0:23:33 and I don’t want you selling it.
    0:23:34 – That’s a great question.
    0:23:36 So what you can do is you can request a copy of your data.
    0:23:37 That’s one thing.
    0:23:39 In many states, you can’t even do that.
    0:23:42 You might generate a lot of medical data,
    0:23:43 social media data and you,
    0:23:45 even though you generated it,
    0:23:47 you can’t even request a copy.
    0:23:50 Now what you can do is you can go to Meta request a copy
    0:23:53 and you can also request it to be deleted
    0:23:55 or to be transferred for it somewhere else.
    0:23:58 Now it’s still really hard to say,
    0:24:00 I want to use a service and product.
    0:24:02 And this is one of the things that I think makes it really
    0:24:05 challenges for people to manage the data properly.
    0:24:07 Because it’s a binary choice,
    0:24:09 you can say, yeah, I want you to delete my data
    0:24:11 and I’m not going to use the service anymore.
    0:24:12 But then you also can’t be part of Facebook.
    0:24:14 And yes, there are certain permissions
    0:24:15 that you can play with.
    0:24:16 What is public?
    0:24:17 What is not public?
    0:24:19 You can even play around with here’s some of the traces
    0:24:22 that I don’t want you to use in marketing.
    0:24:24 But typically, and this is true for,
    0:24:26 I think still Meta and other companies,
    0:24:28 it’s usually a binary choice.
    0:24:30 Either you use our product with most of your data
    0:24:33 being tracked and most of your data being commercialized
    0:24:36 in a way that you might not always benefit from.
    0:24:38 But you get to use the product for free
    0:24:39 or you don’t use it at all.
    0:24:41 And I think that’s the dichotomy
    0:24:43 that’s really hard for the brain to deal with.
    0:24:45 ‘Cause if the trade-off that we have to make as humans
    0:24:48 is service, convenience,
    0:24:51 the ability to connect with other people in an easy way,
    0:24:53 that’s what we’re going to choose over privacy
    0:24:55 and maybe a risk of data breaches in the future
    0:24:58 and maybe a risk of us not being able
    0:24:59 to make our own choices.
    0:25:01 So I think there’s now ways
    0:25:03 in which you can somehow eliminate that trade-off.
    0:25:06 ‘Cause I think if that’s what we’re dealing with,
    0:25:08 it’s an uphill battle.
    0:25:11 – I need to go dark for a little bit here.
    0:25:14 I read in your book about the example of Nazis.
    0:25:18 And I just want to know like today,
    0:25:22 could the Nazis go to Facebook, Apple and Google
    0:25:25 and get enough information from the breadcrumbs
    0:25:29 that we leave to track down where all the Jewish people are?
    0:25:31 Would that be easy today?
    0:25:33 – I think it would be incredibly easy.
    0:25:35 And it’s one of these examples in the book
    0:25:37 that I think is hard to process
    0:25:39 and that’s why it’s so powerful.
    0:25:41 I teach this class on the ethics of data
    0:25:43 and there’s always a couple of people who say,
    0:25:44 “Well, I don’t care about my privacy
    0:25:47 ’cause I have nothing to hide and the perks that I get,
    0:25:50 they’re so great that I’m willing to give up my privacy.”
    0:25:53 And what I’m trying to say is that it’s a risky gamble.
    0:25:55 But first of all, it’s a very privileged position
    0:25:57 ’cause just because you don’t have to worry
    0:25:58 about your data being out there,
    0:26:01 doesn’t mean that that doesn’t apply to other people.
    0:26:02 So I think in the US,
    0:26:05 even the role versus way it’s a Supreme Court decision
    0:26:08 to meddle with abortion rights,
    0:26:12 I think overnight essentially made women across the US
    0:26:14 realize, “Hey, my data being out there
    0:26:15 in terms of the Google searches that I make,
    0:26:18 my GPS records showing where I go,
    0:26:20 me using some period tracking apps,
    0:26:21 it’s incredibly intimate.”
    0:26:24 And it could overnight be used totally against me.
    0:26:28 So the example that you mentioned about Nazi Germany
    0:26:30 is such a powerful one
    0:26:33 ’cause it shows that leadership can change overnight.
    0:26:34 And I care so much about it
    0:26:36 ’cause I obviously grew up in Germany.
    0:26:38 So it was a democracy in 1938.
    0:26:40 And then the next year it wasn’t.
    0:26:42 And what we know is that atrocities
    0:26:44 within the Jewish community across Europe
    0:26:47 totally dependent on whether religious affiliation
    0:26:48 was part of the census.
    0:26:50 So you can imagine if you have a country
    0:26:52 where whether you’re Jewish or not
    0:26:54 is written in the census,
    0:26:57 all that Nazi Germany had to do is go to city hall,
    0:26:58 get hold of that census data
    0:27:00 and find the members of the Jewish community
    0:27:03 made it incredibly easy to track them down.
    0:27:06 But of course you don’t even need that census data anymore
    0:27:09 ’cause you can now have all of this data that’s out there
    0:27:10 that allows us to make these predictions
    0:27:13 about anything from political ideology,
    0:27:15 sexual orientation, religious affiliation,
    0:27:17 just based on what you talk about on Facebook.
    0:27:20 And even you could make the argument
    0:27:22 that maybe it’s the leaders of those companies
    0:27:25 handing over the data voluntarily.
    0:27:28 And I think we’ve even seen in the last couple of days
    0:27:31 how there’s like this political shifts in leadership
    0:27:33 when it comes to the big tech companies.
    0:27:35 But even if they weren’t playing the game,
    0:27:38 it would have been easy for a government to just replace
    0:27:41 that C-suite executives with new ones
    0:27:43 that are probably much more tolerant to
    0:27:44 some of the requests that they have.
    0:27:46 And I think it’s terrifying.
    0:27:47 And I think it’s a good example
    0:27:50 for why we should care about personal data.
    0:27:55 – Okay, so what you’re saying is,
    0:27:57 if I look at pictures of the inauguration
    0:28:02 and I see Apple, Google, Meta, Amazon up on stage.
    0:28:07 And so now the government can say,
    0:28:10 you know, according to Apple,
    0:28:13 you were in Austin and then you landed in an SFO.
    0:28:16 And then according to your visa statement,
    0:28:17 you know, you purchased this.
    0:28:19 And according to your phone’s GPS,
    0:28:21 you went to a Planned Parenthood
    0:28:23 in San Francisco, California.
    0:28:26 So we suspect you of going out of state
    0:28:27 to getting an abortion.
    0:28:30 So we’re opening up an investigation of you.
    0:28:33 That’s all easy today.
    0:28:34 – I think it’s very easy.
    0:28:37 And again, I’m not saying that the leaders
    0:28:40 of those big tech companies are sharing the data right now,
    0:28:41 but it’s certainly possible.
    0:28:44 And for me, there’s like this thing that I have in the book
    0:28:46 is data is permanent and leadership is.
    0:28:48 And right, so once your data is out there,
    0:28:50 it’s almost impossible to get it back.
    0:28:52 And you don’t know what’s gonna happen tomorrow.
    0:28:56 Even if Zuckerberg is not willing to share the data,
    0:28:59 there could be a completely new CEO tomorrow
    0:29:01 who might be a lot more willing to do that.
    0:29:05 So I think that the notion that we don’t have to worry
    0:29:07 in the here and now about our data being out there
    0:29:10 is just a very short-sighted notion.
    0:29:12 And ideally we can find a system.
    0:29:15 And I think there are ways now in which we can get
    0:29:17 some of these perks and some of the benefits
    0:29:20 and they come from using data without us necessarily having
    0:29:23 to collect the data in a central server.
    0:29:24 – Okay, so if I’m listening to this
    0:29:27 and I’m scared stiff because, you know,
    0:29:29 yes, you could look at what I do.
    0:29:31 You could look at, I went to the synagogue
    0:29:34 or I went to the, you know, temple or whatever.
    0:29:36 So yeah, and you’re right.
    0:29:39 Any of those people could replace and who knows.
    0:29:41 So then what do I do?
    0:29:46 – I do think that people should be to some extent scared.
    0:29:48 So I’m really trying to not say that technology,
    0:29:52 it’s all, like we’re all doomed because the data is out
    0:29:53 there and technology can be used too many.
    0:29:55 But I think there’s like many good use cases,
    0:29:58 but I do think we should be changing the system
    0:30:00 in a way that protects us from these abuses.
    0:30:03 And the one thing that I describe in the book,
    0:30:06 which I think we’re actually seeing a lot more of,
    0:30:08 but just not that many people know of,
    0:30:11 are these technologies that allow us to benefit from data
    0:30:13 without necessarily running the risk
    0:30:15 of a company collecting it centrally.
    0:30:17 So what I mean is, and there’s a technology
    0:30:19 that’s called federated learning.
    0:30:22 And you can imagine the example that I give
    0:30:24 is take medical data.
    0:30:27 So if we wanna better understand disease
    0:30:30 and we wanna find treatment that work for all of us,
    0:30:32 not just the majority of people who usually
    0:30:34 the pharma companies collect data of,
    0:30:37 but like we wanna know, given my medical history,
    0:30:39 given my genetic data, here’s what I should be doing
    0:30:42 to make sure that I don’t get sick in the first place
    0:30:44 or I can treat a disease that’s either rare
    0:30:46 or not as easily understood,
    0:30:49 we would all benefit from pooling data
    0:30:51 and better understanding disease.
    0:30:52 Now there’s a way in which you can say,
    0:30:56 instead of me sending all of this data to a central server
    0:30:59 and now this entity that collects all of the data,
    0:31:00 they have to safeguard it.
    0:31:03 Same way that Facebook is supposed to safeguard your data
    0:31:05 against intrusion from the government.
    0:31:08 Instead of having to sit in the central server,
    0:31:10 what we can do is we can make use of the fact
    0:31:12 that we all have supercomputers,
    0:31:14 but that might be your smartphone.
    0:31:16 Your smartphone is so much more powerful
    0:31:18 than the computers that we used to launch rockets to space
    0:31:19 a few decades ago.
    0:31:22 So what this entity that’s trying to understand disease
    0:31:25 could do is they could essentially send the intelligence
    0:31:28 to my phone or ask questions from my data
    0:31:30 and say, okay, here’s like how we’re tracking your symptoms.
    0:31:32 Here’s what we know about your medical history,
    0:31:35 but that data lives on my phone.
    0:31:37 And all I’m doing is I’m sending intelligence
    0:31:40 to the central entity to better understand the disease.
    0:31:42 Apple Siri, for example, is trained that way.
    0:31:44 So instead of Apple going in
    0:31:46 and capturing all of your speech data
    0:31:49 and centrally collecting it right now,
    0:31:51 Apple would be one of these companies
    0:31:54 who has to protect it now and tomorrow.
    0:31:56 And they just send the model to your phone.
    0:31:58 So they send Siri’s intelligence to your phone.
    0:32:00 It listens to what you say.
    0:32:03 It gets better at understanding, gets better at responding.
    0:32:05 And instead of you sending the data,
    0:32:07 it essentially just sends back a better model.
    0:32:10 It learns, it updates, sends back the model to Siri.
    0:32:13 And now everybody benefits ’cause we have a better speech.
    0:32:14 And that’s a totally different system
    0:32:16 ’cause we don’t have to collect the data
    0:32:18 in a central spot and then protected.
    0:32:22 – But Sandra, I mean, the point that you just made
    0:32:27 is that, yeah, Tim Cook may be saying that to us now.
    0:32:29 We’re only sending you the model
    0:32:31 and all your data is staying on your phone,
    0:32:34 but tomorrow’s Apple CEO
    0:32:36 could have a very different attitude, right?
    0:32:38 So how do we know if they’re only still
    0:32:41 sending the model right now?
    0:32:42 – So I think it’s a great question.
    0:32:44 And it’s funny that you mentioned Apple in that space
    0:32:46 ’cause I think they’re thinking about it this way.
    0:32:50 So again, I would much rather have Tim say,
    0:32:53 we’re only gonna locally process on your phone
    0:32:55 and that even if they change it tomorrow,
    0:32:57 what I’m mostly worried about
    0:33:00 is that they collect my data today under Tim Cook
    0:33:02 with the intention of making my experience better.
    0:33:05 They collect it today and then tomorrow there’s a new CEO
    0:33:08 ’cause now that CEO can just go back into the existing data
    0:33:11 and make all of these inferences that we talked about
    0:33:13 that are very intrusive and we don’t want to be out there.
    0:33:15 At least even if Apple decides tomorrow
    0:33:18 to shift from that model to a new one,
    0:33:20 that’s gonna be publicly out there.
    0:33:23 So if that happens, at least people can start from scratch
    0:33:25 and decide whether they still want to use Apple products
    0:33:26 or not.
    0:33:29 My main concern is that all the data that gets collected
    0:33:31 and now leadership changes.
    0:33:32 – Wow.
    0:33:35 Okay, speaking of collected data,
    0:33:39 you mentioned an example of a guy who applied to a store
    0:33:41 and he took a personality test
    0:33:46 and the personality test yielded let’s say undesirable traits.
    0:33:50 And so he didn’t get that job
    0:33:52 and that personality test stuck with him
    0:33:56 and kind of hurt his employment in the future too.
    0:33:58 So what’s the advice?
    0:34:02 Don’t take the personality test or lie on the personality test.
    0:34:04 What’s the guy supposed to do
    0:34:07 if he’s required to take a personality test
    0:34:08 to apply for a job?
    0:34:11 – Yeah, and you’re really going to other dark places
    0:34:13 but I think which I think is important
    0:34:15 ’cause for me, this example
    0:34:18 and this one is not even using predictive technology, right?
    0:34:20 So this one is a guy sitting down
    0:34:22 and admitting that I think in his case,
    0:34:24 he was like suffering from bipolar disorder.
    0:34:27 So kind of sends the score on neuroticism
    0:34:29 which is one of the personality traits
    0:34:32 that kind of says how you regulate emotions through the roof.
    0:34:34 And because he admitted to that,
    0:34:38 he was essentially almost discarded from all of the jobs
    0:34:40 that had like a customer facing interface
    0:34:42 ’cause companies were worried that he wouldn’t be dealing
    0:34:45 and well with people who come and complain.
    0:34:48 Now, the reason for why I think this example is important
    0:34:52 is it just means who other people think we are
    0:34:55 kind of closes some doors in our lives, right?
    0:34:56 So sometimes it opens doors.
    0:34:59 If someone thinks that you’re the most amazing person
    0:35:01 and you absolutely deserve a loan,
    0:35:04 maybe you have opportunities that other people don’t have
    0:35:07 but oftentimes that the danger comes in
    0:35:10 when someone thinks that we have certain traits
    0:35:13 that then would lead to behavior that we don’t wanna see.
    0:35:16 And now in the context of self-reported personality tests,
    0:35:19 at least you have like some say over what that image is.
    0:35:23 If you take it to an automated prediction of an algorithm
    0:35:24 and coming back to this notion
    0:35:26 that those algorithms are pretty good
    0:35:28 at understanding of psychology,
    0:35:29 but they’re certainly not perfect.
    0:35:31 So now you suddenly live in a world
    0:35:33 where someone make a prediction about you
    0:35:35 based on the data that you generate,
    0:35:37 you never even touched that prediction
    0:35:39 ’cause you don’t even get to see it.
    0:35:40 They predict that you’re neurotic
    0:35:42 and maybe they even get it wrong.
    0:35:44 Maybe you’re one of the people where the algorithm
    0:35:46 makes a mistake and gets it wrong.
    0:35:47 And now you suddenly you’re excluded
    0:35:50 from all of these opportunities for jobs, loans and so on.
    0:35:53 And so I think for me, this notion that there’s someone
    0:35:55 who passively tries to understand who you are
    0:35:59 and then takes action that again, sometimes open doors,
    0:36:01 sometimes it’s incredibly helpful
    0:36:03 because maybe we connect you with mental health support
    0:36:07 but at other times it might also close doors
    0:36:09 in a way that you don’t even have insights to.
    0:36:10 And for me, that’s the scary part
    0:36:12 where I feel like we’re losing control
    0:36:15 over essentially our lives.
    0:36:18 – Wait, but are you saying that you should refuse
    0:36:22 to take the personality test or you should lie?
    0:36:26 – So in the case of the personality test,
    0:36:27 first of all, it’s not a good practice.
    0:36:29 So as a personality psychologist,
    0:36:31 the way that we think of these personality tests
    0:36:34 is that it shouldn’t be an exclusion criteria.
    0:36:37 So I think that what they’re meant to do
    0:36:40 is to say, here’s certain professions
    0:36:43 that you might just be more suited for.
    0:36:44 ‘Cause if you’re an introvert
    0:36:46 who kind of hates dealing with other people
    0:36:49 and you’re constantly at the forefront of like a sales pitch,
    0:36:51 you’re probably not gonna enjoy it as much.
    0:36:53 They were never really meant to say,
    0:36:55 you got a low score on conscientiousness
    0:36:56 and we’re gonna exclude you.
    0:36:58 It’s also very short-sighted
    0:37:01 because technically what makes a company successful
    0:37:04 and what makes team successful is to have many people
    0:37:05 who think about the world differently.
    0:37:08 So I have this recent research that’s still very preliminary,
    0:37:11 but it’s looking at startups
    0:37:13 and it just looks at how quickly do they manage
    0:37:15 to hire people with all of these different traits.
    0:37:17 So you can come together and you can say, well,
    0:37:19 but I think this way and then you think this way
    0:37:21 and we all bring a different perspective to the table.
    0:37:23 And they’re usually more successful.
    0:37:25 So this notion that companies just say,
    0:37:27 here’s a trait that we don’t wanna see.
    0:37:29 It is very short-sighted.
    0:37:30 What we do know, and this is,
    0:37:33 I promise coming back to your question,
    0:37:35 is that saying that you don’t wanna respond
    0:37:38 to a questionnaire is typically seen as the worst sign.
    0:37:41 So there was this study where they looked at things
    0:37:42 that people don’t like to admit to, right?
    0:37:44 I think it was like stuff about health,
    0:37:46 stuff about people’s sexual preferences
    0:37:50 and saying, I don’t wanna answer the question is worst
    0:37:53 and hitting the worst option on the menu.
    0:37:55 So I absolutely agree that in that case,
    0:37:58 the guy essentially didn’t have a shot,
    0:38:00 but the problem is once it’s recorded,
    0:38:02 he didn’t even get to take the test again
    0:38:04 because the results were just shared
    0:38:06 from company to company.
    0:38:09 – So what I hear you say is lie.
    0:38:14 – In this case, frankly, if it had been me,
    0:38:15 I probably would have lied.
    0:38:17 If I had known that this is,
    0:38:19 if the company is making the mistake
    0:38:22 of using the test in that way,
    0:38:26 what I would recommend to people taking the test is,
    0:38:29 yeah, like think about what the company wants to hear.
    0:38:30 – Okay.
    0:38:33 – Which is harder to do with data, by the way.
    0:38:36 It’s funny ’cause oftentimes when we think of predictions
    0:38:39 of our psychology based on our digital lives,
    0:38:40 we think of social media and it’s always,
    0:38:43 but I can to some extent manipulate
    0:38:45 how I portray myself on social media.
    0:38:47 That’s true for some of these explicit identity claims
    0:38:50 that we think about and have control over.
    0:38:51 There’s so many other traces.
    0:38:53 Take your phone again.
    0:38:58 The fact like my thing is that I’m not the most organized
    0:38:59 person even though I’m German.
    0:39:02 So I think I was expelled for a reason.
    0:39:06 And I don’t organize my cutlery the way that my husband does.
    0:39:09 And would I admit to this happily on a personality test
    0:39:11 that like in the context of an assessment center,
    0:39:12 probably not, right?
    0:39:14 If someone gives me the question there
    0:39:16 that says I make a mess of things,
    0:39:18 would I be inclined to say I strongly agree?
    0:39:20 Maybe not ’cause I understand
    0:39:21 that’s probably not what they want to hear.
    0:39:23 Now, if they tap into my data,
    0:39:26 they see that my phone is constantly running out of battery,
    0:39:28 which is like one of these strong predictors
    0:39:30 of you not being super conscientious.
    0:39:34 I constantly, I go to the deli on the corner five times a day
    0:39:36 ’cause I can’t even plan ahead for the next meal.
    0:39:37 And I constantly run to the bus.
    0:39:40 So if someone was tapping into my data,
    0:39:42 they would understand 100%
    0:39:44 that I’m not the most organized person.
    0:39:46 So there’s something about this data world
    0:39:48 and all of these traces that we generate,
    0:39:52 which are in a way much harder to manipulate
    0:39:54 than a question on a questionnaire.
    0:39:57 – Well, and now people listening to this podcast
    0:40:02 are thinking, how many times did I use the pronoun I?
    0:40:06 Oh my God, I’m telling people that I have, you know,
    0:40:07 depression and stuff.
    0:40:10 – And again, it’s not deterministic.
    0:40:13 So you might be using a lot of I
    0:40:15 because something happened that you want to share.
    0:40:18 It’s just like on average, it increases your likelihood.
    0:40:21 – Up next on Remarkable People.
    0:40:24 – If I wanted to get a portfolio, a data portfolio,
    0:40:25 on most of the people,
    0:40:27 I would be able to get it really cheaply.
    0:40:29 And that’s something that, again,
    0:40:32 I think most of us or all of us should be worried about.
    0:40:35 And you do see use cases where policymakers
    0:40:37 are actually waking up to this reality.
    0:40:40 There was this case of a judge actually across the bridge
    0:40:41 from here in New Jersey,
    0:40:44 whose son was murdered by someone
    0:40:46 that she litigated against in the past.
    0:40:48 They found her data online from data brokers,
    0:40:51 tracked her down, and in this case, killed her son.
    0:40:55 (gentle music)
    0:40:59 – Thank you to all our regular podcast listeners.
    0:41:02 It’s our pleasure and honor to make the show for you.
    0:41:04 If you find our show valuable,
    0:41:08 please do us a favor and subscribe, rate, and review it.
    0:41:11 Even better, forward it to a friend,
    0:41:13 a big mahalo to you for doing this.
    0:41:18 – Welcome back to Remarkable People with Guy Kawasaki.
    0:41:22 So you had a great section about how,
    0:41:25 by looking at what people have searched Google for,
    0:41:27 you can tell a lot about a person
    0:41:30 or at least draw conclusions.
    0:41:35 So do you think prompts will have the same effect?
    0:41:37 Like, you know, what I asked chat,
    0:41:41 GPT is a very good window into what I am.
    0:41:42 – I think so, right?
    0:41:44 And I don’t necessarily, I think it’s prompts.
    0:41:46 I think it’s questions that we have.
    0:41:47 And if you think about Google,
    0:41:51 there’s questions that I type into the Google search bar
    0:41:54 that I wouldn’t feel comfortable asking my friends
    0:41:55 or even sharing with my spouse.
    0:41:57 So it’s like this very intimate window
    0:41:59 into what is top of mind for us
    0:42:02 that we might not feel comfortable sharing with others.
    0:42:03 Yeah, so I was actually,
    0:42:04 which I thought was so interesting
    0:42:06 ’cause I was part of this.
    0:42:09 It was like a documentary about artistic
    0:42:11 and what they did is they invited a person.
    0:42:13 So they found a person online.
    0:42:15 They looked at all of her Google searches
    0:42:19 and then they recreated her life all the way from,
    0:42:20 here’s the job that she took,
    0:42:22 kind of suffered from anxiety
    0:42:24 and the feeling that she wasn’t good enough
    0:42:26 in the space that she was working in,
    0:42:29 all the way to her becoming pregnant
    0:42:30 and then having a miscarriage.
    0:42:33 And they kind of recreated her life with an actress.
    0:42:35 And then at some point bring in the real person
    0:42:37 and the person watches the movie
    0:42:39 and you can see how just over time,
    0:42:43 she realizes just how intimate those Google searches are
    0:42:46 ’cause what the documentary team had created,
    0:42:49 the life that they had recreated was so close
    0:42:50 to her actual experience.
    0:42:52 And again, just by looking at their data.
    0:42:54 So for me, it was a nice way of showcasing
    0:42:57 that it’s really not just this one data point
    0:42:58 or a collection of data points,
    0:43:02 but it’s a window into our lives and our psychology.
    0:43:05 – And not to get too dark,
    0:43:08 but the CEO of Google was on the stage, right?
    0:43:12 So what happens when generative AI takes over
    0:43:17 and the AI is drafting my email,
    0:43:21 drafting my responses and to take an even further step,
    0:43:25 what happens when it’s my agent answering for me?
    0:43:28 Then is it still as predictive
    0:43:31 or will the agent reflect who I really am
    0:43:32 or it throws everything off
    0:43:36 because it’s not guy answering anymore?
    0:43:37 – So to me, that’s a super interesting question.
    0:43:40 First of all, in a way like generative AI
    0:43:42 democratized the entire process.
    0:43:44 So when I started this research,
    0:43:48 we had to get a data set that takes your digital traces.
    0:43:50 Let’s say what you post on social media
    0:43:52 and maybe a self-report of your personality.
    0:43:55 And then we train a model that gets from social media
    0:43:56 to your personality.
    0:43:59 Now I can just ask chat GPT and say,
    0:44:01 hey, here are guys Google searches.
    0:44:02 Here’s what he bought on Amazon.
    0:44:05 Here’s what we talked about on Facebook.
    0:44:07 What do you think is his big five personality traits?
    0:44:10 What do you think are his moral values?
    0:44:11 What do you think is again,
    0:44:12 like some of these very intimate traits
    0:44:14 that we don’t want to share?
    0:44:15 And it does a remarkable job.
    0:44:17 It’s never been trained to do that,
    0:44:18 but because it’s read the entire internet,
    0:44:21 it has to understand so much about psychology.
    0:44:23 And then obviously taking it to the next level,
    0:44:25 it’s not just understanding,
    0:44:28 but also replicating your behavior.
    0:44:32 And the one thing that I’m most concerned about,
    0:44:33 aside from like manipulative,
    0:44:35 it’s just that it’s going to make us so boring.
    0:44:37 If these language models,
    0:44:39 they’re very good at coming up with an answer
    0:44:43 that works reasonably well, like 80%.
    0:44:45 But it’s very unlikely that it comes up with something
    0:44:47 like super unique that we’ve never thought about,
    0:44:49 that makes us different from other people.
    0:44:51 So I think what happens is that we’re just going to see
    0:44:54 more and more of who the AI believes we are.
    0:44:57 ‘Cause it’s essentially almost like the solidified system
    0:44:59 of here’s who I think guy is,
    0:45:01 and now I’m just optimizing.
    0:45:02 And in the way that humans learn,
    0:45:05 there’s this trade off between exploitation.
    0:45:08 So that is doing the stuff that you know is good for you.
    0:45:11 So if you think about restaurant choices,
    0:45:14 you can either go to the same restaurant time and again,
    0:45:15 because you know that you like it.
    0:45:17 So there’s not going to be any surprise.
    0:45:19 It’s going to be a good experience.
    0:45:21 But the second part of human learning
    0:45:23 and experience is the exploration part.
    0:45:25 And it exposes you to risk,
    0:45:26 because maybe you go to a restaurant
    0:45:28 and it turns out to be not great
    0:45:29 and you would have been better off
    0:45:31 going to your typical choice.
    0:45:33 But maybe you actually also stumble on a restaurant
    0:45:35 that you love.
    0:45:36 And for that, you had to take the risk
    0:45:38 and explore something new.
    0:45:40 And my worry with these AI systems
    0:45:42 and most types of personalization
    0:45:45 is that they very much focus on exploitation.
    0:45:47 They take what you’ve done in the past,
    0:45:47 who they think you are,
    0:45:50 and they try to give you more of that.
    0:45:52 But you don’t get like the fun parts of exploring.
    0:45:54 It’s like Google Maps is amazing
    0:45:57 at getting you from A to B most efficiently,
    0:46:00 but you also never stumble upon these cute little coffee shops
    0:46:01 that you didn’t know were there before
    0:46:03 because you got lost.
    0:46:05 And for me, that’s in a way the danger
    0:46:07 of having these systems replaces.
    0:46:10 Is that just gonna make us basic and boring?
    0:46:15 – What if I ask the opposite question,
    0:46:19 which is I want to help companies be more accurate
    0:46:23 in predicting my choices, right?
    0:46:25 So I wanna tell Google,
    0:46:29 stop sending me world wrestling news and Google news
    0:46:32 and stop telling me about the Pittsburgh Steelers
    0:46:36 and stop sending me ads for trucks
    0:46:38 ’cause I don’t want a truck and I don’t want a Tesla.
    0:46:42 And I wanna make a case that what if you want companies
    0:46:44 to understand you better, then what do you do?
    0:46:47 – First of all, I think it should be an option, right?
    0:46:49 So there should be two different modes for you guys
    0:46:51 that says right now I’m trying to explore.
    0:46:53 Right now I just wanna see something
    0:46:55 that’s different to what I typically want.
    0:46:57 But also now I’m in this mode
    0:46:59 where I just want you to know exactly what I’m looking for.
    0:47:01 And I don’t want you to send me the camera
    0:47:03 even though I was not interested in the camera
    0:47:05 for the last three weeks.
    0:47:08 So in this case, I think what companies can do,
    0:47:11 which is what they I think oftentimes don’t do enough of.
    0:47:14 So it’s like having a conversation with you
    0:47:17 that kind of allows you to interact with the profile.
    0:47:19 Most of the time they just passively say,
    0:47:20 here’s who I think guy is
    0:47:23 and now we’re optimizing for their profile.
    0:47:24 But if they get it wrong,
    0:47:26 there’s no way for you to say no, no, no,
    0:47:28 why don’t you just take out this prediction
    0:47:30 that you’ve made ’cause it’s not accurate,
    0:47:32 which is annoying for me ’cause now as you said,
    0:47:34 you get like ads for wrestling
    0:47:36 that you might not be interested in at all.
    0:47:37 And it’s also bad for business
    0:47:39 ’cause now they’re optimizing for something
    0:47:41 that is not who you are.
    0:47:43 So I think first of all, give people the choice
    0:47:45 whether they wanna be in an explorer mode
    0:47:47 or an exploitation mode.
    0:47:50 And then second part is even within the exploitation mode
    0:47:51 where we’re just trying to optimize
    0:47:53 for who we think you are,
    0:47:56 give people the choice and say, no, you’re wrong.
    0:47:57 I wanna correct that.
    0:47:59 It’s good for the user and it’s good for the company.
    0:48:03 – Well, if anybody out there is listening
    0:48:05 and embraces this idea,
    0:48:09 I suggest you not call it exploitation mode,
    0:48:12 maybe optimization mode might be a more pleasant marketing.
    0:48:14 – Personalization mode, yeah, that’s true, that’s true.
    0:48:16 – Personalization mode, yeah.
    0:48:19 Okay, so some three short,
    0:48:21 tactical and practical questions.
    0:48:23 So knowing all that you know,
    0:48:26 and I think we went dark a few times
    0:48:28 and show people the risk here.
    0:48:33 So do you use email, messages, WhatsApp or signal?
    0:48:36 What do you use personally?
    0:48:37 – I mostly use WhatsApp.
    0:48:38 First of all, it’s encrypted,
    0:48:41 but then it also just what everybody in Europe uses.
    0:48:44 So I wouldn’t even give myself any credit for that.
    0:48:46 And it’s funny ’cause I think the fact
    0:48:48 that I’ve become a lot more pessimistic over the years
    0:48:50 has to do with my own behavior.
    0:48:53 So I know that we can be tracked all the time
    0:48:56 and I still mindlessly say yes to all of the permissions
    0:48:57 and so on and so forth.
    0:48:59 So I think we just don’t have the time
    0:49:02 and the mental capacity to do it all by ourselves.
    0:49:04 There’s only 24/7 in a day.
    0:49:06 And I’d much rather spend a meal with my family
    0:49:08 than going through all the terms and conditions and permission.
    0:49:11 So I think if it’s just up to us,
    0:49:13 it’s an unfair battle that we don’t stand a chance.
    0:49:16 – And why, of all people in the world,
    0:49:18 would you not default to signal
    0:49:21 because it’s encrypted both the message
    0:49:24 and the meta information?
    0:49:26 – It’s mostly because not that many of my friends
    0:49:27 are using it.
    0:49:29 So again, in this case, it would be a trade-off
    0:49:31 between I get protected more,
    0:49:33 but there’s also like a downside
    0:49:35 because I can’t reach out to the people
    0:49:36 that I want to reach out.
    0:49:38 And I feel like if that’s the trade-off,
    0:49:40 the brains of most people will gravitate to,
    0:49:43 I’m just gonna get all of the convenience that I want.
    0:49:46 – Okay, second short question is,
    0:49:49 when you use social media,
    0:49:52 do you use it like read only and you don’t post,
    0:49:54 you don’t comment and don’t like
    0:49:57 or like are you all in on social media
    0:50:00 and dropping breadcrumbs all over the place?
    0:50:02 – I think even if you don’t use social media,
    0:50:05 even if I was completely absent from social media,
    0:50:07 I would still be generating breadcrumbs all the time
    0:50:09 ’cause I have a credit card and I have a smartphone
    0:50:11 and there’s facial recognition.
    0:50:12 I just don’t want people to think
    0:50:15 that social media is the only way to produce traces.
    0:50:17 Now I don’t actively use it as much,
    0:50:21 but not because I know that I shouldn’t be doing it.
    0:50:22 It’s just because it’s so much work.
    0:50:26 I feel like I much rather have interesting offline conversations
    0:50:29 that thinking about what I should post on X
    0:50:31 and some of the other ones.
    0:50:35 So it’s a different reason than worries about privacy.
    0:50:39 – Okay, now is the logic that, yes,
    0:50:41 Google knows something, Apple knows something,
    0:50:44 Meta knows something, X knows something,
    0:50:45 everybody knows something,
    0:50:47 but nobody knows everything.
    0:50:51 So the fact that it’s all sort of siloed
    0:50:55 keeps me safe or is that a delusion?
    0:50:56 – I think it’s probably a delusion.
    0:51:00 So my argument would be that they have most of these traces.
    0:51:03 So if you think of applications, again,
    0:51:05 like when you download Facebook here,
    0:51:07 it asks you to tap into your GPS records,
    0:51:10 into your microphone, into your photo gallery.
    0:51:12 You use Facebook to log into most of the services
    0:51:14 that you’re using elsewhere.
    0:51:17 So they have a really holistic picture
    0:51:20 of what your life looks like across all of these dimensions.
    0:51:21 And by the way, they also have it for users
    0:51:24 who don’t use Facebook because it’s so cheap now
    0:51:27 to buy these data points from data brokers
    0:51:31 that if I wanted to get a portfolio, a data portfolio,
    0:51:32 on most of the people,
    0:51:34 I would be able to get it really cheaply.
    0:51:36 And that’s something that, again,
    0:51:39 I think most of us or all of us should be worried about.
    0:51:42 And you do see use cases where policymakers
    0:51:43 are actually waking up to this reality.
    0:51:47 There was this case of a judge actually across the bridge
    0:51:49 from here in New Jersey, whose son was murdered
    0:51:52 by someone that she litigated against in the past.
    0:51:55 They found her data online from data brokers,
    0:51:58 tracked her down, and in this case, killed her son,
    0:52:00 Biden signed something into a fact
    0:52:03 that now protects judges from having their data out there
    0:52:05 with data brokers, which makes me think
    0:52:07 if we do this for judges and we’re concerned
    0:52:09 that we can easily buy data about judges,
    0:52:12 why not protect everybody else?
    0:52:16 I think there’s a good point to be made that data on us
    0:52:18 is so cheap and available from different sources
    0:52:21 that even if you don’t use social media,
    0:52:23 it’s easy to get your hands on.
    0:52:27 – You introduced the concept in the last part of your book,
    0:52:29 which I don’t quite understand.
    0:52:33 So please explain what a data co-op does.
    0:52:36 – Yeah, it’s one of my favorite parts of the book, actually,
    0:52:38 ’cause it thinks of how do you help people
    0:52:39 make the most of their data, right?
    0:52:43 So we’ve talked a lot about the dark sides,
    0:52:44 and I think regulation is needed
    0:52:48 if we wanna try to prevent the most egregious abuses,
    0:52:50 but it doesn’t really give you a way of,
    0:52:53 first of all, managing your data in the absence of regulation,
    0:52:54 and it also doesn’t give you a way
    0:52:56 to make the most of it in a positive way.
    0:53:01 So data co-ops are essentially these member-owned entities
    0:53:04 that help people who have a shared interest in using data
    0:53:06 to both protect it and make the most of it.
    0:53:09 So my favorite example is one in Switzerland
    0:53:11 that’s called MyData, and they’re focused on the medical space.
    0:53:14 So one of the applications that they have
    0:53:17 is working with MS patients.
    0:53:19 So patients who suffer from multiple sclerosis,
    0:53:20 which is one of these diseases
    0:53:22 that, again, is so poorly understood
    0:53:24 ’cause it’s determined by genetics,
    0:53:25 and it’s determined by your medical history,
    0:53:27 by your environment, and what they do
    0:53:30 is they have a co-op of people.
    0:53:34 So patients who suffer from MS and healthy controls
    0:53:36 that own the data together.
    0:53:39 So it’s a little bit similar to the financial space
    0:53:41 where you oftentimes have entities
    0:53:43 that have fiduciary responsibilities.
    0:53:47 So they’re legally obligated to act in your best interest.
    0:53:50 So data co-ops are entities that are owned by the members.
    0:53:53 They are legally obligated to act in their best interest,
    0:53:56 and now you can imagine, in the case of the MS patients,
    0:53:57 they can pool the data,
    0:53:59 they can learn something about the disease,
    0:54:01 and they can also then, in this case,
    0:54:03 work with doctors of the patients
    0:54:05 and say, here’s something that we’ve learned from the data.
    0:54:08 This treatment might be particularly promising
    0:54:10 for a patient at this stage with these symptoms.
    0:54:12 Why don’t you try this?
    0:54:15 So the people benefit immediately,
    0:54:16 and also because they’re now together,
    0:54:20 they can hire experts that help them manage their data,
    0:54:23 think about, well, here’s maybe some of the companies
    0:54:24 that we wanna share the data with,
    0:54:26 but maybe we do it in a secure place
    0:54:28 that doesn’t require us to send all of the data.
    0:54:30 So these data co-ops, for me,
    0:54:33 is just like a new form of data governance
    0:54:35 that gives us, I think of it as allies.
    0:54:38 So if we have a way that we wanna use data,
    0:54:40 we need other people with a similar goal
    0:54:42 so that we make data, first of all, more valuable,
    0:54:45 ’cause if I have my data, my medical history
    0:54:47 and my genetic data as an MS patients,
    0:54:49 doesn’t help me at all, I need these other people,
    0:54:53 but it’s not coming together as a pharma company
    0:54:56 that’s grabbing all of this data and then making profits,
    0:54:58 but it’s coming together as a community
    0:55:00 and benefiting directly.
    0:55:02 So that’s what data co-ops are.
    0:55:06 But a data co-op doesn’t exactly solve the problem
    0:55:09 of all my breadcrumbs on social media and Apple
    0:55:11 and all the other stuff, right?
    0:55:14 This is for a very specific set of data.
    0:55:17 – Agreed, so it’s not necessarily a specific set of data.
    0:55:19 You could imagine in the European Union
    0:55:21 where you’re allowed to pull your data,
    0:55:24 you could have a data co-op of people
    0:55:26 who just pull together their Facebook data
    0:55:27 and now they go to Facebook and say,
    0:55:31 “Hey, look, we’re all gonna leave if there’s no way,
    0:55:33 “if you’re not putting in, let’s say,
    0:55:34 “technology like federated learning
    0:55:36 “to protect our privacy a bit more.”
    0:55:38 So I do think that there is also ways
    0:55:40 in which people can come together
    0:55:42 and get just a lot more negotiation power at the table.
    0:55:44 Then if you go to Facebook and say,
    0:55:48 “Hey, I’m Guy, I wanna force you to do something different,”
    0:55:49 not sure if they’re gonna listen.
    0:55:52 If you suddenly have 10 million people doing that,
    0:55:54 you are in a better spot.
    0:55:57 – Okay, I like this idea.
    0:55:59 Okay, now I understand it better.
    0:56:01 Thank you very much.
    0:56:04 Listen, I like to end my podcast with one question
    0:56:06 that I ask all the remarkable people
    0:56:08 and clearly you’ve proven you’re remarkable
    0:56:10 with this interview.
    0:56:13 And that would be stepping aside, stepping back,
    0:56:17 stepping up whatever direction you wanna use.
    0:56:20 Like, what’s the most important piece of advice
    0:56:24 you can give to people who wanna be remarkable?
    0:56:26 – I think it’s don’t take yourself too seriously.
    0:56:28 I think some humility and the way
    0:56:32 that you approach yourself and others goes a long, long way.
    0:56:33 – Alrighty.
    0:56:35 This is a great episode.
    0:56:36 Thank you so much.
    0:56:38 And I hope I didn’t go too dark for you,
    0:56:40 but this is a dark subject, actually.
    0:56:41 – I do think it is.
    0:56:44 And I think there’s a lot of room for improvement.
    0:56:46 That’s why I care about the topic so much.
    0:56:48 – Alrighty, so Sandra Matz.
    0:56:50 Thank you very much for being a guest.
    0:56:52 This has been Remarkable People.
    0:56:55 I’m Guy Kawasaki, and I hope we helped you
    0:56:57 be a little bit more remarkable today.
    0:57:00 So my thanks to Matt as a Nizmer, the producer,
    0:57:04 Tessa Nizmer, our researcher, Jeff C. and Shannon Hernandez,
    0:57:05 who make it sound so great.
    0:57:08 So this is the Remarkable People podcast.
    0:57:12 Until next time, mahalo and aloha.
    0:57:18 – This is Remarkable People.

    What can your Google searches reveal about your personality? In this episode of Remarkable People, Guy Kawasaki explores the fascinating world of psychological targeting with Sandra Matz, Professor at Columbia Business School.

    Matz shares eye-opening insights about how our digital footprints expose our deepest traits and behaviors. She reveals how companies predict our personalities through social media posts, explains the surprising link between language use and emotional states, and discusses why data privacy isn’t just about personal convenience—it’s about protecting ourselves in an uncertain future. Whether you’re concerned about data security or curious about what your online behavior reveals about you, this episode provides essential insights for navigating our increasingly digital world.

    Guy Kawasaki is on a mission to make you remarkable. His Remarkable People podcast features interviews with remarkable people such as Jane Goodall, Marc Benioff, Woz, Kristi Yamaguchi, and Bob Cialdini. Every episode will make you more remarkable.

    With his decades of experience in Silicon Valley as a Venture Capitalist and advisor to the top entrepreneurs in the world, Guy’s questions come from a place of curiosity and passion for technology, start-ups, entrepreneurship, and marketing. If you love society and culture, documentaries, and business podcasts, take a second to follow Remarkable People.

    Listeners of the Remarkable People podcast will learn from some of the most successful people in the world with practical tips and inspiring stories that will help you be more remarkable.

    Episodes of Remarkable People organized by topic: https://bit.ly/rptopology

    Listen to Remarkable People here: **https://podcasts.apple.com/us/podcast/guy-kawasakis-remarkable-people/id1483081827**

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  • Alison Wood Brooks: Cracking the Conversation Code

    Alison Wood Brooks: Cracking the Conversation Code

    AI transcript
    0:00:02 (upbeat music)
    0:00:11 – What model roadcaster do you have?
    0:00:13 – You know what’s funny, it’s very above my pay grade.
    0:00:15 I’m in a band and somebody asked for advice
    0:00:18 from my bandmates about what kind of microphone to get.
    0:00:20 I’m wearing my husband’s headphones.
    0:00:21 He’s the drummer in our band.
    0:00:23 And then I have this roadcaster
    0:00:25 and I don’t know how to use it at all.
    0:00:28 All I know how to do is make like one funny sound effect.
    0:00:30 But it’s a roadcaster, I can look at it.
    0:00:31 It’s a roadcaster.
    0:00:34 – Oh, I have a roadcaster, too.
    0:00:35 – Roadcaster, too?
    0:00:36 – Yeah, I’ll play this.
    0:00:37 – Yeah, I can’t hear.
    0:00:39 – So, yeah.
    0:00:41 (upbeat music)
    0:00:46 (laughing)
    0:00:47 – I love it, I love it.
    0:00:48 I was giving it to you
    0:00:51 and you thought it was mine, let’s see.
    0:00:53 – I can change my voice, I can have my dress.
    0:00:56 (laughing)
    0:00:58 (laughing)
    0:01:02 – Podcasters just wanna have fun, so.
    0:01:03 (laughing)
    0:01:05 – That’s my only trick, guy.
    0:01:08 (laughing)
    0:01:10 – So, is today launch day?
    0:01:12 – Today is launch day.
    0:01:15 You’re catching me on such a crazy day.
    0:01:17 It’s so miraculous.
    0:01:19 – I figured that out last night.
    0:01:21 Yeah, today is launch day and I said,
    0:01:23 maybe her PR firm made a mistake
    0:01:27 and they didn’t intend to take up her morning on launch day.
    0:01:28 I feel so bad.
    0:01:30 Are you sure you have time to do this?
    0:01:31 – You’re so kind.
    0:01:34 It’s such a welcome distraction.
    0:01:36 Otherwise, what am I gonna be doing?
    0:01:39 Just hitting refresh on the sales page, I don’t know.
    0:01:41 (laughing)
    0:01:44 – You’re not on the Today Show or Joe Rogan or anything.
    0:01:47 – Well, I went on Mel Robbins yesterday.
    0:01:50 When my kids were home on a snowy MLK day,
    0:01:52 I went and visited Mel Robbins
    0:01:54 and today I get to talk to you.
    0:01:57 (laughing)
    0:02:00 – You need to talk to your PR firm to get better people
    0:02:02 for your launch day than me.
    0:02:03 Oh my God.
    0:02:04 (laughing)
    0:02:07 – You’re too humble, too humble.
    0:02:10 – Oh shit, I forgot to introduce you.
    0:02:13 So, listen everybody, I’m Guy Kawasaki.
    0:02:15 This is the Remarkable People podcast
    0:02:18 and we’re on the mission to make you remarkable
    0:02:21 and today we have the remarkable Alison Wood Brooks.
    0:02:24 She’s a professor at Harvard Business School.
    0:02:28 I like to call her the Queen of Conversation
    0:02:30 because she teaches a course
    0:02:33 on how to be a great conversationalist
    0:02:37 and we’re honored to have her on her launch day
    0:02:39 and as an author, I can tell you,
    0:02:42 launch day is not an ideal day to do a long interview.
    0:02:44 You got so much other things to do.
    0:02:47 So, her PR firm screwed up and scheduled her
    0:02:48 on the wrong day.
    0:02:49 So, we’re gonna make the best of it.
    0:02:50 – We gotta forgive them.
    0:02:52 You’ve done a wonderful job.
    0:02:54 I get to talk to you, Guy, come on.
    0:02:57 (laughing)
    0:02:59 – So, I know we’re supposed to start with small talk.
    0:03:01 So, how’s the weather in Boston?
    0:03:03 – You know what, it is beautiful here.
    0:03:06 We had a snow storm and I love snow.
    0:03:09 It’s so gorgeous and my kids went sledding yesterday.
    0:03:11 It was very picturesque.
    0:03:12 Where are you in the world?
    0:03:13 Are you in Silicon Valley?
    0:03:17 – Yes, I’m in Santa Cruz and we have a gorgeous day today.
    0:03:20 Madison and I are gonna go surfing later today too.
    0:03:22 – Oh, imagine that.
    0:03:24 My kids were surfing on the snow yesterday
    0:03:25 and you get to actually go surfing.
    0:03:26 That sounds nice.
    0:03:28 (laughing)
    0:03:32 – I fully understand your hierarchy of small talk,
    0:03:34 directed talk and deep talk.
    0:03:36 So, we gotta engage in some small talk
    0:03:38 to observe your book, right?
    0:03:39 – That’s right.
    0:03:40 No pressure.
    0:03:42 – So, I gotta pitch you some soft balls
    0:03:43 in this small talk phase.
    0:03:46 What’s something that you’re really lousy at
    0:03:47 that you love to do?
    0:03:49 – I love that question.
    0:03:50 It’s one of my favorites.
    0:03:53 One of my really lousy at what I love to do.
    0:03:55 Probably cooking.
    0:03:58 I don’t cook often, but when I do, it’s so soothing
    0:04:02 and it’s so cozy and warm and I’m so bad at it, guy.
    0:04:03 I’m not a good cook.
    0:04:06 I have no business being in the kitchen,
    0:04:09 but I do love creating a meal for my family
    0:04:11 every once in a while.
    0:04:14 – Well, you know, they have this thing called home fresh
    0:04:16 and it comes in a box and everything’s in it.
    0:04:20 They have very good meals in that box.
    0:04:21 – Here’s the challenge.
    0:04:24 I’ve got three kids and they’re such picky eaters.
    0:04:27 I feel like I can’t get, there’s no rest.
    0:04:30 The Venn diagram of foods that everybody in my family
    0:04:34 will eat is a possibly tiny overlapping zone.
    0:04:38 And I don’t think a home fresh finds the zone.
    0:04:39 But we’ll see.
    0:04:41 I’ll look into it.
    0:04:44 – Just go to Costco and get the dollar half hot dog.
    0:04:44 That’s good enough.
    0:04:46 – Exactly, that’s the over, you found it.
    0:04:50 That is the overlapping part of the Venn diagram, hot dogs.
    0:04:51 – I’ve had four children.
    0:04:54 I know how that Venn diagram works.
    0:04:56 – How old are your kids now, guys?
    0:04:58 – They are no longer kids.
    0:05:03 They’re 19, 23, 30 and 32 or something like that.
    0:05:08 I’m a grandfather, I’m a new grandfather.
    0:05:09 – Congratulations.
    0:05:11 How many grandkids do you have?
    0:05:12 – One that I know of.
    0:05:17 – One that you know of, a baby or a toddler?
    0:05:20 – Three months old.
    0:05:22 – Congratulations, you’re a new grandfather.
    0:05:25 That’s a huge deal.
    0:05:28 – So I saw some interviews of you
    0:05:30 and you were complimenting this podcast
    0:05:32 about how many questions he had
    0:05:33 and how he was jumping around
    0:05:36 and I’m gonna set the new standard for you today, okay?
    0:05:40 – Oh, I love it, I love it.
    0:05:43 I’ve had some competitiveness in you guys, I like that.
    0:05:47 – You can ask Madison, I’m a very competitive person
    0:05:50 and to answer the question that I asked you,
    0:05:53 I’m lousy at surfing, but I love to do it.
    0:05:56 So that’s kind of where I’m at.
    0:05:57 First question for you is,
    0:06:00 you know that person in your book
    0:06:02 where you had a conversation
    0:06:04 and you told her that her boyfriend
    0:06:05 wasn’t good enough for you?
    0:06:07 – Yes, I do.
    0:06:08 – Are they still married?
    0:06:10 – They’re still married, they have children,
    0:06:13 they’re, as far as I can tell, happily married
    0:06:18 and I did get a text from her when she received the book
    0:06:21 and I hadn’t warned her about the story.
    0:06:26 So we are still friends and everything’s copacetic
    0:06:28 and she actually did not remember
    0:06:31 that number thing happening.
    0:06:34 She didn’t, and I think I was very relieved
    0:06:36 that she didn’t remember.
    0:06:39 – So you’re telling me that to this day,
    0:06:42 you don’t know if she was offended by that question?
    0:06:44 – Correct, and at this point,
    0:06:46 I don’t think she knows if she was offended.
    0:06:48 I mean, this is something that’s true.
    0:06:52 I do think this is a very vivid thing about conversation.
    0:06:54 It’s easy to get hung up on things
    0:06:57 when you feel like they don’t go well,
    0:06:59 but you have no idea how other people
    0:07:01 are experiencing a conversation
    0:07:04 or how they’re experiencing you
    0:07:06 and truly we had an amazing friendship.
    0:07:07 It was a very close friend of mine.
    0:07:10 Honestly, I did that to a lot of my friends.
    0:07:11 At that point in my life,
    0:07:12 I felt like it was very much my place
    0:07:15 to be protective of all of my girlfriends
    0:07:17 who I thought were amazing
    0:07:20 and no partner was worthy of them.
    0:07:24 And so I just went around sprinkling feedback left and right
    0:07:26 of like, this guy’s not good enough for you.
    0:07:28 And now in retrospect, I’m like,
    0:07:29 well, that was an interesting phase of life,
    0:07:33 maybe not my place to be tossing that around so casually,
    0:07:36 but learning how other people experience
    0:07:38 a conversation like that is very enlightening.
    0:07:41 I mean, in the moment, you really have no idea
    0:07:45 how people hear you or what they’re learning from you.
    0:07:48 – Maybe Madison should introduce you to her boyfriend
    0:07:51 so you can check him out for her.
    0:07:54 – Now she’s gonna be scared that I’ll write
    0:07:56 about their relationship in a book
    0:07:58 and have it be in print for the all the time.
    0:08:00 – Well, the test will be,
    0:08:02 if you don’t like Madison’s boyfriend,
    0:08:07 then she’ll probably be living happily ever after with him
    0:08:09 based on her track record.
    0:08:11 – That’s right, if there is one clear take away from this,
    0:08:13 it’s that my instincts are not good
    0:08:15 about other people’s love lives.
    0:08:17 (laughing)
    0:08:20 – I can hardly wait till your daughter’s have boyfriends.
    0:08:21 Oh, that’s-
    0:08:22 – I know, I know.
    0:08:25 I have two boys and a little girl.
    0:08:27 – Oh, you only have one girl.
    0:08:28 – There are only nine, seven and five,
    0:08:31 but it does take a lot of self-control for me
    0:08:34 as like a psychologist and just,
    0:08:35 I’m obsessed with relationships
    0:08:37 so to not ask them every day,
    0:08:38 like what’s going on?
    0:08:39 Who’s gonna crush on who?
    0:08:40 What’s got how you feelin’?
    0:08:41 What’s new?
    0:08:43 (laughing)
    0:08:45 Too soon, I just want the break.
    0:08:47 – Is she still licking your nose?
    0:08:49 – Oh, you know what, guys?
    0:08:52 She does, she’s in kindergarten now
    0:08:54 and she is very funny.
    0:08:57 She’s very silly and she’s so proud
    0:09:01 that she is the first story in the book, her name’s Charlotte.
    0:09:05 And she knows that story
    0:09:06 and she doesn’t remember it
    0:09:09 because when it happened, she was a baby, she was one.
    0:09:10 But I’ve retold it to her
    0:09:12 and now she hears from other people,
    0:09:15 “Hey, this is the story so cute at the beginning of the book.”
    0:09:20 And so she’s very proud that she is, you know, this book star.
    0:09:22 And now it’s this inside joke between the two of us.
    0:09:23 Just last night, I was like,
    0:09:25 “Charlotte, my book’s coming out tomorrow.”
    0:09:27 And she came right over and she goes,
    0:09:28 “I lick you.”
    0:09:30 And licked me right on the nose.
    0:09:31 (laughing)
    0:09:32 So cute.
    0:09:36 Even the boys, even the boys now say, “I lick you.”
    0:09:38 It’s a family, ongoing family joke.
    0:09:42 – I guess that’s what social distancing is
    0:09:44 in the Brooks family.
    0:09:47 – Yeah, there’s no distance in a family like ours.
    0:09:48 Oh my God.
    0:09:52 – So I happen to notice that
    0:09:54 there’s a lot of licking stories in your book
    0:09:57 because you talk about Carrie Fisher’s dog
    0:10:01 licking her hand during Terry Gross’ interview.
    0:10:03 So there’s some licking thing.
    0:10:04 – There is a licking theme.
    0:10:07 I thought about it as I was writing it
    0:10:10 and I was like, “Why is there so much licking in this book?
    0:10:13 “What do I kind of invite to my giving to people?
    0:10:14 “You’re so right.
    0:10:16 “What a great reader you are, guy.
    0:10:17 “It’s true.”
    0:10:22 – Well, I mean, something like that sticks out.
    0:10:27 – Okay, so now shifting gears a little bit.
    0:10:32 Your course at Harvard is Hall to Talk Gooder, right?
    0:10:34 – That’s right.
    0:10:36 – So I want to know if you are inspired
    0:10:39 by the Think Different campaign of Apple
    0:10:43 where you purposely do something dramatically incorrect.
    0:10:45 – I wasn’t directly thinking of Apple,
    0:10:47 but I do think the principle is the same.
    0:10:50 My intention was just be different.
    0:10:51 I mean, to be different.
    0:10:53 And at Harvard, to be different,
    0:10:55 it doesn’t require much levity.
    0:11:01 There’s not a lot of silliness.
    0:11:03 I think it’s a weakness of ours.
    0:11:06 And I really wanted to make that point in the course title
    0:11:08 when it’s sitting in the course catalog
    0:11:12 alongside democracy in America
    0:11:14 and global capitalism.
    0:11:17 And then you get to this course as how to talk gooder.
    0:11:18 It jumps out at you.
    0:11:20 It’s very different.
    0:11:22 There’s a double meaning too
    0:11:24 because there’s a theme of kindness in the book.
    0:11:26 Gooder is in the sense of like,
    0:11:29 what does it mean to be a good person?
    0:11:31 But also better in all the ways
    0:11:33 we’re hoping to be better communicators.
    0:11:39 – Maybe Susan Acker and Naomi Bagadonuts
    0:11:42 are gonna rename their course because of that, right?
    0:11:45 ‘Cause they have a really plain name.
    0:11:46 – That’s right.
    0:11:49 Yes, their course is called Humor Serious Business.
    0:11:51 Their book is Humor Seriously.
    0:11:53 I visited their course.
    0:11:54 They have visited my course.
    0:11:58 Actually, Naomi visits my course every time I teach it.
    0:11:59 She’s such a talented teacher.
    0:12:02 She comes during our Levity module and talk.
    0:12:04 So we’re very much on the same page.
    0:12:05 Maybe I can get them to rename their course,
    0:12:07 something even sillier.
    0:12:11 – Okay, I notice, you’re gonna figure out
    0:12:13 that I notice the damnedest things,
    0:12:16 but I notice that when you introduce Naomi,
    0:12:19 you introduced her as a comedian,
    0:12:20 not as a professor.
    0:12:22 Was that an inside joke?
    0:12:25 Or did you have a lousy copy editor who didn’t check?
    0:12:26 – You know what?
    0:12:27 Probably both.
    0:12:28 No, I’m kidding.
    0:12:32 Actually, the way that I introduce people in the book
    0:12:34 is the way that I think of them in my mind,
    0:12:36 how I categorize them.
    0:12:38 So Naomi’s a professor,
    0:12:40 but she’s not a behavioral scientist
    0:12:44 in the way that so many of my professor friends are scientists.
    0:12:47 In my mind, the value add of my relationship with Naomi
    0:12:49 is that she is really a practitioner.
    0:12:50 She’s out there in the world.
    0:12:52 She’s teaching humor to people
    0:12:54 who have been incarcerated in Palo Alto.
    0:12:56 She’s teaching humor workshops.
    0:12:57 She’s out there.
    0:13:00 She’s consulting with so many companies.
    0:13:02 And that’s a different role.
    0:13:04 That’s a different job than what so many
    0:13:07 of my behavioral science research friends are doing.
    0:13:11 – I can just see Katie Milkman and Angela Duckworth
    0:13:15 in a prison in Philadelphia teaching the grit.
    0:13:17 Let me teach you grit, sir.
    0:13:18 – Hey, they would do it.
    0:13:20 I mean, if you could get a large scale,
    0:13:22 large enough scale prison,
    0:13:24 they would, I’m sure love to get in there,
    0:13:27 especially Angela and Katie.
    0:13:28 They’re amazing.
    0:13:31 – They’re gonna give a whole new meaning
    0:13:33 to the Milkman delivers.
    0:13:35 – Exactly.
    0:13:37 One of the studies that I talk about in the book
    0:13:39 is that about parole hearings.
    0:13:41 So we’ve had the lick theme.
    0:13:44 Now we’re picking up on a prison theme.
    0:13:48 We moved on from licking to prison.
    0:13:50 It’s showing we’re going up the pyramid.
    0:13:51 – That’s right.
    0:13:53 Yeah, exactly.
    0:13:54 Reaper and Reaper.
    0:14:03 – Shifting gears again.
    0:14:08 Do you think people can have a conversation with an LLM?
    0:14:11 – It’s a good question.
    0:14:12 I think it goes back to this question
    0:14:15 of what are your goals in conversation?
    0:14:20 I think an LLM, an AI, a chatbot are quite good
    0:14:25 at fulfilling some of our conversational needs.
    0:14:30 It’s why there’s such great promise in companionship
    0:14:32 through AI or through LLMs
    0:14:35 because they can help us not feel alone.
    0:14:37 They can help us have fun.
    0:14:39 They’re an incredible sounding board.
    0:14:41 They help feed good ideas to us.
    0:14:46 There’s so many needs we have that a non-human entity
    0:14:47 can fulfill.
    0:14:51 Here’s where I get a little bit worried.
    0:14:52 I mean, there’s a lot that’s worrisome,
    0:14:55 but one of the things that I’ve been thinking about
    0:15:00 is something that humans struggle with in conversation
    0:15:03 is getting past our own self-centeredness,
    0:15:07 our own egocentrism that we focus so singularly
    0:15:10 and naturally on our own point of view.
    0:15:13 In the book, we take this position of a kind conversation,
    0:15:16 a good conversation that relentlessly pushes themselves
    0:15:18 to think about the other person’s perspective,
    0:15:20 not just think about it, but ask about it.
    0:15:22 Ask questions, learn as much as you can
    0:15:25 about what’s really in the other person’s mind
    0:15:26 because we’re bad at guessing, right?
    0:15:30 We’re bad at knowing what other people are thinking about.
    0:15:32 So we have these egocentric tendencies,
    0:15:34 we like talking about ourselves,
    0:15:36 we like thinking about our own perspective,
    0:15:38 and we have to really work hard to get over that.
    0:15:43 When you’re interacting with a non-human entity,
    0:15:46 you don’t need to do that at all.
    0:15:48 The whole point is to get the entity
    0:15:51 to fulfill your needs as much as possible.
    0:15:54 It’s completely self-centered in a way.
    0:15:56 You don’t need to relentlessly push yourself
    0:15:58 to understand its perspective.
    0:16:00 It doesn’t really have a perspective.
    0:16:01 It doesn’t have needs.
    0:16:06 A chatbot, an AI, an LLM, it doesn’t have needs
    0:16:08 and it doesn’t have desires.
    0:16:11 And so what I worry about is,
    0:16:16 if we are interacting with non-human entities too much,
    0:16:20 is it training us to be even more selfish
    0:16:21 than we already are?
    0:16:28 – That’s a scary thought, I hope that Sam Altman
    0:16:31 and the people at OpenAI read this book
    0:16:35 because it might improve their agent aspect
    0:16:37 of LLMs, right?
    0:16:37 – For sure.
    0:16:39 Some companies have come over the years,
    0:16:41 many people and companies have come to me
    0:16:44 looking for advice and guidance and consulting
    0:16:47 about how to make their bots more human-like.
    0:16:50 How can we make them better at conversation?
    0:16:53 At first, I was flattered and excited to engage with them
    0:16:54 and then I sort of stopped
    0:16:58 because I’m just not sure that that’s what that means
    0:17:00 and if that’s actually helpful to us at this point.
    0:17:04 – There’s a lot of upside there
    0:17:08 when every voicemail system says press one for tech support,
    0:17:11 press two for sales, press three, four, executive directory,
    0:17:14 press four if you wanna get this menu over again,
    0:17:16 I’m sure you can improve that.
    0:17:18 – I definitely can, I definitely can.
    0:17:20 I would be interested to hear,
    0:17:23 so for people who are working on LLMs and bots,
    0:17:25 I would love to hear what they think of the insights
    0:17:28 and talk and how much of it is translatable
    0:17:30 to bot development and how much is not, right?
    0:17:33 Like how much is uniquely, the human mind
    0:17:36 is uniquely positioned to do.
    0:17:40 – Do you think that you could use an LLM
    0:17:44 to train you to be a better conversationalist?
    0:17:47 You could prompt it with what are some great topics
    0:17:50 because you say it’s okay to create a topic list, right?
    0:17:53 – So this is where LLMs can be so helpful.
    0:17:56 I think as a training mechanism for a human
    0:17:58 to become a better conversationalist for sure.
    0:18:01 In fact, before LLMs became a thing,
    0:18:05 I developed a case at HBS with a company called Summersion,
    0:18:06 which is essentially this,
    0:18:09 they created like simulated conversation partners
    0:18:13 so that my students could practice interacting
    0:18:15 with people that are different from who they would normally
    0:18:18 encounter in their normal lives and get like lots of reps.
    0:18:20 You just talk, talk, talk, talk, talk, talk
    0:18:22 and get lots of different responses
    0:18:24 from this simulated conversation partner.
    0:18:26 So an LLM could do a lot of things.
    0:18:29 My sister recently asked ChatGPT like,
    0:18:32 “Hey, I want to have better conversations with my parents.”
    0:18:35 So then she fed information about our parents.
    0:18:38 She was like, “What would people who live in upstate New York
    0:18:41 “in the Finger Lakes who have nine grandchildren
    0:18:44 “or 72 years old, what would they want
    0:18:48 “their adult children to ask them about?”
    0:18:49 And it gave great ideas.
    0:18:52 It was a great way to brainstorm topics
    0:18:55 because the LLM has a lot more data about people
    0:18:57 that meet those demographic characteristics
    0:18:59 than we might guess.
    0:19:02 Then like we as young, you know, 40-somethings
    0:19:04 could guess that they would want to talk about.
    0:19:07 So seeding topics, brainstorming topics is a great idea.
    0:19:11 Simulating conversation and practicing, great.
    0:19:14 Pushing us to become more kind, I’m not so sure.
    0:19:19 – I think you should ask your parents,
    0:19:21 vis-a-vis your grandchildren,
    0:19:26 have you created a generation skipping trust for my kids?
    0:19:28 That’s the most important question
    0:19:31 you could ask your parents for your grandchildren.
    0:19:34 – I’m adding that to my topic, let’s write now, guy.
    0:19:36 – Generation skipping trust
    0:19:39 so that they don’t give you something, you pay tax,
    0:19:41 you give it to your kids, they pay tax.
    0:19:45 It skips your generation, go straight to their generation.
    0:19:47 – That’s amazing, that’s amazing.
    0:19:50 – I went to law school for two weeks and dropped out.
    0:19:52 So, you know, I picked that right up.
    0:19:53 – The only thing that you learned
    0:19:56 during your two weeks of law school about generation skipping
    0:19:58 trust? – It was so valuable.
    0:20:00 Imagine if I had stayed two years, my God.
    0:20:03 – Imagine, imagine, imagine the hacks.
    0:20:06 – I’d be teaching at Harvard Law School,
    0:20:07 we would be colleagues.
    0:20:11 – But you can’t surf here, guy.
    0:20:14 You can’t surf, I mean, I guess you can in the summer,
    0:20:15 but not in the winter.
    0:20:18 – I love a good acronym.
    0:20:23 And your acronym is TOC, T-A-L-K.
    0:20:26 So, please explain what TOC stands for.
    0:20:28 – Can I tell you through this book,
    0:20:30 I’ve already learned that acronyms are very polarizing.
    0:20:32 Some people really, really love them
    0:20:35 and find them to be so helpful to help them remember stuff.
    0:20:36 Other people are very like,
    0:20:39 come from a very anti-acronym place.
    0:20:41 – I’m pro-acronym.
    0:20:42 – I’m also pro-acronym.
    0:20:44 I think really good mnemonic device to help remember.
    0:20:47 But I hope this acronym, people find very helpful.
    0:20:50 T stands for topics.
    0:20:53 A stands for asking questions.
    0:20:58 L is for levity and K is for kindness.
    0:20:59 – And so those four things
    0:21:02 are the foundation of great conversation.
    0:21:04 – Yeah, the ambition.
    0:21:06 And I think, I hope it delivers on this promise,
    0:21:11 is that it provides a comprehensive landscape
    0:21:15 of conversation where, so lots of prior work,
    0:21:18 I mean, if you focus only on persuasion
    0:21:22 or you focus only on influence or you only on negotiation,
    0:21:24 only on relationship development,
    0:21:27 the problem is that you’re missing out on how those things,
    0:21:30 those goals trade off with other important goals,
    0:21:33 like having fun or maintaining privacy
    0:21:36 or like just liking to be with people.
    0:21:39 And so it’s overly narrow view.
    0:21:41 The promise of this acronym in this book
    0:21:42 is a broader perspective.
    0:21:45 Like, let’s consider all of the things
    0:21:47 that we want as humans at one time
    0:21:50 and then come up with these four reminders,
    0:21:52 these four guardrails that are gonna help us
    0:21:54 do all of the things better.
    0:21:57 – May I make a suggestion with your acronym?
    0:21:59 – How dare you?
    0:22:00 How dare you guys?
    0:22:02 Yes, I can’t wait to, I can’t wait.
    0:22:03 – What do you mean, I read in your book,
    0:22:05 it’s okay to bring up sensitive questions.
    0:22:08 – I can’t change it at this point, Guy,
    0:22:10 but yes, I’m all ears, I can’t wait to hear.
    0:22:14 – Okay, so I think you should change
    0:22:18 ASKING, ING, to ASKS,
    0:22:23 because then all elements of your acronyms will be nouns.
    0:22:26 – You’re right, it is a jarring gerund.
    0:22:28 It is a jarring change of grammar.
    0:22:33 But here’s the thing, when I hear the word ASKS, the noun,
    0:22:36 I think when people use the word ASK as a noun,
    0:22:40 they’re usually talking about, I have a big ASK.
    0:22:43 And there they mean, I’m asking for something.
    0:22:47 I’m gonna ask you to give them something that serves me,
    0:22:51 which is totally against the spirit of ASKING in this book,
    0:22:54 which is like, no, you’re ASKING for the sake
    0:22:58 of information exchange and learning.
    0:22:59 – But I would make the case
    0:23:02 that as a Harvard Business School professor,
    0:23:05 and someone who’s already broken the bounds
    0:23:07 of good grammar with gooder,
    0:23:12 you can change the meaning of ASK to just be a synonym
    0:23:16 for questions, for generating conversation.
    0:23:19 – You know what, I was talking to Patrick McGinnis
    0:23:21 the other day, he was interviewing me about the book.
    0:23:22 He has this great podcast.
    0:23:25 He’s the guy who invented the word FOMO,
    0:23:26 fear of missing out.
    0:23:29 And we had like a jolly good bonding moment
    0:23:33 because of our shared experience of inventing acronyms.
    0:23:37 I like this guy, I like the idea of the lofty goal
    0:23:40 of me changing the whole meaning of the word ASK.
    0:23:42 I like this, I like the ambition of it.
    0:23:43 I’m gonna keep it in mind.
    0:23:45 I will tell people that this is your vote.
    0:23:47 When I say A is for ASKING and I’ll say,
    0:23:50 and guy, Kawasaki told me it should be ASK.
    0:23:56 – It’s my OCD Chicago manual of style upbringing.
    0:23:57 What can I say?
    0:23:58 – I applaud you.
    0:24:02 I applaud your OCD grammatical ways, thank you.
    0:24:06 – We should ask Angela Duckworth what she thinks.
    0:24:07 – Let’s call her in.
    0:24:08 I can call her right now.
    0:24:10 You want to dial in, where you’re in?
    0:24:12 (laughing)
    0:24:14 Angela, what do you think?
    0:24:17 – So, you know, I want people to read the book.
    0:24:19 So I’m not gonna force you to explain
    0:24:20 each of the four things,
    0:24:25 but I noticed that you busted some myths in this book.
    0:24:29 So I’m gonna mention what I think four myths you bust
    0:24:32 and how and why you busted them, all right?
    0:24:35 So first of all, myth number one is small talk
    0:24:37 is a waste of time.
    0:24:39 Tell me why that’s wrong.
    0:24:40 – It is wrong.
    0:24:42 Everybody feels like it’s a waste of time
    0:24:44 because it’s so unpleasant.
    0:24:46 Everybody knows that once you’re there,
    0:24:48 it’s shallow, meaningless, empty,
    0:24:50 start to have these alarm bells go off like,
    0:24:52 “Oh, we’re not doing conversation right.
    0:24:53 “We gotta get to the real stuff.
    0:24:55 “We gotta get to the productive stuff,
    0:24:56 “the meaningful stuff.”
    0:24:58 We all know that feeling.
    0:25:01 The problem isn’t with small talk itself,
    0:25:04 it’s that we get stuck in it for too long.
    0:25:06 Small talk is a very important social ritual.
    0:25:08 It’s where conversation has to start,
    0:25:10 especially between strangers
    0:25:12 or people who don’t know each other that well
    0:25:14 or who haven’t seen each other in a while.
    0:25:17 It’s a very well-worn social ritual.
    0:25:19 That’s how we start conversations.
    0:25:21 The point though is to use it as a place
    0:25:24 to search for better stuff.
    0:25:27 And ideally to search for better stuff quickly.
    0:25:29 I wanna hear people talking about surfing
    0:25:31 within the first four turns of a conversation
    0:25:33 and how much they love it
    0:25:36 and how their kids are surfing down the snow
    0:25:38 rather than like, “Oh yeah, it’s cold.
    0:25:40 “Oh yeah, I don’t like the cold.
    0:25:42 “It’s warmer here in California.”
    0:25:44 And a lot of conversations do stay
    0:25:48 in that very mundane world for much too long.
    0:25:51 So the trick is just making sure you look for the doorknobs
    0:25:53 to better or more interesting rooms
    0:25:55 and get the courage to go through those doorways,
    0:25:57 go to better places.
    0:26:00 – Is there a rule of thumb about when to make the switch?
    0:26:02 – It would be weird if right away
    0:26:06 I had been like, “Tell me about your mother.”
    0:26:08 That’s the best jarring.
    0:26:10 It’s almost as jarring as the asking Jaron
    0:26:13 in the middle of the talk, across the–
    0:26:17 – Well, we got from weather in Boston to licking dogs
    0:26:19 and licking noses pretty quick, right?
    0:26:21 – Yeah, I think both of us are people
    0:26:25 who are very hungry to move past small talk.
    0:26:28 But I don’t, but we don’t dread it, right?
    0:26:29 Like you have to do it.
    0:26:31 You just have, it’s the starting place.
    0:26:34 It’s the launch pad to go somewhere else.
    0:26:36 And some people have developed the skill
    0:26:39 of moving away from it more quickly and more smoothly.
    0:26:41 And everybody can develop that skill.
    0:26:43 – Okay, myth number two.
    0:26:46 I think a lot of people would say it’s kind of tacky
    0:26:50 to prepare a topic list in advance of meeting people
    0:26:52 that you shouldn’t pre-plan the topics
    0:26:53 you’re gonna talk about.
    0:26:55 So bust this myth.
    0:26:57 – I’m so happy to bust this myth.
    0:26:59 I love the word tacky.
    0:27:02 When we survey people, when we say,
    0:27:05 imagine prepping topics before a conversation,
    0:27:07 especially with someone you know well,
    0:27:10 like your spouse or your lover.
    0:27:11 Yeah, look at your topic list.
    0:27:13 Let’s go.
    0:27:14 I love it.
    0:27:17 So a lot of people are very averse to this idea.
    0:27:19 They’re like, I shouldn’t have to brainstorm topics.
    0:27:21 I’m gonna know what to talk about
    0:27:22 once I’m in a conversation,
    0:27:25 especially with people that I know well.
    0:27:27 In the experience of it, in reality,
    0:27:29 once you get to a conversation,
    0:27:33 having thought ahead about it is incredibly helpful,
    0:27:35 not just for a podcast interview or for a work meeting
    0:27:38 where you’ve brainstormed an agenda,
    0:27:41 but even for conversations with people that you love
    0:27:43 and know well and see every day
    0:27:45 because it forces you to just think about them.
    0:27:47 It’s a perspective taking nudge where you’re like,
    0:27:50 oh yeah, what’s going on in my partner’s life?
    0:27:52 What do I really need to remember to ask them?
    0:27:55 It’s a way to show them that you care
    0:27:58 and that it helps you remember to raise the topics
    0:28:00 that you should be raising with them.
    0:28:02 Make things more enjoyable, less anxiety-inducing,
    0:28:04 smoother, more productive, all the good things.
    0:28:06 – You know, there is no one who is more positive
    0:28:10 about AI than Guy, and I often do this,
    0:28:13 and I think AI is smarter than me.
    0:28:14 There’s no doubt in my mind,
    0:28:16 chat, GPT is smarter than me.
    0:28:17 – Oh yeah, smarter than all of us for sure.
    0:28:21 I mean, my definition, it’s like as smart as the masses,
    0:28:22 right?
    0:28:22 With the crowd.
    0:28:27 – But one thing AI absolutely cannot do that I can do
    0:28:31 is come up with questions and topics for a podcast.
    0:28:33 Because before every podcast, I usually ask,
    0:28:38 what should I ask Katie Milken or Angela Duckworth
    0:28:39 or Steve Wolfram?
    0:28:41 And they always come up with really boring questions
    0:28:44 like what was the most exciting part of your career?
    0:28:46 What do you look forward to, et cetera, et cetera.
    0:28:50 And if there is ever a day where I ask,
    0:28:54 what should I ask Allison in a podcast?
    0:28:58 And the LLM says, Guy, ask her why she talks so much
    0:29:02 about licking, that’s the day that AI has arrived.
    0:29:04 – Why do you think that is?
    0:29:05 Do you think it’s a unique skill set
    0:29:07 that you have as an individual
    0:29:09 or do you think it’s a broader human ability?
    0:29:13 We’re just better at knowing or anticipating
    0:29:16 what will be fun and interesting to talk about
    0:29:17 with other people.
    0:29:20 – I think it’s because using your vernacular
    0:29:24 of system one and system two, I’m about system 10.
    0:29:25 That’s why.
    0:29:28 – Say more.
    0:29:29 – Okay, wait, more mids.
    0:29:31 I got two more mids.
    0:29:32 – Oh yeah, that’s right, keep going.
    0:29:33 Sorry, don’t let me derail you.
    0:29:37 – So myth number three,
    0:29:40 it’s bad to ask too many questions.
    0:29:43 – Oh, I love busting this myth.
    0:29:45 Everybody can think of a person.
    0:29:47 They can think of a person or think of a conversation
    0:29:50 where they were annoyed that somebody asked too many questions.
    0:29:52 It felt like an interrogation.
    0:29:55 That memory is so salient that it leads us to believe
    0:29:57 that you can ask too many questions
    0:30:01 when in most contexts, for most people,
    0:30:04 it’s either impossible to ask too many questions
    0:30:06 or the number of questions that you would need to ask
    0:30:09 to get to that annoying point is so extremely high
    0:30:12 that you almost can’t possibly get there.
    0:30:15 This is true particularly in cooperative conversations
    0:30:18 where you’re collaborating or you’re on a date
    0:30:20 or you’re just there to have fun, connect with people.
    0:30:23 That’s a big chunk of the conversations we have in our life,
    0:30:26 our cooperative conversations.
    0:30:30 And even in competitive, conflictual conversations
    0:30:31 where you need to negotiate something.
    0:30:36 – My fourth myth is that it is bad to ask sensitive questions.
    0:30:42 – It’s bad to not ask sensitive questions.
    0:30:43 It’s terribly bad.
    0:30:46 It means you’re going to get stuck in small talk world,
    0:30:50 mundane, meaningless, unproductive world forever.
    0:30:54 We have all kinds of fears about asking sensitive questions.
    0:30:55 We don’t want to hurt people’s feelings.
    0:30:56 We don’t want to seem rude.
    0:30:58 We don’t want to seem intrusive.
    0:31:00 We don’t want to seem incompetent, right?
    0:31:04 Sometimes we worry that asking a question will make it look
    0:31:06 like we should already know the answer to it.
    0:31:09 In truth, asking sensitive questions
    0:31:13 is the most direct pathway to connection, to learning,
    0:31:17 to teaching, to, ironically, even to privacy, right?
    0:31:20 Because only by asking a sensitive question,
    0:31:22 can you learn where somebody’s personal boundary is
    0:31:23 where they can say, actually,
    0:31:25 I’m not comfortable talking about that.
    0:31:27 Otherwise, you’ll never find it.
    0:31:30 And you can never learn how to, you know,
    0:31:31 where are their boundaries?
    0:31:32 What are they comfortable talking about
    0:31:33 and not talking about?
    0:31:36 So, yes, we need to ask more sensitive questions.
    0:31:38 – So how much do you make
    0:31:40 as a Harvard Business School professor?
    0:31:41 – That’s such a good question.
    0:31:43 (laughing)
    0:31:44 – Love it.
    0:31:45 I’ll tell you what, book deals help,
    0:31:48 book deals help you earn a lot more.
    0:31:49 And I think that’s why a lot of professors
    0:31:52 are writing these trade books.
    0:31:54 – I need a number here.
    0:31:56 (laughing)
    0:31:58 – I’m still not tenured.
    0:31:59 I’m a junior faculty member.
    0:32:01 So I actually don’t know
    0:32:03 what my tenured faculty colleagues make.
    0:32:06 – I’m asking you, not your tenured faculty colleagues.
    0:32:11 You think you can just avoid my sensitive questions.
    0:32:12 – But I, can I be real with you?
    0:32:17 My husband is a financial advisor.
    0:32:20 And I don’t even know how much money I need.
    0:32:21 – Okay, okay.
    0:32:24 – The money flows, the money flows to my husband.
    0:32:26 – I learned from your book
    0:32:29 that I learned from your book
    0:32:32 that you have to learn when to switch topics.
    0:32:33 – I actually want to answer your question.
    0:32:35 I think the sincere answer to your question
    0:32:37 is more than enough.
    0:32:40 Too much, I mean too much.
    0:32:41 – Speaking of tactics,
    0:32:46 so do you think it’s better to switch too many topics
    0:32:51 or what’s worse, too fast or too slow switching?
    0:32:52 – We know this.
    0:32:53 I know this answer,
    0:32:56 not just based on my personal hunches or preferences.
    0:32:58 Of course, I love rapid topic switching.
    0:33:00 I think because I have an ADHD,
    0:33:02 sort of an inattentive brain,
    0:33:04 I think you do too.
    0:33:06 But we also actually have data on this.
    0:33:10 This is a huge data set that was collected from BetterUp,
    0:33:12 which it’s just amazing conversations.
    0:33:14 After their conversations,
    0:33:16 like hundreds of thousands of conversations,
    0:33:17 they ask people,
    0:33:20 did you cover the right amount of topics?
    0:33:21 And most people say, yeah,
    0:33:24 I think we covered about the right amount of topics.
    0:33:26 But of all the people who said no,
    0:33:28 we did not cover the right amount of topics,
    0:33:30 people are much more likely to say
    0:33:34 that they covered too few than too many.
    0:33:38 So the most common mistake is moving too slowly
    0:33:39 through topics.
    0:33:42 And we see that when we manipulate the speed
    0:33:44 with which people move from one thing to the next.
    0:33:46 So we’ve run experiments where we tell people,
    0:33:48 move faster.
    0:33:49 As soon as this thing starts to lag,
    0:33:51 we want you to move to something else.
    0:33:54 And those conversations are much more enjoyable.
    0:33:55 – Okay.
    0:33:56 So now let me ask you.
    0:34:00 So what about when people who are hesitant to ask
    0:34:03 sensitive questions start with the question
    0:34:06 like I did, may I ask you a sensitive question?
    0:34:08 Do you think that is a cop out?
    0:34:10 Do you think that is a waste of time?
    0:34:13 Or do you think that is a good social grace?
    0:34:15 – I think it’s a nice sign posting.
    0:34:16 It’s a little bit of a warning,
    0:34:19 like, hey, something’s coming, pay attention.
    0:34:23 It at least gives the veneer or the veil of politeness
    0:34:24 and caring, right?
    0:34:26 You’re also saying,
    0:34:27 I’m gonna ask you something sensitive.
    0:34:30 If you don’t want to answer it, I understand, right?
    0:34:32 That’s a nice disclaimer.
    0:34:33 The same is true when you switch topics.
    0:34:35 You can note, like, is it okay
    0:34:37 if I take a hard left turn here?
    0:34:39 Is it okay if we smoke bomb and move to something else?
    0:34:42 It’s almost like you’re asking permission of your partner,
    0:34:45 even though they’re sort of required to say yes,
    0:34:47 because they don’t know what’s coming next.
    0:34:49 But yes, I think it’s lovely.
    0:34:51 Or you can just do it, just ask.
    0:34:53 How much money do you make, guy?
    0:34:56 You know, like just go for it and see how people run.
    0:34:58 – My wife is my financial planner.
    0:34:59 I really don’t know.
    0:35:01 And everything is a direct deposit.
    0:35:02 I don’t check my balance.
    0:35:05 But can I tell you a really funny story?
    0:35:06 – Yes.
    0:35:07 – You can use this story.
    0:35:09 – I think I get to decide if it’s funny,
    0:35:11 but okay, go ahead.
    0:35:13 – I guarantee you when I tell you something is funny,
    0:35:14 it’s funny, all right?
    0:35:16 So when I was at Apple,
    0:35:18 I used to work with some of the executives
    0:35:22 in outside companies who are Macintosh users.
    0:35:26 And one very famous person was a woman named Sandra Kurtzig.
    0:35:29 She started a computer company called Ask Computing.
    0:35:32 It was manufacturing software.
    0:35:34 She was the first woman in Silicon Valley
    0:35:35 to take a company public.
    0:35:37 So she was very, very rich.
    0:35:40 And she had this Ferrari Testerosa,
    0:35:43 which I love Ferraris, not that I have her own one.
    0:35:45 So anyway, she reaches out to us.
    0:35:48 She says, I’m having problems with my Macintosh.
    0:35:51 So Guy goes over to her house
    0:35:53 to help her with her Macintosh, right?
    0:35:56 And she shakes the mouse and the screen wakes up.
    0:36:00 And the window in the front is Quicken.
    0:36:02 And I know how to use Quicken.
    0:36:04 I know exactly where the current balance
    0:36:05 of your checkbook is.
    0:36:07 And as soon as she wakes up Quicken,
    0:36:10 I look down and it’s like, holy shit,
    0:36:13 she has a quarter million dollars in her checking account.
    0:36:14 And ever since that day,
    0:36:16 it’s been one of my goals
    0:36:19 to have a quarter million dollars in your checking account.
    0:36:21 And I have achieved that goal, Allison.
    0:36:23 – Yes, Guy, yes.
    0:36:28 I love that your eyes darted so quickly to the balance.
    0:36:31 It’s like, it’s such a lovely measure
    0:36:32 of your inner curiosity.
    0:36:34 I love it so much.
    0:36:35 And you’ve done it.
    0:36:36 Is that it?
    0:36:37 You can drop the mic.
    0:36:40 You’ve achieved all the things you wanted in life.
    0:36:44 Quicken, you’re 250 in your checking account.
    0:36:48 – Tell that to your husband.
    0:36:51 So if you ever need help with your Macintosh,
    0:36:53 be sure you have quick books closed
    0:36:57 when you call me to your house or I will know.
    0:36:58 – I love it.
    0:36:58 I love it.
    0:37:02 I hope you’re not tracking my screen right now.
    0:37:03 We’re talking to that.
    0:37:06 I’m like, oh God, what does he have access to on my computer?
    0:37:07 What do you want?
    0:37:08 What is this?
    0:37:09 What does this even do?
    0:37:10 – It’s too late.
    0:37:12 I already posted it on threads.
    0:37:13 How much money you have?
    0:37:18 Clayton Christensen is up there laughing.
    0:37:21 And I was like, Guy, you’re really taking it to her.
    0:37:22 Go, Guy, go.
    0:37:24 – I’m just cheering you on.
    0:37:26 I can’t decide if he’s what would be cheering you on
    0:37:27 more or cheering me on more.
    0:37:29 I think he’s cheering us on together.
    0:37:32 – He is saying, I’m gonna write a new book
    0:37:34 called “A Conversationalist Dilemma.”
    0:37:38 – Exactly, when you love old people so much,
    0:37:39 what do you do?
    0:37:43 – So, okay.
    0:37:47 Another question, what happens or what’s the impact
    0:37:51 or the value if somebody gives you
    0:37:54 an inappropriate, mean, or destructive answer
    0:37:59 and the person then says, I was just being honest.
    0:38:02 Does that excuse you from being an asshole?
    0:38:04 – There’s a really great Taylor Swift lyric
    0:38:08 that says, “Casually cruel for the sake of being honest.”
    0:38:11 Ooh, that line will cut you like a knife.
    0:38:12 And I think it cuts you like a knife
    0:38:13 because it really captures something
    0:38:16 that we all feel torn about.
    0:38:20 This tension between benevolence or kindness
    0:38:23 or politeness and honesty
    0:38:27 because often the true contents of our minds are not kind.
    0:38:29 Our brains are built for a judgment
    0:38:32 and social evaluation and negative evaluation
    0:38:34 of other people and their work.
    0:38:36 And as you could tell from the book,
    0:38:38 I think a lot about what kindness means.
    0:38:41 Sometimes being honest in the short term,
    0:38:43 maybe giving feedback that someone needs to hear
    0:38:46 is kindest in the long term,
    0:38:50 but still you can deliver that honesty
    0:38:52 in a way that hopefully,
    0:38:53 and I think there’s some nice ingredients
    0:38:55 in the book to do this,
    0:38:59 in a way that isn’t even hurtful in the moment
    0:39:01 so that we can navigate this conundrum
    0:39:04 between benevolence and honesty
    0:39:07 even there with more kindness.
    0:39:10 – Up next on Remarkable People.
    0:39:14 – They are on a Zoom call but emailing at the same time.
    0:39:16 And so you get to see how overlapping
    0:39:19 and twisted and braided our conversations are these days.
    0:39:21 And what you realize is,
    0:39:25 it’s not just about choosing topics and asking questions.
    0:39:27 It’s doing that while you’re also engaged
    0:39:29 in like six other conversations at the same time
    0:39:32 that have their own unique topics and their own questions
    0:39:35 and sometimes a human mind on the other end
    0:39:37 synchronously and sometimes not.
    0:39:39 And this new conversational world
    0:39:41 that requires us to toggle like this
    0:39:43 can feel quite overwhelming.
    0:39:45 (gentle music)
    0:39:49 – Thank you to all our regular podcast listeners.
    0:39:52 It’s our pleasure and honor to make the show for you.
    0:39:54 If you find our show valuable,
    0:39:56 please do us a favor and subscribe,
    0:39:58 rate and review it.
    0:40:00 Even better, forward it to a friend,
    0:40:03 a big mahalo to you for doing this.
    0:40:07 – Welcome back to Remarkable People with Guy Kawasaki.
    0:40:12 What’s your advice when you have to converse
    0:40:16 with someone that you just completely disagree with?
    0:40:20 If I went to some dinner and I had to sit next to Elon Musk,
    0:40:22 like how do I approach a conversation
    0:40:25 with someone I completely disagree with?
    0:40:28 – You wanna think about what your goals are, right?
    0:40:30 So we have goals in the short term,
    0:40:35 like to survive the dinner and not have it be miserable,
    0:40:40 not get in such a heated argument that you cause a scene
    0:40:43 or probably like ruin a potential relationship
    0:40:45 with Elon Musk forever.
    0:40:47 Those are kind of inhumane.
    0:40:49 Maybe that’s your goal, that’s okay if it is.
    0:40:51 But then you have longer term goals.
    0:40:54 If you are thinking about how could I leverage
    0:40:57 a meaningful relationship with Elon Musk,
    0:40:59 if you’re playing the long game,
    0:41:00 your goal in the short term should be
    0:41:03 to have a great conversation with him.
    0:41:05 And the way that persuasion actually works
    0:41:09 between people is that you have to be in a good relationship.
    0:41:11 And if you have very differing views,
    0:41:16 they may slowly over time come to bend
    0:41:19 to the gentle pressure of your differing viewpoint,
    0:41:21 but you’re not gonna persuade him
    0:41:24 over a correspondence dinner at the White House
    0:41:26 in one conversation to change all of his views
    0:41:28 that you agree with.
    0:41:28 So I think-
    0:41:32 – The odds of me being invited to the White House are zero,
    0:41:34 so yeah.
    0:41:35 – You know what I mean?
    0:41:36 I think a lot of us have this instinct
    0:41:38 where we’re receiving, we hate the guy,
    0:41:40 we don’t agree with almost anything
    0:41:42 that someone else stands for,
    0:41:44 and therefore we have this need to be right
    0:41:47 and say something that really puts them in their place.
    0:41:50 But that’s not how to pursue.
    0:41:52 If you really have goals to persuade someone,
    0:41:54 you gotta play the long game.
    0:41:54 – Okay.
    0:41:57 I’ll tell him that I think Starlink is very well done.
    0:41:58 How’s that?
    0:41:59 – That’s a good start.
    0:42:01 compliments are a great start, guys.
    0:42:02 That sounds nice.
    0:42:04 Yes.
    0:42:05 – I hope it’s a short dinner.
    0:42:06 – Right?
    0:42:10 – Yeah, that’s one I’m gonna have to ask ChatGPT.
    0:42:14 What topics should Guy discuss with Elon at dinner
    0:42:15 in the White House?
    0:42:19 – To avoid getting into, immediately into a shouting match.
    0:42:20 Yeah.
    0:42:22 (laughing)
    0:42:24 – Next question, also tactical.
    0:42:28 How do you end or divert a conversation
    0:42:33 where someone is hitting on you or sexually approaching you?
    0:42:35 – I don’t wanna brag, but this was much of my life.
    0:42:38 So I have an experience with Elon.
    0:42:41 – Oh, that’s a 1% problem.
    0:42:42 – Yeah.
    0:42:44 You don’t have to end it, right?
    0:42:46 A bit of flattery is nice, no matter what,
    0:42:50 as long as it doesn’t feel threatening.
    0:42:53 And as long as it’s not disrespectful to someone else,
    0:42:56 to your partner, if you’re in a relationship or,
    0:42:59 or if it’s inappropriate in the context,
    0:43:01 if it’s someone in the workplace who’s coming
    0:43:05 and sort of coming onto you sexually in a way,
    0:43:08 so much of conversation is about reading your own needs,
    0:43:10 reading the other person’s needs,
    0:43:12 and then reading the context.
    0:43:14 So if you’re at a bar and somebody comes up to you
    0:43:16 and is hitting on you, that’s appropriate,
    0:43:18 but you should probably say, oh, actually I’m married
    0:43:21 or I’m in a relationship, I’m unavailable.
    0:43:23 If you’re in the workplace, things get trickier
    0:43:27 because then you have power dynamics and other goals
    0:43:30 and outcomes at play.
    0:43:31 That one gets harder.
    0:43:33 Most organizations have an anonymous line
    0:43:36 where you can contact a sort of title nine
    0:43:40 or mandatory reporter type of line to seek advice,
    0:43:41 especially if it’s someone who comes to you
    0:43:45 who has actual power over you in terms of your work.
    0:43:48 And hopefully you feel comfortable confiding
    0:43:53 in some sort of mentor to ask for advice about what to do.
    0:43:55 But in general, if somebody is,
    0:43:56 it makes an advance towards you
    0:43:58 and certainly outside of the workplace,
    0:44:00 I think you can take it as a compliment
    0:44:01 and just be honest with them.
    0:44:04 – Thank you so much, but I’m not available to be in that way.
    0:44:07 – I know, I hate when women treat me as an object, but okay.
    0:44:10 (laughing)
    0:44:13 – It’s all that surfing guy, you’re like a surfing stud.
    0:44:19 – You got into a whole discussion about NPR
    0:44:21 and how great their questions are,
    0:44:23 but I have a question for you.
    0:44:26 It seems that when I’m listening to NPR,
    0:44:30 they ask a lot of closed end questions.
    0:44:32 And just let me parody that.
    0:44:35 Like some of these interviews on NPR, they say,
    0:44:38 well, you saw your mother kill your father when you were eight
    0:44:41 and there was blood all over the kitchen floor.
    0:44:44 And then you had to testify against your father.
    0:44:47 Can you tell us more about how that affected you?
    0:44:49 Well, the answer is yes or no, right?
    0:44:53 But what happens when you ask a closed end question like that?
    0:44:56 – Yeah, I think especially for an outlet like NPR
    0:44:58 or for many people when they’re asking closed ended questions,
    0:45:01 it’s a sort of way, it’s a leading question
    0:45:04 and it’s a way of almost fact-checking.
    0:45:07 It’s literally saying, I know this about you already
    0:45:11 and I need you to confirm or deny that it’s true.
    0:45:13 Or some people use closed ended questions
    0:45:15 to help set context for a new topic
    0:45:16 to judge how much you know.
    0:45:18 So if I were to change and say,
    0:45:20 Guy, have you seen the TV show Silo?
    0:45:21 – Nope.
    0:45:25 – Right, so I just need that information quickly
    0:45:28 in order to guide how much, what I’m gonna say next.
    0:45:29 Am I gonna continue down that path?
    0:45:31 Or like, this isn’t gonna be interesting to you
    0:45:33 ’cause you haven’t seen the show, so I’m gonna pivot.
    0:45:36 So closed ended questions do have an important purpose,
    0:45:38 but they’re a completely different animal
    0:45:40 than the lovely open ended launch pads
    0:45:43 that we were talking about before.
    0:45:44 Open ended launch pads, by the way,
    0:45:48 good questions that inspire real information exchange
    0:45:49 and authenticity and connection.
    0:45:51 Often start with the word what.
    0:45:55 As opposed to I say, what is your favorite TV show right now?
    0:45:58 You’ll give me an answer and then we can go from there.
    0:46:01 So I will learn more than twice as much information
    0:46:03 by asking that question than saying,
    0:46:04 have you seen the show Silo?
    0:46:06 Where I get a yes or a no.
    0:46:08 As opposed to open ended questions
    0:46:09 that start with the word why.
    0:46:11 Why haven’t you watched Silo yet?
    0:46:13 Or why don’t you watch more TV?
    0:46:15 Those questions are open ended in theory,
    0:46:17 but they feel accusatory.
    0:46:21 So the relational part of that kind of question asking
    0:46:23 a little bit goes by the wayside.
    0:46:26 – Okay, just for the record, my favorite TV show
    0:46:29 was Yellowstone, and I’m the only person
    0:46:31 in Silicon Valley who liked Yellowstone.
    0:46:34 – Yeah, that is surprising.
    0:46:36 Oh my gosh, wow.
    0:46:39 – And my favorite character was Rip.
    0:46:42 – Oh, he’s a great character.
    0:46:43 I get it.
    0:46:44 You know what?
    0:46:45 There’s another topic for you
    0:46:47 to talk to Elon Musk about, okay?
    0:46:48 At the White House Dinner.
    0:46:51 You can talk about your share of Yellowstone
    0:46:52 and Rip Hamilton.
    0:46:54 Is it a Rip Hamilton?
    0:46:55 I don’t know, Rip.
    0:46:59 – Now I have a lot less hesitation
    0:47:03 to accept the White House Dinner in the next four years.
    0:47:05 – Yeah, you’ve already got two topics.
    0:47:09 We’ll find some more once you’re free and filming.
    0:47:11 – I want to know about the differences
    0:47:14 if you notice between men and women in conversations.
    0:47:17 And when I read this section about your friend
    0:47:20 calling you up and asking you about a vaginal mesh,
    0:47:24 I said, “I cannot imagine a man calling up another man.”
    0:47:27 So is there a difference between men and women?
    0:47:29 – Okay, agree to disagree.
    0:47:31 Because the number of conversations
    0:47:34 that I have overheard men talking about getting snipped
    0:47:37 after they’ve had their children,
    0:47:40 like more than 15 conversations have I eavesdropped
    0:47:42 on men talking. – Really?
    0:47:43 – When are you getting snipped?
    0:47:44 Are you snipped?
    0:47:45 Are you gonna do it?
    0:47:47 Are you gonna do it on master’s weekend
    0:47:49 so you can lay around and watch the go?
    0:47:50 (laughing)
    0:47:53 Truly, it’s like so many, so many has.
    0:47:55 So I think that’s the male version
    0:47:58 of the vaginal mesh conversation.
    0:47:59 As scientists, we have a lot to learn
    0:48:03 about gender similarities and gender differences
    0:48:05 in terms of communication.
    0:48:09 You see a lot of hypotheses and hunches
    0:48:11 thrown around in the public
    0:48:15 about gender differences in conversation
    0:48:18 that are not yet substantiated by scientific evidence.
    0:48:20 And in fact, the stuff that we do know
    0:48:23 is like actually men and women talk
    0:48:25 in a lot of the same ways.
    0:48:27 So there’s this great study by Matthias Mel.
    0:48:29 They’ve had people wear badges
    0:48:32 that just recorded ambient noise on people
    0:48:34 every two minutes or so in their lives.
    0:48:36 And so you get this full sample
    0:48:39 of somebody’s auditory life.
    0:48:41 And through that method, they found that men and women
    0:48:45 speak exactly the same amount of words on average per day,
    0:48:48 about 16,000 words per day on average.
    0:48:49 Now, when you start to look at,
    0:48:52 well, when are they talking and what are they saying?
    0:48:53 That’s where you can get into,
    0:48:55 well, are there content differences?
    0:48:58 Are women more likely to talk about vaginal mesh than men?
    0:48:59 Yeah, probably, but men are more likely
    0:49:02 to talk about their vasectomies.
    0:49:04 But science really hasn’t gotten to a point
    0:49:06 of how a fine grained figuring out,
    0:49:07 are there gender differences?
    0:49:08 Are there racial differences?
    0:49:09 Are there age differences?
    0:49:11 And what are they?
    0:49:13 What are the topics that different demographic groups
    0:49:14 are discussing?
    0:49:17 And what does that mean for how they relate to each other,
    0:49:20 for how we see each other as similar and different?
    0:49:22 That’s, I think, a very exciting area
    0:49:23 for scientists to pursue,
    0:49:26 is looking at the content of what people are saying.
    0:49:29 – I want you to know today that between sets,
    0:49:32 as we serve, I’m going to go asking all the men
    0:49:33 if they’ve been snipped.
    0:49:37 I can come across as a sensitive man, but–
    0:49:38 – But again, you’re probably beyond
    0:49:41 that phase of life where it’s irrelevant anymore.
    0:49:46 – Actually, this is another topic I can have
    0:49:48 with Elon. – Yes.
    0:49:51 – Don’t you think you should be snipped by now?
    0:49:53 – Yes, vasectomy, I’m adding it.
    0:49:56 I’m literally compiling your list for Elon.
    0:49:59 This is so fun, I didn’t anticipate this,
    0:50:00 but I’m really enjoying it.
    0:50:02 (laughing)
    0:50:04 – All right, so you brought up the topic
    0:50:06 of academic research.
    0:50:09 So as I was reading your book, I thought to myself,
    0:50:12 there’s a lot of dependency in this book
    0:50:15 about speed dating experiments.
    0:50:17 Are you at all worried that speed dating
    0:50:20 may not extrapolate to everybody in the real world?
    0:50:22 – Yes, of course.
    0:50:25 This science of conversation is very new.
    0:50:28 It is very important for people to realize this.
    0:50:30 People have been studying language,
    0:50:32 human language, the development of language.
    0:50:34 They’ve been studying public speaking,
    0:50:37 so one way where one person just says something
    0:50:41 and nobody responds for a very, very long time.
    0:50:43 We know a lot about language.
    0:50:46 We know very little about dialogue
    0:50:48 because only in the last 10 years
    0:50:50 have we come across a technology
    0:50:53 that allows us to record real conversations
    0:50:54 at very large scale,
    0:50:58 the tools to analyze those conversations at large scale.
    0:50:59 And so we’re at this phase right now
    0:51:03 where we’re learning things very, very quickly,
    0:51:05 but we are still quite limited by the data sets
    0:51:08 that we have access to that are of the gold standard
    0:51:11 of academic rigor that you would rely on.
    0:51:14 And so you kind of have to make these sort of logical leaps
    0:51:17 of like, well, if things are going well in speed dating,
    0:51:19 probably some of those things are generalizable
    0:51:20 to real dating.
    0:51:23 And then, well, what about dating is specific to dating
    0:51:28 or versus it’s actually translatable to all conversations?
    0:51:29 And so that’s where we are right now.
    0:51:32 It’s starting to figure out, well, what is context specific
    0:51:35 and what is generalizable across lots of areas
    0:51:37 where people talk to each other.
    0:51:40 – I’m not saying that most people who listen to my podcast
    0:51:43 are in the dating game, but while I have it,
    0:51:45 do you have some tips for dating?
    0:51:47 – I do, I do.
    0:51:50 Number one, it depends on if the person is a stranger to you.
    0:51:52 So if it’s a first date,
    0:51:55 it’s really important that you don’t have long pauses.
    0:51:57 So long pauses are the death knell
    0:52:01 or conversations between strangers is very awkward.
    0:52:04 So just keep asking questions, keep asking, follow up questions,
    0:52:07 bring, have your list of topics ready to go
    0:52:08 so you don’t have to panic
    0:52:11 when you know you need to change the topic.
    0:52:13 You can use any of the topics that we’ve used here today.
    0:52:15 Actually, on your date would be great.
    0:52:18 Really, I think on a date, whether it’s with a stranger
    0:52:21 or with someone that you’ve been dating for a while
    0:52:24 and with all people in all contexts,
    0:52:27 asking follow up questions is a superpower
    0:52:31 because you don’t need to have prepared at have time.
    0:52:33 You don’t need to know anything about them
    0:52:35 or about or have any knowledge of anything.
    0:52:38 You just need to listen to what your partner is saying
    0:52:40 and continue to ask questions about it.
    0:52:44 We see people fail to do this a lot in our data,
    0:52:47 both in speed dating, but in other contexts as well,
    0:52:49 negotiating, sales calls,
    0:52:52 just normal conversations between family members.
    0:52:55 When someone shares something important with you,
    0:52:57 if they are courageous enough
    0:52:59 to share something about their life with you,
    0:53:02 you should follow up on it and ask more about it
    0:53:04 as a signal that you care, that you heard them
    0:53:06 and that you wanna know more.
    0:53:10 – So now, another kind of dating is the job interview.
    0:53:12 So now you’re trying to get a job.
    0:53:16 How do you have a good conversation as the applicant,
    0:53:17 not as the recruiter?
    0:53:20 – Yeah, as an applicant, I think in our minds
    0:53:22 when we think of conversational job interviews,
    0:53:24 there’s this very clear script of like,
    0:53:26 well, this employer is gonna be asking me questions
    0:53:30 and I need to prove how great I am.
    0:53:32 I need to prove how interesting, smart, competent
    0:53:35 and well suited to this role I am.
    0:53:39 Anything you can do to flip that script is gonna go great
    0:53:42 because a real conversation that’s rewarding
    0:53:45 and actually makes you look competent is a give and take.
    0:53:48 So you can’t just sit there and wait for an interviewer
    0:53:50 to hit you with question after question.
    0:53:52 They’re gonna get bored with that.
    0:53:53 They’re not actually gonna be impressed
    0:53:56 with almost anything you say, probably.
    0:53:59 So again, ask questions back, ask follow up questions,
    0:54:02 try and learn about their perspective.
    0:54:05 Instead of trying to prove how great you are as an applicant,
    0:54:08 try and be interested in the work that they’re doing
    0:54:09 and learn as much as you can about it
    0:54:10 so that you can actually judge
    0:54:13 whether you are a good fit for the role.
    0:54:17 – You could ask, what do you think of your CEO
    0:54:20 going to the inauguration that’ll definitely get you an offer?
    0:54:24 – If you were giving him advice about the topics to raise
    0:54:27 with the people at his table,
    0:54:29 what would you advise him to say?
    0:54:31 And then you could raise him about it together.
    0:54:33 That would be so fun.
    0:54:34 And it would be such undeniable evidence
    0:54:37 that you’re interesting and creative.
    0:54:39 (laughing)
    0:54:43 – I’m glad I’m not applying for a job anytime soon.
    0:54:45 (laughing)
    0:54:50 So now, bring me up to speed, like your research,
    0:54:54 what are the implications of doing all this on Zoom
    0:54:56 instead of in real life?
    0:54:58 – Yeah, I think about this a lot.
    0:54:59 I had written a whole chapter in the book
    0:55:02 about digital communication and I took it out
    0:55:04 at the very end of the editing process.
    0:55:05 – Why?
    0:55:07 – I know, because I want the book to be timeless.
    0:55:10 By the time I had written it a year earlier,
    0:55:11 it was already outdated.
    0:55:13 I mean, while I was writing the book,
    0:55:17 LLNs, chat, GPT, AI, it all happened.
    0:55:20 And there’s going to be more of that in the future.
    0:55:24 Whatever you say now is going to change dramatically.
    0:55:26 Most of what you could say now is going to change
    0:55:29 just rapidly and in exciting ways.
    0:55:31 But now I get to actually talk about it.
    0:55:32 So let me tell you what was in that chapter
    0:55:34 that I find so important.
    0:55:36 I think there’s a lot of rhetoric in our culture
    0:55:39 about getting kids off their phones
    0:55:41 and letting them have a good childhood.
    0:55:44 I think what we need to talk about a little bit more
    0:55:45 is like, well, we’re all part of this world.
    0:55:47 It’s not just children.
    0:55:51 We are all toggling constantly between our phone
    0:55:53 and the computer and then turning and talking
    0:55:55 to someone in real life and then someone calls
    0:55:57 and then you’re texting at the same time.
    0:56:00 So we’re all doing this conversational toggling.
    0:56:04 And I think we don’t have any idea what that’s doing
    0:56:07 to our brains, what it’s doing to our relationships
    0:56:11 and certainly how it’s affecting our conversational skills.
    0:56:14 So I’m interested to see what happens.
    0:56:17 In my class, I ask my students to do an audit
    0:56:19 of their conversational lives
    0:56:21 where I ask them to take 20 minutes in your life.
    0:56:24 And I want you to write down every incoming
    0:56:27 and outgoing message, whether it’s an email, a text,
    0:56:30 a phone call, a real life conversation,
    0:56:32 some reels and memes on TikTok.
    0:56:34 Well, I should say Instagram now.
    0:56:35 And so they write it all out
    0:56:38 and you get this really wild sample.
    0:56:41 It’s a transcript, but it’s all over the map, right?
    0:56:43 They’re sending texts while they’re talking
    0:56:45 to their mom on speakerphone.
    0:56:49 They are on a Zoom call but emailing at the same time.
    0:56:51 And so you get to see how overlapping
    0:56:54 and twisted and braided our conversations are these days.
    0:56:57 And what you realize is it’s not just
    0:57:00 about choosing topics and asking questions.
    0:57:02 It’s doing that while you’re also engaged
    0:57:04 in like six other conversations at the same time
    0:57:07 that have their own unique topics and their own questions.
    0:57:10 And sometimes a human mind on the other end
    0:57:12 synchronously and sometimes not.
    0:57:14 And this new conversational world
    0:57:16 that requires us to toggle like this
    0:57:18 can feel quite overwhelming.
    0:57:20 When they look back on their audit,
    0:57:23 the students often say that only the ones
    0:57:24 where they were synchronous,
    0:57:28 whether it’s in person or on Zoom, felt real.
    0:57:30 That felt rewarding.
    0:57:33 Felt like they had some sense of human connection.
    0:57:35 And I think that’s not trivial.
    0:57:37 – My phone is off.
    0:57:38 – You’re so kind.
    0:57:40 I just got six text messages.
    0:57:41 Sorry, guy.
    0:57:45 – Okay, so two last questions
    0:57:48 because I don’t wanna take up too much of your time
    0:57:48 on launch day.
    0:57:53 So I wanna know who is in the Alison Woodbrooks
    0:57:57 conversation hall of fame.
    0:58:00 – Oh, what a great question.
    0:58:01 My mom.
    0:58:02 My mom is-
    0:58:03 – Your mom?
    0:58:05 – Yeah, she’s amazing.
    0:58:07 I talk to her every day.
    0:58:09 I’m gonna cry just thinking about it.
    0:58:12 She’s such a good listener.
    0:58:16 She’s so funny and she cares so much about me
    0:58:18 and about all the people that she knows
    0:58:20 that I think she was an incredible role model
    0:58:22 for me my whole life.
    0:58:25 And I’ve never said that out loud before, guy.
    0:58:26 Thank you for asking.
    0:58:27 – Wow.
    0:58:29 – I could give answers to letters like celebrities
    0:58:32 that I think are amazing.
    0:58:33 Most of them are very good listeners
    0:58:35 and are good at levity.
    0:58:39 So people like Stephen Colbert, Conan O’Brien,
    0:58:41 Nikki Glaser, in the book you,
    0:58:44 Terry Gross is a really amazing question asker.
    0:58:47 Really anyone who is in the public sphere
    0:58:50 and become successful for having conversations,
    0:58:52 this is what their core skill set is, right?
    0:58:54 Like that’s why they’ve been successful
    0:58:56 is that they are good at preparing topics.
    0:58:58 They are good at asking questions.
    0:58:59 Joe Rogan, right?
    0:59:01 Like whether you agree or disagree with him,
    0:59:03 he’s a terrific conversationalist.
    0:59:04 He’s great at asking questions.
    0:59:06 He’s good at getting people to open up.
    0:59:09 Guy Kawasaki, great at bringing levity
    0:59:12 and then moving topics quickly and asking follow-up.
    0:59:14 – You mentioned Joe Rogan and Guy Kawasaki
    0:59:15 in the same sentence.
    0:59:17 – I’m sorry, I know.
    0:59:18 – I’m arrived.
    0:59:19 – I know.
    0:59:21 – We can end the recording right here.
    0:59:22 (laughing)
    0:59:26 – You see, this is what’s so beautiful about the world.
    0:59:31 You see examples of conversational greatness all the time.
    0:59:35 You also see examples of fumbles and stumbles all the time.
    0:59:38 And it’s because we’re all human beings.
    0:59:40 We’re all just trying to do our best.
    0:59:44 Sometimes we strike gold and we find amazing moments
    0:59:47 of connection and information exchange and closeness.
    0:59:50 And sometimes we mess it up and that’s okay.
    0:59:51 – Speaking of messing this up,
    0:59:55 right, as I was reading your book and as we’re having
    1:00:00 this discussion, when we adopted our fourth child,
    1:00:03 so we have two adopted children.
    1:00:07 So we adopted him about 17, 18 years ago.
    1:00:13 I was at a dinner with my wife and a friend and his wife.
    1:00:16 And he said, you know, we told him
    1:00:18 we’re adopting another child, right?
    1:00:20 And he said something like,
    1:00:22 aren’t you concerned about adoption?
    1:00:24 Because adoption, typically these kids,
    1:00:28 they didn’t have good prenatal nutrition
    1:00:31 or they come from broken homes or drugs in the house.
    1:00:35 Adopted kids have a lot of problems.
    1:00:37 And I have never forgiven him for that
    1:00:42 because he, this is after we told him we have one kid,
    1:00:45 we’re adopting another kid.
    1:00:47 Not that we’re thinking about adoption.
    1:00:51 We have adopted kids and we’re going to adopt this.
    1:00:54 And I thought that was such an insensitive thing to do.
    1:00:57 I have never forgiven him.
    1:01:00 And he probably has no idea why I’ve been pissed off
    1:01:02 for about 20 years with him all this.
    1:01:04 – Would you ever think about telling him?
    1:01:06 – Would you ever think about telling him?
    1:01:08 – After reading your book and this discussion,
    1:01:12 maybe I will because he probably, from his side,
    1:01:13 maybe he was just thinking,
    1:01:16 I want my friend to make a really wise decision
    1:01:17 about adoption.
    1:01:21 I don’t want him to go in with blinders on.
    1:01:22 – Or maybe it was out of his own fear.
    1:01:24 Maybe he had been thinking about adoption
    1:01:28 and that’s what he’s afraid of for himself or for you or,
    1:01:31 yeah, we make mistakes like that.
    1:01:32 That’s an insensitive thing to say.
    1:01:34 It sounds very self-centered, right?
    1:01:39 It sort of reeks of being focused on what you know
    1:01:40 and what you’re afraid of
    1:01:42 rather than asking a question of,
    1:01:45 do you have any fears about this, right?
    1:01:47 Like that would have been much more adaptive thing
    1:01:50 to do in that moment for them.
    1:01:52 – I would tell you what country he’s from,
    1:01:55 but it would immediately help some people identify
    1:01:57 who I’m talking about, some of them.
    1:01:58 (laughing)
    1:02:00 – I could make guesses, but I don’t want to make,
    1:02:03 I don’t want to, I don’t want him stereotyped.
    1:02:07 – All right, so my last question for you,
    1:02:12 Alison Wood, the queen of conversation is, ironically,
    1:02:15 how do you be a better listener?
    1:02:18 As opposed to conversationalist.
    1:02:20 – Yeah, it’s so funny, the title of the book is talk,
    1:02:22 but I think the secret sauce,
    1:02:25 the secret message of the whole thing is about listening.
    1:02:28 You can’t talk well without listening.
    1:02:31 And it turns out that listening is really hard,
    1:02:33 especially for people who have attentional issues,
    1:02:36 but really for everybody, there’s great research.
    1:02:40 The resting state of the human mind is mind wandering.
    1:02:44 It is not built to pay attention to another person
    1:02:47 continuously while you’re engaging with them.
    1:02:50 So it takes effort to get out of our natural mind wandering
    1:02:52 state and actually listen to each other.
    1:02:54 That is effortful.
    1:02:55 It is worth putting in that effort.
    1:02:59 You need to do it in order to have good conversation.
    1:03:01 And when you do it, when you look at somebody else,
    1:03:02 you listen to what they’re saying,
    1:03:04 you process what they’re saying,
    1:03:07 you think hard about it, you try and really engage with it,
    1:03:09 you should get credit for it
    1:03:12 by showing them that you’ve heard them.
    1:03:15 And so many, many years of research on active listening
    1:03:19 have told us to use nonverbals like nodding and smiling
    1:03:20 to show someone that we’ve heard them.
    1:03:23 That’s good, that’s a great start, that matters.
    1:03:26 But really the advanced course on listening
    1:03:29 is using your words to show someone that you’ve heard them.
    1:03:33 I can only call back to this story about adoption
    1:03:35 for your kids because I was listening to you
    1:03:37 and I care about it and I’ve been thinking about it.
    1:03:40 I can only call back to your surfing earlier
    1:03:42 in the conversation because I cared about that
    1:03:44 and I latched onto it and I heard it.
    1:03:46 I can only ask a follow-up question
    1:03:49 if I heard what you said and I care to know more.
    1:03:51 So these verbal signals like follow-up questions,
    1:03:53 callbacks, paraphrasing,
    1:03:55 just repeating what someone has said,
    1:03:57 hey, I hear you saying that you were upset by this
    1:04:00 and maybe you’re thinking about contacting this guy again
    1:04:02 to reach out, do you think you’ll actually do that?
    1:04:06 So repeating what someone has said can be really,
    1:04:10 really valuable and makes people feel heard and seen
    1:04:13 and loved and it’s really where so much
    1:04:15 of the conversational magic lies.
    1:04:20 – This has been speaking of magic, a magical conversation.
    1:04:20 – I agree.
    1:04:24 – I can look forward to having dinner with Elon Musk.
    1:04:27 I never would have predicted that.
    1:04:28 – Now you can get excited about it.
    1:04:31 We’ve got four topics brainstormed.
    1:04:33 We’re gonna get at least 10 more together
    1:04:34 and then we’re gonna make it happen
    1:04:36 ’cause I wanna record this conversation at CO4.
    1:04:39 – You’ve changed my life, you’ve changed my life.
    1:04:42 I want you to get the transcript of this
    1:04:45 and do an analysis and I want you to figure out
    1:04:47 this is like speed podcasting.
    1:04:50 – If I wasn’t doing so many podcasts for the book,
    1:04:53 I would honestly, so many of my students have done that.
    1:04:55 Actually, this year, two of my students
    1:04:56 did this creative thing.
    1:05:00 They took a real podcast recording of me and somebody
    1:05:04 and then they created an LLM podcast of fake Allison
    1:05:07 and fake other person and then they did a conversation,
    1:05:10 side-by-side conversation analysis of both
    1:05:14 to see what are the pros of human-to-human conversation
    1:05:18 compared to LLM conversation
    1:05:21 and your hypothesis guy was definitely confirmed,
    1:05:25 which is humans are better at asking questions.
    1:05:27 They’re better at laughing with each other.
    1:05:29 They’re better at finding sparkly moments
    1:05:31 of levity and connection.
    1:05:34 So thank you, it’s such a gift to do this together.
    1:05:38 – You know what, I noticed, speaking of questions
    1:05:41 from left field, I noticed you had a podcast
    1:05:46 and I watched it and on your side, on your shelf,
    1:05:49 you had his logo.
    1:05:50 Do you remember that?
    1:05:51 – I don’t.
    1:05:55 Oh, maybe Matt Abraham says, “Think fast, talk smart.”
    1:05:59 – No, it wasn’t Matt Abraham, it was somebody else
    1:06:01 and I thought, I wonder if he superimposed that
    1:06:03 on the video or that.
    1:06:07 – Alison is so clever that when she is interviewed
    1:06:12 by a podcaster, she puts the podcasters book on her shelf
    1:06:16 and I said, “That is why she’s at Harvard Business School.”
    1:06:19 – I’m that ahead of the curve.
    1:06:22 I’m sure he superimposed it, but I will aspire
    1:06:25 to be the kind of person that would do that for sure.
    1:06:29 – And I swear to God, I thought about it,
    1:06:30 but I didn’t do it.
    1:06:33 I was gonna put talk on my shelf.
    1:06:34 – Yeah, where’s your-
    1:06:35 – But I forgot.
    1:06:37 – Yeah, get it on your shelf, guy.
    1:06:40 Tell everybody about it.
    1:06:43 Our world needs it so badly right now and always.
    1:06:45 We need better communicators.
    1:06:50 – Speaking of LLM, so there’s such a thing as Kawasaki GPT
    1:06:52 and we put the transcripts of every one
    1:06:55 of my interviews in there.
    1:06:58 So pretty soon, people can go to Kawasaki GPT
    1:07:01 and ask Alison questions based on this interview.
    1:07:04 Well, you let me know if you do an analysis
    1:07:06 of this conversation, I would love the output.
    1:07:09 I would love to see what you uncover about our connection.
    1:07:13 – No, but I don’t have the academic wherewithal to do this.
    1:07:15 You should make this a project to like-
    1:07:16 – I should.
    1:07:20 – Are you tired of listening to people talk on speed dates?
    1:07:21 You should listen to-
    1:07:22 – Never.
    1:07:25 – Guy and I do a podcast to see what great conversation
    1:07:28 is like, how many questions did they ask?
    1:07:30 How many times did they switch topics?
    1:07:32 How many times did they come back?
    1:07:36 How many sensitive questions about salaries did Guy ask?
    1:07:38 – Well, it is, I mean, doing a book tour like this
    1:07:41 with lots of podcasts, it is a very interesting,
    1:07:44 natural sort of case study of conversation
    1:07:45 because I’m always there.
    1:07:46 I’m always constant.
    1:07:48 It’s just that the host is changing.
    1:07:51 And in theory, it’s the related topics.
    1:07:52 We’re always talking about the book,
    1:07:56 but the variability is stackering.
    1:07:58 What you end up talking about,
    1:08:01 my favorite is when they’re more conversational like this,
    1:08:02 like where you, you know,
    1:08:03 you’re talking about the book,
    1:08:05 but you’re talking about other stuff too.
    1:08:07 I think everybody wants that.
    1:08:09 – So in version two of your book,
    1:08:11 you can mention this conversation,
    1:08:14 but what’s even more important to me in version two
    1:08:18 of this book is that you change asking to ask.
    1:08:18 – I’ll do it.
    1:08:19 I’ll do it.
    1:08:21 I’m gonna add, I’m gonna make a footnote
    1:08:23 in the next edition.
    1:08:26 Addition two, Guy Kawasaki says this should be asks.
    1:08:31 I’m gonna change the entire meaning of the word asks
    1:08:32 for him.
    1:08:35 – Allison, I’m sure you have other important things to do.
    1:08:37 So thank you so much.
    1:08:40 This has been just a remarkable conversation.
    1:08:42 – It’s amazing to connect, Guy.
    1:08:43 – I’m Guy Kawasaki.
    1:08:45 This has been remarkable people.
    1:08:49 And man, what a remarkable conversation we had today.
    1:08:52 This is gonna go down in the annals of podcast history.
    1:08:54 My thanks to Matt for bringing us together
    1:08:58 and also for being in the same group of people
    1:09:01 with Katie Milgman and Angela Duckworth and Bob Cialdini.
    1:09:04 These are all the people who lead behavioral research.
    1:09:08 And thanks to Madison Nizmer, who is our producer.
    1:09:09 Tessa Nizmer, our researcher.
    1:09:12 Jeff C. and Shannon Hernandez.
    1:09:14 We got a lot of people who make remarkable people,
    1:09:15 remarkable.
    1:09:18 So until next time, thank you very much.
    1:09:21 And Mahalo and Aloha.
    1:09:26 This is Remarkable People.

    Join Guy Kawasaki for a fascinating conversation with Alison Wood Brooks, Harvard Business School professor and author of Talk. As the creator of the innovative “How to Talk Gooder” course, Brooks reveals the science behind great conversations, sharing insights on everything from the power of asking sensitive questions to navigating difficult discussions. Learn her TALK framework and discover why small talk isn’t a waste of time after all.

    See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

  • Mike Maples Jr.: Inflection Points and Startup Success

    Mike Maples Jr.: Inflection Points and Startup Success

    AI transcript
    0:00:02 (upbeat music)
    0:00:10 – Hello, I’m Guy Kawasaki.
    0:00:12 This is the Remarkable People podcast,
    0:00:16 and we’re in the business of helping you become remarkable.
    0:00:19 So we scour the globe for the most remarkable people,
    0:00:23 and we found a remarkable person named Mike Maples Jr.
    0:00:26 And in the prelude, we were just discussing,
    0:00:28 he and I go way back.
    0:00:30 In college, he read my books,
    0:00:32 which is kind of a disturbing thing
    0:00:36 when people tell you that they read your book in college,
    0:00:39 and now they’re way out of college.
    0:00:43 But anyway, so he is a venture capitalist today.
    0:00:47 He’s the co-founder of a leading Silicon Valley seed fund
    0:00:51 called Floodgate, and he has invested in companies
    0:00:54 like Twitter, and Twitch, and Okta.
    0:00:57 He’s really one of the pioneers of seed capital
    0:00:59 in the mid-2000s.
    0:01:02 So with no further ado, Mike Maples Jr.,
    0:01:04 welcome to Remarkable People.
    0:01:07 – Hey, thanks Guy, and I’ve been looking forward to this.
    0:01:09 I think I’ve probably known you much longer
    0:01:11 than you’ve known me, because I got to know you
    0:01:14 somewhat through your books when I was in college.
    0:01:17 – Wow, like I said, that’s kind of a double edged sword.
    0:01:20 Well, as long as you don’t think that I wrote Rich Dad,
    0:01:22 Poor Dad, I call that a win.
    0:01:24 So I’m easy to please that way, Mike.
    0:01:26 – Yeah, yeah.
    0:01:29 The ones I really remember in my formative years
    0:01:31 were The Macintosh Way,
    0:01:34 and then the other one was Selling the Dream.
    0:01:36 And I think in Selling the Dream,
    0:01:40 I was actually at Kepler’s bookstore when you launched it.
    0:01:42 I probably have a signed copy.
    0:01:43 And one of the aspects of it I remember
    0:01:46 is I think it had the Macintosh product introduction plan.
    0:01:48 – Yes, in the back.
    0:01:50 – So at the time, I was a young product manager
    0:01:53 at Silicon Graphics, and you didn’t really get trained
    0:01:55 in marketing back in those days.
    0:01:57 And so everything I knew about marketing
    0:01:59 is just what I read in marketing books.
    0:02:01 That was an actual introduction plan.
    0:02:03 I was like, “Hey, man, I could really learn something
    0:02:04 “from this.”
    0:02:08 And then reading your books led me to Regis McKenna
    0:02:09 and some of his work.
    0:02:11 I always thought that he had some really good ideas
    0:02:12 around relationship marketing
    0:02:15 and how do you evangelize ideas.
    0:02:17 Yeah, so I feel like I’ve probably known you,
    0:02:19 hopefully I don’t seem like a stalker,
    0:02:23 but I’ve known you since you were CEO of ACIAS.
    0:02:24 – Wow.
    0:02:26 – Man, you’re going back.
    0:02:28 You’re going back so far.
    0:02:29 I was young.
    0:02:31 (laughs)
    0:02:35 So I loved your book and I see so much stuff
    0:02:37 that I agree with in your book.
    0:02:39 And let’s start with something very basic.
    0:02:43 Your book is all about getting these inflections
    0:02:46 and getting insights from the inflections
    0:02:48 and turning it into ideas.
    0:02:51 So let’s start with a definition to help everybody.
    0:02:55 What exactly do you consider an inflection?
    0:02:59 – Yeah, so an inflection is a change event
    0:03:02 that’s actually external to a startup
    0:03:04 or any business for that matter.
    0:03:08 And it allows a startup capitalist
    0:03:10 to compete by changing the subject.
    0:03:13 So what I like to say is that in startups,
    0:03:15 better doesn’t matter
    0:03:18 because business is never a fair fight.
    0:03:19 And if you’re a startup,
    0:03:23 you have to have some form of weapons
    0:03:25 to wage asymmetric warfare on the present.
    0:03:29 You have to turn the incumbents’ greatest perceived strengths
    0:03:31 into their biggest weaknesses.
    0:03:33 And the way entrepreneurs do that
    0:03:34 is they harness inflections.
    0:03:37 They use inflections to bend the arc of the present
    0:03:39 to a radically different future.
    0:03:41 And by doing that,
    0:03:45 they deny the premise of the rules of competition.
    0:03:47 They show up seemingly out of left field
    0:03:50 and now all of a sudden they disorient the incumbents.
    0:03:53 Airbnb did this in hospitality
    0:03:55 and Twitter did this in blogging and communication.
    0:03:58 But nobody ever when they saw Airbnb said,
    0:04:00 “Well, how does that compare to Four Seasons?”
    0:04:02 And nobody when they saw Twitter said,
    0:04:04 “How does that compare to WordPress?”
    0:04:07 It stood alone as an entirely new thing.
    0:04:09 I like to say better doesn’t matter when you’re startup
    0:04:11 because if you’re better,
    0:04:14 then the customer’s gonna have an alternative
    0:04:15 to your startup.
    0:04:17 And why would they pick your product
    0:04:19 when you’re 80% likely to go out of business?
    0:04:20 They’re only gonna pick your product
    0:04:23 if it can’t be reconciled with anything
    0:04:24 they’ve ever seen before.
    0:04:25 And if they say, “Oh my gosh, where have you been
    0:04:26 all my life?”
    0:04:29 And so the way that the founder achieves that goal
    0:04:31 is they harness inflections.
    0:04:33 They use the power of inflections to offer something
    0:04:36 that would seem unthinkable before the inflection happened.
    0:04:38 – But Mike. – Yes.
    0:04:43 – Do inflections cause companies to succeed
    0:04:47 or do companies cause inflections to succeed?
    0:04:49 Which way does it flow?
    0:04:51 – Yeah, so I like that question
    0:04:54 and it is one of these kind of recursively existential
    0:04:56 questions too, right?
    0:04:58 And the way I internalized it was,
    0:05:01 I was like, okay, what should founders care about?
    0:05:04 And what I thought was, okay,
    0:05:08 founders need some type of a power to change the subject.
    0:05:11 And so when I think about an inflection,
    0:05:13 whether the founder caused it or leveraged it,
    0:05:16 what matters I think from the founder point of view
    0:05:17 is three things.
    0:05:21 One is just what is the specific empowerment?
    0:05:24 Does it offer something that can provide a 10x benefit
    0:05:29 or something radically unique that’s never been seen before?
    0:05:31 Or is it just an API call that got added
    0:05:33 to Stripes API list, right?
    0:05:36 So like a good example of an inflection would have been
    0:05:41 it was empowering was the iPhone 4S had a GPS chip in it.
    0:05:43 And you could have had the idea for ride sharing
    0:05:45 before the iPhone 4S, but it wouldn’t have mattered
    0:05:47 because you couldn’t have implemented a system
    0:05:49 that embodied that idea.
    0:05:52 But now all of a sudden you have a GPS chip in the phone,
    0:05:55 you can locate riders and drivers with an algorithm.
    0:05:57 So that’s an example of something very empowering.
    0:06:01 The second thing we wanna see in an inflection is,
    0:06:02 who does it empower?
    0:06:03 Who cares?
    0:06:05 And in the case of the iPhone 4S,
    0:06:08 a lot of people care ’cause a lot of people have smartphones.
    0:06:11 And so the potential surface area of the empowerment
    0:06:13 is very high because if you believe
    0:06:15 that smartphones will keep happening
    0:06:17 and they’ll keep having GPS chips in them,
    0:06:19 then potentially that’s hundreds of millions
    0:06:21 if not billions of people someday.
    0:06:25 And then the third aspect of the inflection is,
    0:06:27 I call it the empowerment conditions.
    0:06:31 And so we’ve had nuclear power since the ’40s,
    0:06:33 but we haven’t built a nuclear power plant
    0:06:35 in the United States since the 1970s.
    0:06:37 And so just because you have a power
    0:06:39 doesn’t mean you’re gonna use it or be allowed to use it.
    0:06:41 And there might be political factors,
    0:06:43 there might be trust factors,
    0:06:44 there could be a lot of reasons
    0:06:47 that people don’t decide to adopt it.
    0:06:49 So those are the three things I look for.
    0:06:50 What’s the magnitude of the empowerment?
    0:06:52 Who does it empower?
    0:06:54 And under what conditions will people decide
    0:06:55 to take advantage of it?
    0:06:58 And under what conditions will they decide not to?
    0:06:59 And if you can get all three of those things
    0:07:02 going your way as a founder,
    0:07:05 now it’s kind of like a rock and David slingshot
    0:07:06 against Goliath, right?
    0:07:09 Now you have something that you can bring to the party
    0:07:11 that changes the subject.
    0:07:14 – When I read your book and I read that concept,
    0:07:18 I thought to myself, oh my God, this is such a high fence.
    0:07:23 In a sense, you’re saying that every successful startup
    0:07:27 either caused or significantly jumped on an inflection.
    0:07:31 And I gotta tell you, I see a lot of startups
    0:07:36 that I would hardly affiliate them with truly an inflection.
    0:07:39 So are you that tough?
    0:07:41 I mean, if somebody shows up at flood gate
    0:07:45 and they just have something better, better,
    0:07:47 do you just throw them out the door?
    0:07:48 – Well, I don’t throw them out the door.
    0:07:50 I wish them well, right?
    0:07:52 But what I say to them is, look,
    0:07:55 do you want to pursue an idea that has outlier,
    0:07:58 unbounded upside potential or not?
    0:08:01 And if you’re not harnessing an inflection
    0:08:02 in your startup idea,
    0:08:06 you’re competing in somebody else’s sandbox.
    0:08:09 So the mistake most startups make is they say,
    0:08:11 I want to go after big market.
    0:08:14 And that makes sense on the surface
    0:08:17 because big markets have lots of customers and revenue.
    0:08:20 But the problem is that the founder often unwittingly
    0:08:23 buys into a context, which is the market
    0:08:26 as it’s defined as the market.
    0:08:28 And if the market’s already defined,
    0:08:30 then somebody’s defined it.
    0:08:32 And that person has the advantage over you
    0:08:35 because they get to define the discussion that occurs
    0:08:37 and they already have the advantages of the incumbency.
    0:08:40 And so therefore, it’s kind of like
    0:08:41 if you’re competing over territory
    0:08:43 that’s a tiny little municipality
    0:08:45 and an already discovered thing,
    0:08:47 you’re not gonna have as big of an upside
    0:08:49 as if you’re Lewis and Clark mapping
    0:08:51 the Louisiana Purchase territory
    0:08:55 and discovering the undiscovered land.
    0:08:58 And so I’m not interested in the total existing
    0:09:00 or total available market.
    0:09:01 I’m interested in the total future market.
    0:09:04 I’m interested in a product that defines a future market
    0:09:06 because it harnesses these inflections.
    0:09:08 And so I just say to a founder, hey, look,
    0:09:11 I’m not for everybody, but that’s what I’m in it for.
    0:09:14 I’m trying to find startups that harness these inflections
    0:09:17 in unconventional ways to create a product
    0:09:20 that radically changes how people feel and act.
    0:09:22 And to me, that’s where the startup wins
    0:09:24 is when they do that.
    0:09:25 There’s two ways to look at the future.
    0:09:26 Do you believe it’s gonna be a new
    0:09:28 and improved version of the present?
    0:09:31 In which case the incumbents are gonna usually win that.
    0:09:33 Or do you believe that the future is not gonna be able
    0:09:35 to be reconciled with the present?
    0:09:37 In which case the startup can win.
    0:09:40 And by the way, you work for a guy who’s the master at this
    0:09:42 and he did it even in a big company.
    0:09:45 So like Steve Jobs, when he comes back to Apple,
    0:09:48 everybody says, hey, you should license the Mac OS
    0:09:51 and run it on Intel and you should have a clone market
    0:09:54 just like Microsoft and IBM do and all this stuff.
    0:09:56 Jobs didn’t do that.
    0:09:59 Jobs always found a way to change the subject.
    0:10:01 With the iPod, he found this inflection
    0:10:03 in the sense of a tiny little hard disk
    0:10:06 that he could put into a music player.
    0:10:09 And with the iPhone, he waited until the technology was ready
    0:10:11 that the touch screen was good enough
    0:10:13 and that the power in the phone was good enough
    0:10:16 that he could put Mac OS in a phone device.
    0:10:20 But Jobs never competed by being better at something.
    0:10:23 He always competed by showing up
    0:10:24 with something radically different
    0:10:26 and helping the rest of us understand
    0:10:28 what was important about it.
    0:10:30 And he did that by harnessing inflections.
    0:10:32 He just naturally knew how to do that
    0:10:34 because he knew that was his weapon
    0:10:36 to sort of change the discussion.
    0:10:39 – So let’s talk about what I consider
    0:10:42 maybe the biggest inflection certainly in my career.
    0:10:45 And I might argue in the history of mankind,
    0:10:48 which is artificial intelligence.
    0:10:53 And it seems to me that, you know, I use chat, GBT,
    0:10:58 I use Claude, I use Perplexity, I use four or five LLMs.
    0:11:01 And for the life of me, I cannot tell you why
    0:11:04 I use one or over the other.
    0:11:08 If you were to talk to the CEO of Claude or Perplexity
    0:11:09 and you would tell them like,
    0:11:12 listen, you’re just doing something better.
    0:11:14 Maybe your model is better or something,
    0:11:16 but you are not fundamentally changing.
    0:11:19 How does Perplexity or Claude compete
    0:11:22 against Gemini in Google?
    0:11:26 I just don’t see how they differentiate.
    0:11:27 – Yeah, it’s interesting.
    0:11:30 And I love this question because it highlights
    0:11:32 a real challenge I think right now,
    0:11:35 which is yes, you want an inflection,
    0:11:37 but you also want to have an insight.
    0:11:39 It’s not enough to just have a powerful idea.
    0:11:41 If a whole bunch of other people have
    0:11:43 that same powerful idea,
    0:11:47 then the opportunity gets somewhat competed away.
    0:11:49 You want to be non-consensus and right.
    0:11:51 So if we go back to the example of Lyft
    0:11:54 and then we can relate it to AI, I suppose,
    0:11:57 the iPhone 4S had an inflection
    0:12:02 in terms of empowering people to locate riders and drivers.
    0:12:06 But the founders of Lyft and Uber had to have the insight
    0:12:07 that, oh, that means you could create
    0:12:11 a transportation network that has network effects.
    0:12:14 And that’s where the creativity of the founder comes in.
    0:12:16 And now it’s obvious.
    0:12:18 Now people are like ride-sharing, of course.
    0:12:20 But at the time, it seemed crazy.
    0:12:22 Like, who’s going to get in a stranger’s car?
    0:12:23 They’re like, nobody’s going to do that.
    0:12:24 That’s crazy.
    0:12:27 Just like, who’s going to stay in a stranger’s house?
    0:12:28 That’s crazy.
    0:12:30 And so most of the great startups,
    0:12:33 they have to have an insight because
    0:12:35 if human beings are conditioned to like things,
    0:12:37 and so if everybody likes your idea,
    0:12:40 it’s too similar to what they already know,
    0:12:42 which means it’s too much of an incremental improvement.
    0:12:45 It’s too much competing on better versus different.
    0:12:46 So the best startup ideas I’ve seen
    0:12:50 have this quality of most people don’t like it at first
    0:12:51 or don’t think it’s going to work
    0:12:54 or they think it’s irrelevant.
    0:12:56 But there’s a small subset of people who are like,
    0:12:58 oh, my gosh, where have you been all my life?
    0:12:59 I’ve seen the light.
    0:13:00 This is amazing.
    0:13:01 You want that.
    0:13:03 You want to be non-consensus and right.
    0:13:04 It’s not enough just to be right.
    0:13:06 You have to be non-consensus and right.
    0:13:10 So when I back to perplexity and Claude and these guys,
    0:13:12 I don’t really think of them as startups
    0:13:15 in the way that maybe you and I think of startups.
    0:13:18 The way I think of perplexity and those guys
    0:13:20 is I think of them more as like small versions
    0:13:22 of big companies.
    0:13:25 And if I think about those companies,
    0:13:30 they’re not really trying to, in a capital efficient way,
    0:13:34 create some asymmetrically radically difference.
    0:13:36 They’re partnering with the big tech companies
    0:13:38 to create scalable technology.
    0:13:40 And I think it just happens to be
    0:13:44 that right now, small versions of big tech companies.
    0:13:47 But I don’t think of chat GPT and Claude and those guys
    0:13:49 as like startup capitalists.
    0:13:52 I think of them as probably someday a large division
    0:13:53 of a big tech company.
    0:13:55 We just don’t know which one yet.
    0:13:58 In a sense, even though what they do is so exciting,
    0:14:02 it sounds kind of boring when you put it that way.
    0:14:03 I think what they’re doing is great.
    0:14:06 I just don’t think of them as startup people
    0:14:09 in the same way that I thought of the Lyft guys
    0:14:10 or the Twitter folks, right?
    0:14:12 I think of them as more like back in the day
    0:14:14 when you’d have these joint ventures
    0:14:17 between IBM and Apple or when you’d have big companies
    0:14:18 spinning off divisions and stuff like that.
    0:14:20 I think of it as more like that
    0:14:23 than I think of it as classic startup capitalism.
    0:14:28 – So with all this talk about the entrepreneurs,
    0:14:31 the true entrepreneurs who are creating
    0:14:34 or writing this inflection point,
    0:14:37 I guess my big question for you, Mike,
    0:14:41 is how do you separate the nutcases
    0:14:42 from the pattern breakers?
    0:14:45 Because at the time you hear some of these pitches,
    0:14:48 you must think these people are nuts.
    0:14:50 And then five years later, you say,
    0:14:51 “Oh, they were so right.”
    0:14:53 So how do you figure that out?
    0:14:55 Who are the nutcases and who are the breakers?
    0:14:57 – Yeah, and it’s funny, like some books
    0:15:02 are born of experience and competence and expertise.
    0:15:06 This book that I wrote started more out of embarrassment,
    0:15:07 right?
    0:15:08 I had passed on air bed and breakfast,
    0:15:10 which became Airbnb.
    0:15:13 And I would have made like thousands of times of money
    0:15:15 if I’d done it.
    0:15:17 And then I noticed that 80% of my exit profits
    0:15:18 had come from pivots.
    0:15:23 So Twitter had started as a podcasting company called Odio.
    0:15:25 Twitch had started out as a terrible idea
    0:15:27 called Justin.tv.
    0:15:28 And so I’m looking at this and I’m like,
    0:15:30 “What business am I even in here?
    0:15:31 What am I doing?
    0:15:32 Am I just throwing darts?
    0:15:35 Should I just retire before I get exposed?”
    0:15:36 And what I started to realize was
    0:15:38 that these startup ideas that were working,
    0:15:40 they were harnessing inflections
    0:15:42 and they were non-consensus and right.
    0:15:44 Now, here’s the tricky part,
    0:15:45 and it gets to your question, I think,
    0:15:48 which is when you’re non-consensus and right,
    0:15:51 you don’t know that you’re right at first.
    0:15:52 You only know that you’re non-consensus.
    0:15:55 If you knew you were right, it would be too obvious.
    0:15:57 And so the less obvious it is,
    0:15:59 the less you can know for sure that you’re right.
    0:16:03 So on some level, you have to try the idea.
    0:16:04 You have to decide,
    0:16:07 I don’t know if I’m 100% right yet,
    0:16:10 but this is a non-consensus area that’s worth pursuing.
    0:16:14 It’s worth my energy and time to figure out.
    0:16:16 And if I’m not 100% right, I might pivot.
    0:16:19 So how do you tell the difference?
    0:16:21 What’s the right kind of crazy?
    0:16:22 What’s the wrong kind of crazy?
    0:16:25 The question I like to ask is,
    0:16:27 is this from the future?
    0:16:28 And I think William Gibson,
    0:16:31 the cyberpunk author was right when he said
    0:16:32 the future’s already here,
    0:16:34 it’s just not evenly distributed.
    0:16:37 For example, when Mark Andreessen worked
    0:16:41 on the Mosaic browser at the University of Illinois,
    0:16:44 he was in a supercomputer lab with a really fast network
    0:16:45 and powerful computers.
    0:16:49 His idea of what networks were gonna be
    0:16:52 was a better version of the future
    0:16:54 than Microsoft’s top-down or AOL
    0:16:57 or the US government or AT&T or Time Warner’s view
    0:16:58 of a tops-down network.
    0:17:01 I think that the way you know
    0:17:04 that a non-consensus idea is worth pursuing
    0:17:07 is the authenticity of the founder
    0:17:09 to that future that they’re pursuing.
    0:17:11 I think that if you’re living in the future
    0:17:13 before other people,
    0:17:15 and you’re harnessing powerful inflections
    0:17:17 before other people,
    0:17:19 the odds that you’re gonna build the right thing
    0:17:22 are much higher to be correct.
    0:17:24 And so that your intuition about what to build
    0:17:26 is far more likely to be right.
    0:17:28 And so that’s what I really look for is,
    0:17:31 I wanna know is this founder living in the future
    0:17:33 for the rest of us?
    0:17:36 Are they intrinsically motivated by that future?
    0:17:39 Are they just pursuing what they think is hot?
    0:17:43 And do they have insights about what to build
    0:17:47 because of their authentic obsession with that future?
    0:17:51 And I believe that that causes you to be more likely
    0:17:53 to build the right thing,
    0:17:55 but it also makes you more credible to early believers.
    0:17:57 It causes other people to say,
    0:18:00 hey, I agree that this guy Kawasaki guy
    0:18:02 with this asius relational database here,
    0:18:04 I think he’s noticed something
    0:18:05 that others haven’t noticed.
    0:18:07 And I wanna join that movement.
    0:18:10 And I remember this from when you were a founder.
    0:18:14 I think in your database at fourth dimension,
    0:18:15 tell me if I’m wrong about this,
    0:18:18 but your contacts, you would have a tag next to them.
    0:18:21 And one of the tags was like true believer.
    0:18:24 And Joe Lemont, my roommate college,
    0:18:26 you had tagged him as a true believer.
    0:18:29 And so that’s like these early startup markets
    0:18:32 are animated by belief, not utility, right?
    0:18:35 People buy from startups for aesthetic reasons,
    0:18:36 not practical reasons.
    0:18:38 And they do it because they co-create the future
    0:18:39 with the founders.
    0:18:42 It’s the early believers that do that with the founders.
    0:18:45 And it’s the belief in a different
    0:18:48 but aesthetically superior future
    0:18:51 that drives people to move the present
    0:18:53 to a different future together.
    0:18:55 And so that’s what I’m looking for, right?
    0:18:57 I want the idea that’s not consensus,
    0:18:59 but I wanna believe that the person comes
    0:19:02 by the idea honestly, that they come by it
    0:19:06 by authentically pursuing a future that I can get mine.
    0:19:08 (upbeat music)
    0:19:27 – So today in artificial intelligence,
    0:19:32 do you have any examples of this non-consensus
    0:19:36 kind of inflection idea?
    0:19:39 – Yeah, so I’d say that AI has been really challenging
    0:19:42 for me because I see inflections every week,
    0:19:46 but somebody shows up and says I have this great idea.
    0:19:49 And I’m like, I would totally use that product,
    0:19:52 but I don’t know why there’s not gonna be 10 just like it,
    0:19:54 which means it doesn’t have enough of an insight.
    0:19:57 So I’ll give an example of one that I think does.
    0:20:00 So I’m involved with this company called Applied Intuition,
    0:20:04 and they make autonomous vehicle simulation software
    0:20:09 and software-defined platforms for the car companies.
    0:20:12 And so let’s say your General Motors or Porsche
    0:20:15 or you’re one of these big car companies,
    0:20:19 Tesla has a software-defined car and you don’t really,
    0:20:21 and you don’t really know how to build it,
    0:20:23 and you don’t really know how to,
    0:20:26 the electric vehicles are more like a software platform
    0:20:30 architecture versus a supply chain with a bajillion suppliers
    0:20:33 that you’ve all done business with for 50 years.
    0:20:36 And so Casar, you and I started this company
    0:20:39 with some friends of his from Google.
    0:20:41 And so they’d grown up in Detroit.
    0:20:43 Casar had worked at General Motors
    0:20:45 after graduating from undergrad.
    0:20:48 Then he went to Silicon Valley, was at Google for a while,
    0:20:50 worked on the Google Maps team,
    0:20:52 knew all the guys at Waymo.
    0:20:56 And so he can go to the CEO of a company like Porsche
    0:20:59 and say, hey, if you wanna have a software-defined car,
    0:21:01 I’m your only path to getting there.
    0:21:03 You don’t have the internal talent.
    0:21:06 I have the best developers in the world
    0:21:07 tackling this problem.
    0:21:11 And you can only get this talent if you do business with me.
    0:21:14 And now is Sam Altman gonna release a new version of chat
    0:21:15 GPT that does that?
    0:21:17 No, right, because he’s not in the business
    0:21:19 of creating software-defined cars.
    0:21:22 Those are examples of businesses I like
    0:21:24 because it involves deep technology,
    0:21:29 but it involves a multidisciplinary approach.
    0:21:30 You have to not just be good at the AI,
    0:21:32 but you have to be able to speak the language
    0:21:33 of the car companies.
    0:21:36 And you have to be able to implement systems
    0:21:38 at global enterprise scale
    0:21:41 and help the customer reach the promised land.
    0:21:44 And it’s very strategic to these car companies.
    0:21:45 They know they have to move in the direction
    0:21:47 of being a software-defined car.
    0:21:50 And so that’s the kind of stuff I’ve been seeing lately
    0:21:52 that I get excited about.
    0:21:55 But what if somebody says there’s only 25 major car companies
    0:21:56 in the world?
    0:21:59 How big is the market, Mike?
    0:22:00 Yeah, and in that case,
    0:22:03 you have to be able to get giant contracts, right?
    0:22:05 You have to have individual customers
    0:22:07 in the hundreds of millions of dollars
    0:22:09 to make that business work.
    0:22:10 But you can, right?
    0:22:12 Bosch doesn’t have that many customers in the car industry,
    0:22:15 but they probably do about $50 billion a year
    0:22:16 selling to the car companies.
    0:22:18 And so if you become the complete answer
    0:22:20 to something that company cares about,
    0:22:22 you can do pretty well.
    0:22:25 But companies aren’t just gonna give $100 million
    0:22:27 to just some bozo, right?
    0:22:29 They’re not gonna give you a giant contract
    0:22:31 unless they think you can really do the job
    0:22:32 and you’re the only guy that can do it.
    0:22:35 And so you have to have a particular set of skills
    0:22:38 that people buy into, or it’s gonna be hard.
    0:22:41 I don’t wanna really catalyze PTSD in you,
    0:22:43 but can you discuss the cases
    0:22:46 where you had a false positive?
    0:22:49 In other words, that you thought someone was a pattern breaker,
    0:22:52 but after all, didn’t?
    0:22:54 Oh, sure, in fact, it’s most of the time.
    0:22:57 My business is very strange.
    0:23:01 Warren Buffett, I’ve heard him say rule number one,
    0:23:02 don’t lose money.
    0:23:05 Rule number two, don’t forget rule number one.
    0:23:08 For me, rule number one is don’t pass on Airbnb.
    0:23:09 If I had been wrong about Airbnb,
    0:23:11 I could only lose 100% my money.
    0:23:12 But if you’re right,
    0:23:15 you can sometimes make a thousand times or more.
    0:23:18 Buffett talks about his margin of safety.
    0:23:22 What I care about is my margin of asymmetric upside, right?
    0:23:24 I care about how big could it be
    0:23:26 in the rare event that it works.
    0:23:28 So I have this really weird way
    0:23:30 of coming up with an investment thesis.
    0:23:33 I’m like, okay, given that it’s 80% likely I’m wrong,
    0:23:36 how big does it need to be if I’m right?
    0:23:39 And if it can’t be big enough,
    0:23:41 no matter what the odds are,
    0:23:42 I just can’t invest in it
    0:23:45 because I have to get paid for the risk I take, right?
    0:23:47 I’m taking crazy high risk.
    0:23:48 And so I’m like, you know,
    0:23:51 unlike say Buffett who never wants to lose money,
    0:23:53 I’m saying to myself, okay,
    0:23:57 given that it’s 80% likely I’m gonna lose money,
    0:24:00 in the 20% case, how big does it need to get?
    0:24:02 Which is just a different way of showing up in the world, right?
    0:24:05 It’s a different way of thinking about success.
    0:24:10 So I don’t look at risk as the chance of success or failure.
    0:24:12 I think of risk through an expected value lens.
    0:24:15 I’m like, okay, in the 20% case it’s right,
    0:24:16 how big does it need to be
    0:24:18 to be a good expected value bet,
    0:24:20 even though it’s risky.
    0:24:23 – What if at the moment of making an investment,
    0:24:25 it’s really not an assessment
    0:24:28 of how big can something be
    0:24:32 because you don’t know what this company’s gonna pivot to,
    0:24:33 right?
    0:24:35 So when you talk about Justin TV,
    0:24:40 you couldn’t do an analysis of how big Justin TV would be,
    0:24:44 but when Justin TV pivoted to Twitch, then you could,
    0:24:47 but that wasn’t at the point of investment.
    0:24:50 So how do you factor in the pivots?
    0:24:52 – Yeah, and so the way I do it is,
    0:24:55 I like to say, I don’t wanna study
    0:24:57 the total addressable market
    0:24:59 for the reason that you mentioned, right?
    0:25:03 What I believe is that companies that harness inflections
    0:25:04 define new markets.
    0:25:07 And I can’t size a future market, right?
    0:25:09 Future hasn’t happened yet.
    0:25:11 So what I need to do is it reminds me in physics,
    0:25:14 you have potential energy and mechanical energy.
    0:25:18 And what I’m looking for is a future potential market.
    0:25:21 And I believe that big future potential markets happen
    0:25:23 from powerful inflections.
    0:25:26 So the more powerful the inflection is,
    0:25:29 the more capacity it has to change the future.
    0:25:32 And the more capacity it has to impact the future
    0:25:33 in a broad way.
    0:25:36 And so what I do is I take a leap of faith.
    0:25:40 I say, based upon this inflection, based upon this insight,
    0:25:42 and based on the founders’ authentic match
    0:25:44 to the future they’re pursuing,
    0:25:46 I think the odds are in my favor.
    0:25:50 I don’t have to know exactly how the dots will connect.
    0:25:53 I only have to think that the odds are highly probable
    0:25:56 that the founder will find a way to connect those dots.
    0:25:57 I love this job saying,
    0:25:59 you can only connect the dots looking backwards.
    0:26:01 And I think that’s what he was getting at, right?
    0:26:06 You’re pursuing opportunities that are ambiguous,
    0:26:09 but that doesn’t mean they’re not a risk worth taking.
    0:26:11 And so you’re betting on the founder’s ability
    0:26:15 to navigate their insight to the right product proposition.
    0:26:17 To the example that you gave with Twitch,
    0:26:18 JustinTV is a terrible idea,
    0:26:20 but they navigated the idea to Twitch,
    0:26:22 which was a great idea.
    0:26:24 But the inflections, the underlying inflections
    0:26:26 were always there from the very beginning.
    0:26:28 – Now, what about false negatives
    0:26:31 where you turned down somebody and they turned out great?
    0:26:33 What have you learned about why you made
    0:26:35 false negative decisions?
    0:26:37 – To me, those are the biggest errors in my business.
    0:26:40 Passing on air bed and breakfast at the time
    0:26:41 was a terrible idea.
    0:26:43 I’ve passed on other good ones too.
    0:26:45 We passed on Pinterest early.
    0:26:49 We passed on a company called Anaplan, passed on Figma.
    0:26:52 And so whenever we pass on these,
    0:26:54 in fact, whether I saw them or not,
    0:26:58 I keep this database if I call them 100 bag or startups.
    0:27:01 So I have this list of a little over a hundred companies
    0:27:02 and I study them.
    0:27:05 I create a time capsule of what it looked like
    0:27:07 at the seed round.
    0:27:10 So I have the seed deck from Pinterest and Dropbox
    0:27:13 and Airbnb and all these companies.
    0:27:14 And I look at it and I say to myself,
    0:27:17 okay, where was the signal?
    0:27:20 What was the thing that would have told you to say yes?
    0:27:24 And why did I have a failure of imagination and say no?
    0:27:27 And with Airbnb, my failure of imagination was,
    0:27:30 I thought people aren’t gonna want to stay
    0:27:31 in a stranger’s house.
    0:27:32 That’s crazy, right?
    0:27:34 And it was around the time that Craigslist killer,
    0:27:35 I was like, somebody’s gonna get killed
    0:27:36 in one of these things.
    0:27:38 And it was a screwed up meeting.
    0:27:40 Brian couldn’t get the site to work in our meeting.
    0:27:42 He had a room full of cereal boxes.
    0:27:44 He was trying to sell me Obama O’s
    0:27:45 and Captain McCain Crunch.
    0:27:48 And so that’s the other thing I learned
    0:27:50 is sometimes the pitch doesn’t go well,
    0:27:52 but that doesn’t mean it’s not gonna succeed.
    0:27:55 So I try to go back in time.
    0:27:56 The other thing I’ve learned, Guy,
    0:27:59 is that even the founders misremember how to happen
    0:28:00 a lot of the time, right?
    0:28:01 And so when it works,
    0:28:04 everybody remembers the stuff they knew
    0:28:05 and the good decisions they made.
    0:28:08 But a lot of times they know things that weren’t so
    0:28:10 at the time.
    0:28:13 And so you have to be almost like Joe Colombo detective,
    0:28:14 right?
    0:28:16 You do a forensic analysis of what it looked like
    0:28:17 at the time.
    0:28:19 And then you got to ask yourself,
    0:28:21 do any of the frameworks that we use
    0:28:23 to evaluate these things,
    0:28:25 would they have been useful here?
    0:28:26 Would they have caused us to say yes,
    0:28:28 or are we just breathing our own fumes?
    0:28:31 Do we believe a bunch of stuff about what’s true
    0:28:32 in the world that just didn’t true
    0:28:35 or doesn’t capture the reality of this situation?
    0:28:36 That’s what I try to do.
    0:28:40 I try to go back in time and really understand it.
    0:28:42 There’s a lot of things you can do to understand it.
    0:28:44 You can look at the initial seed pitch deck
    0:28:45 and you can say,
    0:28:47 is that what the product ended up being?
    0:28:49 Or did it end up being something different?
    0:28:51 How long did it take for them to get to a million revenue,
    0:28:53 10 million, 100 million revenue?
    0:28:54 What caused that?
    0:28:56 What kind of business model was it?
    0:28:59 What was the defensible mode that they created?
    0:29:02 You could start to kind of look for the signals
    0:29:04 that would have clued you in that,
    0:29:06 “Hey, this is a bet we’re taking.”
    0:29:09 – I have not done what you just described
    0:29:14 in any form as organized or rational or careful as you,
    0:29:16 but my conclusion,
    0:29:20 the more I am in Silicon Valley and around tech startups,
    0:29:24 my conclusion is coming to that the older I get,
    0:29:25 the less I know,
    0:29:27 and I could almost make the case
    0:29:29 that you should just invest in the stupidest things
    0:29:31 that come across your deck
    0:29:34 because that’s the ones that’s gonna succeed.
    0:29:37 I cannot figure this out.
    0:29:39 I would have never invested in,
    0:29:40 as you say,
    0:29:41 you’re gonna let a stranger stay in a house,
    0:29:44 you’re gonna let a stranger rent your car,
    0:29:46 you’re gonna let a stranger ride with you,
    0:29:48 you would get in a stranger’s car,
    0:29:50 get in a stranger’s house,
    0:29:53 you would take a stranger’s tour or rental.
    0:29:56 I would do none of those and look at that.
    0:29:59 I’d be zero for three right there.
    0:30:00 – Yeah, it’s tough, right?
    0:30:02 And it’s a humbling game for sure.
    0:30:04 And the other thing about it,
    0:30:07 guy is like massive success is one Airbnb away, right?
    0:30:11 You get one of those every 10 years, you’re really good.
    0:30:12 It is a humbling game,
    0:30:16 but like for me, it’s just so darn interesting, right?
    0:30:19 We know a whole lot about business now,
    0:30:20 but a hundred years ago,
    0:30:23 there were no org charts and there wasn’t accounting
    0:30:26 and there wasn’t corporate strategy as we know it.
    0:30:28 There wasn’t Michael Porter Five Forces,
    0:30:30 there wasn’t any of this stuff.
    0:30:32 All that stuff had to be figured out.
    0:30:34 And I think we’re at the beginning of infinity
    0:30:37 of really understanding startup capitalism.
    0:30:39 And so I just think a startup capitalist
    0:30:40 is a different type of capitalist.
    0:30:44 They don’t create value by persistently compounding
    0:30:46 an advantage like a big company does.
    0:30:50 They create value by doing something radically different.
    0:30:51 And that’s another way to show up in the world
    0:30:53 and be valuable.
    0:30:56 And so I just think there’s so much to learn about that.
    0:30:58 When I think that just like there’s a process
    0:31:01 for building a great company that’s a going concern,
    0:31:05 I think that there are processes and patterns
    0:31:07 that can be understood about what it takes
    0:31:10 to create a great startup that changes the future.
    0:31:12 And there’s so little that’s known about it.
    0:31:14 So we’re having this conversation right now, right?
    0:31:16 It seems kind of random, right?
    0:31:19 It seems like trying to predict the weather or something.
    0:31:21 But to me, that’s what makes it so interesting
    0:31:23 is it’s so hard to figure out
    0:31:25 that it’s worth trying to figure out.
    0:31:28 – I tell you, Mike, as I get older and older,
    0:31:30 my strategy is get lucky,
    0:31:34 but get lucky is not a good strategy.
    0:31:35 – That’s pretty good sometimes.
    0:31:40 – So I’m gonna take you down a rat hole
    0:31:42 and you can tell me we don’t wanna go down this rat hole,
    0:31:45 but you have the data to know these people
    0:31:46 better than most people.
    0:31:51 So I look at the current Mark Andreessen,
    0:31:56 the current Elon Musk, the current Mark Zuckerberg.
    0:31:59 And I ask myself, what happens to these people?
    0:32:01 These people started off trying to make the world
    0:32:05 a better place, democratizing, computing,
    0:32:07 freedom of information, all that.
    0:32:10 And now they turn into these MAGA people
    0:32:13 and you got any thoughts about what happens?
    0:32:17 Is it age or is it when you start being worth
    0:32:19 a billion dollars or more or something just happens in you?
    0:32:22 What happens to these people?
    0:32:23 – Let’s see.
    0:32:26 So I’m gonna tread carefully on the political questions.
    0:32:27 – Why?
    0:32:29 – But I mean, I guess we could talk about it some.
    0:32:33 But one thing that I’ve observed in a lot of these folks
    0:32:36 is that they tend to be disagreeable.
    0:32:39 When you think about it, a startup
    0:32:41 is a fundamentally provocative act.
    0:32:43 It’s a disagreement with the present.
    0:32:46 You’re showing up as a founder and you’re saying,
    0:32:49 hey, the way you think the world is, I’m challenging that.
    0:32:52 The way you think the world is, that’s not how it’s gonna be.
    0:32:53 It’s not gonna be about taxis anymore.
    0:32:54 It’s gonna be about ride sharing.
    0:32:57 It’s not gonna be about cars with drivers.
    0:32:58 It’s gonna be autonomous vehicles.
    0:33:00 It’s not gonna be gas, ice cars.
    0:33:02 It’s gonna be electric vehicles.
    0:33:04 Yes, I am gonna start a company
    0:33:06 that blasts rockets into outer space.
    0:33:08 Even though my competition is the US government
    0:33:11 and they have an infinite supply of money that they can print.
    0:33:14 These people tend to be disagreeable.
    0:33:16 And by that, I don’t just mean being a jerk.
    0:33:19 They tend to just be willing to disagree.
    0:33:23 Justin Kahn, before he started Justin TV,
    0:33:25 he started a calendaring company
    0:33:28 and Google launches a Google calendar.
    0:33:31 And Justin decides to sell the company on eBay.
    0:33:33 And I was like, I didn’t even know it’s possible
    0:33:34 to sell a company on eBay.
    0:33:36 Full distinct for $250,000.
    0:33:38 Some of the disagreeableness is just the willingness
    0:33:42 to be unconventional in how you pursue your ideas
    0:33:43 and your mission.
    0:33:47 I think that Elon is naturally disagreeable.
    0:33:48 There are aspects of disagreeableness
    0:33:50 that people don’t like,
    0:33:52 but if you make the diamond,
    0:33:54 not have the properties of the diamond,
    0:33:56 it won’t cut glass anymore, right?
    0:33:57 I think that most of these people
    0:33:59 who create these outlier results,
    0:34:01 they’re not normal people.
    0:34:03 And they’re not normal in ways
    0:34:05 that change the world for the better.
    0:34:06 And they’re not normal in ways
    0:34:08 that some people may not like.
    0:34:11 But like Elon said on Saturday Night Live that time,
    0:34:13 he’s like, I blast rockets into outer space.
    0:34:16 I’m trying to change humanity.
    0:34:18 Did you expect me to be a normal chill dude?
    0:34:19 He’s just not gonna be.
    0:34:21 That’s not who he is.
    0:34:24 And so I’ve kind of learned that these people
    0:34:26 don’t end up fitting neatly into a box
    0:34:28 that you wish they would fit into.
    0:34:30 And I imagine that you’ve known some founders,
    0:34:33 you knew Steve Jobs way better than I ever would have.
    0:34:35 But I imagine there were things that Steve did
    0:34:38 that probably maybe you wish he didn’t do.
    0:34:39 But it is what it is.
    0:34:41 It comes with a territory.
    0:35:02 I wanna end up with kind of a,
    0:35:05 just like a quick series of questions.
    0:35:07 I’m assuming that many entrepreneurs
    0:35:08 are gonna listen to this podcast
    0:35:11 and your legitimate successful VC,
    0:35:14 they probably would love to be in front of you.
    0:35:16 So just some quick questions,
    0:35:19 very tactical and practical for an entrepreneur.
    0:35:21 So question number one is,
    0:35:23 how do people get to a VC?
    0:35:26 Do they like send out 2,000 emails?
    0:35:28 But how do people get to you?
    0:35:31 The best way is to get a referral
    0:35:33 from somebody that we respect.
    0:35:36 And people tend to trivialize that discussion.
    0:35:38 So people tend to say that just means
    0:35:40 that whoever has the best network wins
    0:35:42 and there’s gonna be certain people
    0:35:45 who get excluded from being entrepreneurs.
    0:35:46 But there’s a reality guy,
    0:35:49 which is if you’re starting a startup,
    0:35:52 you have to convince people to join your movement.
    0:35:55 And if you’re sitting out there in the future by yourself
    0:35:56 and nobody joins your movement,
    0:35:58 that future is not gonna happen.
    0:36:01 And so to me, it’s not a function
    0:36:03 of how well connected you are.
    0:36:06 Getting an intro from someone I respect
    0:36:10 is a function of your ability to persuade somebody credible
    0:36:12 that your future matters.
    0:36:14 And that other people are gonna wanna join you
    0:36:15 in that future.
    0:36:17 And so, yeah, something could come over the transom,
    0:36:19 but how am I supposed to know?
    0:36:21 How am I supposed to know how good they are?
    0:36:25 I’ve gotta find some way to validate
    0:36:29 that their ideas about the future make sense
    0:36:30 to credible people.
    0:36:32 And by the way, it doesn’t have to be like Reed Hoffman
    0:36:34 or Mark Andreessen that makes the intro.
    0:36:37 It could be you’re living in a certain future
    0:36:39 in synthetic bio,
    0:36:42 and it’s a scientist who’s very credible in that area
    0:36:44 is like this is one of the most amazing things
    0:36:45 I’ve ever seen.
    0:36:49 And so I just need some signal from the future
    0:36:53 that’s valid, that validates the idea and the insight.
    0:36:55 I’d say that’s the key thing.
    0:36:59 If your insight is starting to get traction,
    0:37:01 that should be a solvable problem, right?
    0:37:02 There should always be somebody credible
    0:37:05 who embraces the idea, who’ll make the intro.
    0:37:09 So I’d say that that’s the primary thing that we look for.
    0:37:11 – Okay, next question.
    0:37:12 What do you want in the pitch?
    0:37:15 What’s the content of the pitch?
    0:37:18 – Okay, yeah, so I’ll give some super tactical advice on that.
    0:37:22 All things being equal, I like to say slide number one,
    0:37:26 say what you do as if I know literally nothing.
    0:37:29 You don’t say we’re Airbnb,
    0:37:34 we’re a marketplace for unused residential housing space.
    0:37:35 I don’t know what that is.
    0:37:38 That’s jibber jabber jargon.
    0:37:40 What you want to say is something like,
    0:37:44 we’re Airbnb, we let you read an extra room in your house.
    0:37:46 And here’s why that’s important.
    0:37:49 A lot of times you’ll get a pitch
    0:37:53 and your 10 slides in, I don’t know what the startup does still.
    0:37:56 And that’s hard to process, right?
    0:37:58 And I’m sympathetic to founders on this front
    0:38:01 because they get advice, they get bad advice.
    0:38:03 They get advice that says millennials are a thing,
    0:38:05 put that slide up front.
    0:38:08 Marketplaces are a thing, talk about marketplaces.
    0:38:10 And I’m 10 minutes in, I don’t know what you do yet.
    0:38:14 So slide number one is what do we do is if I know nothing?
    0:38:17 Slide number two is what do I know
    0:38:19 about the future that’s not obvious?
    0:38:22 Is really your chance to convey the insight?
    0:38:25 Slide number three is anything impressive
    0:38:28 that’s happened so far objectively?
    0:38:32 Customers, patents, letters of intent,
    0:38:37 just some proof that people in the world care about this thing
    0:38:40 and that they’re joining the movement and signing up.
    0:38:41 What I find is that the founder
    0:38:46 can get those three things right quickly, 10 minutes in.
    0:38:49 Now the venture capitalist is leaning forward.
    0:38:52 Now, it’s funny, I think we rift on this earlier.
    0:38:56 What happens too often is founders get bad advice.
    0:38:59 And so they create what I like to call a Franken Deck.
    0:39:01 And so what happens is they’ll pitch their advisor
    0:39:03 and the advisor wants the best for them.
    0:39:05 They’ll say, hey, VCs love marketplaces
    0:39:07 ’cause they have network effects.
    0:39:09 Don’t say you rent an extra room in your house.
    0:39:12 Say we’re marketplace for residential real estate
    0:39:15 ’cause marketplace, hot network effect,
    0:39:17 those are the real estate big.
    0:39:18 Okay, put that in there.
    0:39:20 And then the founder say, oh yeah, you’re right,
    0:39:21 okay, I’ll do that.
    0:39:23 And then they’ll say the other thing is
    0:39:25 this is an appealing service for millennials.
    0:39:27 So you should have a few slides up front
    0:39:29 that talk about the importance of millennials
    0:39:31 and handcrafted experiences, all that stuff.
    0:39:34 And you haven’t talked about the total available market yet.
    0:39:35 So you ought to talk about that.
    0:39:37 You need a few slides on that.
    0:39:39 You need a few slides on the real estate market,
    0:39:41 residential– – You need AI in there too.
    0:39:43 – Today you’d say you need AI.
    0:39:46 And so then what happens is you go in
    0:39:50 with this deck of 20 slides and you pitch somebody
    0:39:54 and the VC passes partly ’cause they don’t know what you do.
    0:39:57 And then they give a reason in their pass note
    0:39:58 for why they passed.
    0:40:00 And it’s like, oh man, there’s another objection.
    0:40:02 I better have a slide that counters that objection.
    0:40:04 And so before you know what you have 30 slides,
    0:40:07 each of which is designed to anticipate
    0:40:09 and counter an objection.
    0:40:11 And what I like to say to founders is
    0:40:14 the only people that matter are the people
    0:40:15 who believe your insight.
    0:40:17 If a VC doesn’t believe your insight,
    0:40:18 they’re not gonna invest.
    0:40:21 There’s no way to overcome their objection.
    0:40:24 They’re not gonna invest no matter what until it’s proven.
    0:40:27 What you wanna find is the subset of people in this world
    0:40:28 who believe what you believe.
    0:40:30 That’s true of customers, it’s true of investors,
    0:40:32 true of early employees.
    0:40:35 Don’t waste any urges of energy on anybody else.
    0:40:37 And the problem with the Franken Deck is
    0:40:40 the person who was ready to believe doesn’t know what you do
    0:40:45 because they got confused by just how convoluted
    0:40:46 the pitch was.
    0:40:50 And that person was gonna be much more likely to say yes,
    0:40:51 if you just show up and say,
    0:40:54 we let you rent an extra room in your house,
    0:40:57 you’re gonna be able to do this because Facebook Connect
    0:41:00 lets hosts and guests know who each other are
    0:41:02 and people are used to online reviews
    0:41:03 and everybody’s connected.
    0:41:06 Millennials want these kinds of experiences and all that.
    0:41:08 That’s the conversation you need to have
    0:41:10 with the person who’s prepared to believe.
    0:41:12 And the person who’s not prepared to believe doesn’t matter
    0:41:14 because they’re not gonna do anything anyway.
    0:41:16 And so their opinion doesn’t matter either.
    0:41:18 This is the important point.
    0:41:20 The source of their objection doesn’t matter
    0:41:22 because they’re not gonna join your movement.
    0:41:24 Only those who are prepared to join your movement
    0:41:27 have valid input about your strategy.
    0:41:29 And that’s really important I find,
    0:41:31 is to say, hey, I’m only gonna spend time
    0:41:34 with the people I think are ready to move with me
    0:41:38 and I’m gonna bias my feedback collection
    0:41:39 to what they say.
    0:41:42 – I gotta tell you Mike, I gotta believe
    0:41:44 that many entrepreneurs listening to this,
    0:41:47 their heads are basically exploding
    0:41:51 because they’ve been hammered and I gotta take feedback.
    0:41:54 I gotta check off all the boxes and I gotta do all this.
    0:41:57 And basically you’re saying you got them in three slides
    0:41:59 and if you don’t get them in three slides,
    0:42:00 you’re never gonna get them.
    0:42:03 So just cut your losses, stop wasting time
    0:42:07 and go find somebody who does believe the three slides.
    0:42:10 – I think so and some people may disagree with me here,
    0:42:13 but when you think about it, it’s inspiring.
    0:42:16 When you realize that great ideas
    0:42:20 are usually disliked by most at first.
    0:42:21 By the way, that’s true of everything.
    0:42:24 That’s true of Euclidean geometry.
    0:42:27 It’s, you know, Copernicus, when he says the sun
    0:42:29 is at the center, not the earth,
    0:42:33 the pope puts him under house arrest and says,
    0:42:35 hey, maybe you ought to change your opinion about that.
    0:42:37 A lot of the great ideas in human history,
    0:42:39 you know, people when Einstein proposed
    0:42:40 the general theory of relativity,
    0:42:43 they’re like, this guy sounds like he’s smoking weed.
    0:42:47 That’s one of the most abstract, crazy things I’ve ever heard.
    0:42:52 And so most great ideas are heretical at first.
    0:42:57 And actually, if most people don’t like your startup idea,
    0:42:59 that’s a positive sign.
    0:43:03 If everybody liked your startup idea, it’s too incremental.
    0:43:06 When you realize that, it’s inspiring, right?
    0:43:09 When you realize, hey, given that most people
    0:43:12 are gonna dislike my idea, who cares about them?
    0:43:13 They don’t matter.
    0:43:16 They’re not creating the future, I am.
    0:43:19 I and my early believers are gonna create the future.
    0:43:21 They’re not gonna have a say in it.
    0:43:23 And so I need to go find who those people are
    0:43:25 and not waste a single urge of energy
    0:43:27 on anybody who’s not those people.
    0:43:29 And so what we wanna do is we wanna find the people
    0:43:32 who say, oh my gosh, where have you been all my life?
    0:43:33 This is amazing.
    0:43:36 I can’t wait to join your call to adventure
    0:43:38 and go do this with you.
    0:43:39 That’s what you’re looking for.
    0:43:42 And the people who aren’t ready to accept your call
    0:43:44 to adventure, their objections don’t matter
    0:43:47 because they don’t apply to your adventure, right?
    0:43:50 Only objections that matter are the objections
    0:43:53 from fellow believers because they help you see the future
    0:43:54 in a more clear way.
    0:43:59 – Mike, I have more questions,
    0:44:02 but there’s no question I’m gonna ask
    0:44:05 that’s gonna elicit an answer that is a better way
    0:44:08 to end this podcast than what you just said.
    0:44:10 So we’re gonna (laughs)
    0:44:11 – Okay, I like it.
    0:44:14 – I call this the casino theory
    0:44:16 and I often apply it to surfing.
    0:44:20 So I’ll tell you the casino theory of surfing and podcasting.
    0:44:23 So sometimes when you go to Las Vegas
    0:44:25 and you have 50 bucks in your pocket,
    0:44:29 you go to a casino and you bet it on blackjack or craps
    0:44:33 or whatever and just magically you have $500.
    0:44:37 So my casino theory is that most people have that $500
    0:44:40 and they keep playing until they lose it.
    0:44:42 But if you’re smart and you got lucky,
    0:44:45 you got 500 bucks, you walk out, right?
    0:44:49 You quit gambling, you walk out with the 500.
    0:44:51 So the casino theory of surfing is
    0:44:53 after you caught a great wave,
    0:44:54 don’t try to keep catching waves,
    0:44:56 you’re just gonna get disappointed.
    0:44:58 And the casino theory of podcasting is
    0:45:01 when you had a great answer like that,
    0:45:02 you don’t ask more questions,
    0:45:05 you just quit now and you end the podcast
    0:45:07 ’cause that was a great answer
    0:45:09 and all these entrepreneurs are on the world.
    0:45:11 They’re putting pieces of their brain back in their head
    0:45:14 because you just said something that’s contrary
    0:45:16 to what they’ve heard for the last two years.
    0:45:20 So that’s the way to end this podcast, Mike.
    0:45:22 – All right, I appreciate your taking the time guy
    0:45:24 and it’s great to see you
    0:45:26 and congrats on all the success you’ve had
    0:45:30 and many types of ways and scenarios, right?
    0:45:34 You’ve been a polymath when it comes to the tech industry.
    0:45:35 It was great to see you.
    0:45:38 – I wish I could say that I caused
    0:45:42 or really capitalized on inflections
    0:45:47 as much as some of the stories that you wrote about.
    0:45:49 And actually, if I think about it,
    0:45:50 at the start of my career,
    0:45:53 I got on the Macintosh inflection
    0:45:54 and at the end of my career,
    0:45:56 I got on the Canva inflection.
    0:45:58 And I gotta tell you, in both cases,
    0:46:01 I consider myself lucky, not smart.
    0:46:02 – Yeah, and it’s interesting.
    0:46:04 Probably you don’t wanna sell past the order
    0:46:06 like what you said, you wanna end on the right note.
    0:46:09 But the other thing about this surfing thing is,
    0:46:11 if you go after the right waves,
    0:46:13 you only have to be right once.
    0:46:15 And so that’s the way I look at it,
    0:46:17 is you wanna pursue opportunities
    0:46:19 where you only have to be right once
    0:46:22 because you’ll be spectacularly right.
    0:46:24 The only way to really lose in entrepreneurship
    0:46:26 is to lose your time.
    0:46:28 Pursuing something that you realize
    0:46:30 in hindsight wasn’t worthy of your talent and time.
    0:46:32 And so we wanna go after ideas
    0:46:35 that are waves that are worth surfing.
    0:46:36 Because like you said,
    0:46:38 if you catch the ideal wave, you did it.
    0:46:39 – Thank you, Mike.
    0:46:42 That was just a remarkable interview.
    0:46:43 I’m Guy Kawasaki.
    0:46:46 This is remarkable people and all you entrepreneurs
    0:46:50 who just had all your myths exploded.
    0:46:51 I empathize with you,
    0:46:54 but better you hear it now from Guy and Mike
    0:46:56 than you hear it two years from now
    0:46:59 after all these rejections and disappointments.
    0:47:02 So that’s how to be a remarkable entrepreneur.
    0:47:05 I wanna thank the rest of the remarkable people team.
    0:47:08 That’s of course, Matt as a Nismar producer,
    0:47:10 Tessa Nismar researcher,
    0:47:14 Luis Magana, Fallon Yates, and Alexis Nishimuro.
    0:47:16 We are the remarkable people team
    0:47:18 and we are hell bent for leather
    0:47:21 on a mission to make you remarkable.
    0:47:25 Until next time, Mahalo and Aloha.
    0:47:30 (orchestral music)
    0:47:32 This is remarkable people.

    Buckle up for a mind-bending journey into the heart of startup innovation! On this episode of Remarkable People, Guy Kawasaki goes deep with Silicon Valley’s master of disruption, Mike Maples Jr. As the wizard behind Floodgate who spotted Twitter and Twitch before they exploded, Mike shatters conventional wisdom about what makes startups soar. Forget everything you think you know about “better products” – Mike reveals why the craziest ideas often win big and why being dismissed might be your biggest advantage. Warning: this episode may permanently rewire your entrepreneurial brain!

    Guy Kawasaki is on a mission to make you remarkable. His Remarkable People podcast features interviews with remarkable people such as Jane Goodall, Marc Benioff, Woz, Kristi Yamaguchi, and Bob Cialdini. Every episode will make you more remarkable.

    With his decades of experience in Silicon Valley as a Venture Capitalist and advisor to the top entrepreneurs in the world, Guy’s questions come from a place of curiosity and passion for technology, start-ups, entrepreneurship, and marketing. If you love society and culture, documentaries, and business podcasts, take a second to follow Remarkable People.

    Listeners of the Remarkable People podcast will learn from some of the most successful people in the world with practical tips and inspiring stories that will help you be more remarkable.

    Episodes of Remarkable People organized by topic: https://bit.ly/rptopology

    Listen to Remarkable People here: **https://podcasts.apple.com/us/podcast/guy-kawasakis-remarkable-people/id1483081827**

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  • Chika Oriuwa: Poetry, Purpose, and Breaking White Coat Barriers

    Chika Oriuwa: Poetry, Purpose, and Breaking White Coat Barriers

    AI transcript
    0:00:14 I only know two Nigerians you and lovey. I don’t know if you know lovey. Oh, yes. Well,
    0:00:20 I don’t know her personally, but I follow her on social media. Very cool. Very cool.
    0:00:24 We once got into a whole discussion about Nigerian weddings and how they like go for
    0:00:33 three days and stuff. Did you have a Nigerian wedding like that? I did. It was a very lavish
    0:00:42 affair, you could say. It was massive and this was in 2022. So we were just not really
    0:00:45 coming out of the pandemic, but starting to get a little bit more socially comfortable
    0:00:52 with the new normal. And we had like 600 people at my traditional Nigerian wedding. I know
    0:00:58 I’m very proud of my Nigerian culture. I’m very proud of my Igbo culture. But still,
    0:01:04 it was a lot. And then I had our traditional Western wedding.
    0:01:11 One of the people who have been on this podcast is John M. Chu. And John M. Chu is a director
    0:01:17 of crazy rich Asians. So I could reach out to him and ask him if he wants to make crazy
    0:01:25 rich Nigerians and be you and love you. Oh my goodness. That would be a wild time.
    0:01:29 And you know, I would actually love to see Nigerians painted in that light in the sense
    0:01:37 of we’re not, I feel like a lot of African culture doesn’t always get painted or seen
    0:01:42 in that perspective of, you know, there’s absolutely affluence within African cultures.
    0:01:47 It’s there as well. So I think you might be tapping into a really interesting side.
    0:01:52 I mean, let’s face it. Most Americans think that Africa is a country, not a continent,
    0:01:53 right?
    0:01:59 Oh, yes. Yes. Yes. And that’s something that definitely, oh, it gets to me every time I
    0:02:00 hear people say that.
    0:02:05 So this initial discussion has been so funny. We’ll probably keep it in the podcast. But
    0:02:08 at some point I should introduce you.
    0:02:15 So I’m Guy Kawasaki. You’ve been already listening to the remarkable people podcast
    0:02:20 and we’re on a mission to make you remarkable. And today we have a remarkable guest who’s
    0:02:27 also been a Barbie role model. Her name is Chika Oriwa. She’s a remarkable person. She
    0:02:34 has a background in medicine. She was one out of 259 students who’s in the University
    0:02:41 of Toronto Medical School, and she’s an activist, a poet, and just kind of is outstanding in
    0:02:47 everything basically. So that’s why she’s on our podcast. So Chika, welcome to remarkable
    0:02:48 people.
    0:02:53 Thank you for having me here, Guy. And thank you for that introduction. I’m so honored.
    0:03:00 I think the honor is mine, but yeah, we won’t go there. So I have a question for you, one
    0:03:05 author to another because I’ve authored 16 books and I’m the one of the hardest things,
    0:03:12 if not the hardest thing about writing a book is figuring out the title, right? So I just
    0:03:18 want to know, having read your book, did you ever consider calling your book, even you
    0:03:22 as opposed to what you did call your book?
    0:03:28 So the origin story of the title is very interesting because when I was finishing writing up the
    0:03:33 book proposal, which I’m sure you’re very familiar with and getting that big massive
    0:03:38 document of the outline and the pitch and everything, I needed a title in order to submit
    0:03:42 it to the publisher. And I was like, oh, I don’t know what to put. Unlike the rest, I
    0:03:48 thought it was just going to be a placeholder. But then my agent loved it. My husband was
    0:03:51 like, this is a great title. And I was like, yeah, okay, well, we’ll just keep it there
    0:03:58 for now. But as I actually went to write the book, that phrase, even you, it was one of
    0:04:03 the most resonant, I would say, that it resonated with me, but it also resonated with a lot
    0:04:11 of the readers when they ended up also reading it. But I think if there was an alternate title,
    0:04:18 I would give the book, it would probably be especially me, which is the line that follows
    0:04:23 even you in I believe it’s chapter three towards the end of it, where I say even me and then
    0:04:30 I think especially me. And I think I want that to encapsulate truly what I’m trying
    0:04:36 to drive home with this book is that we get to define what our greatness is, we get to
    0:04:42 define what our story is. And I don’t want anyone to ever try and take away that ownership
    0:04:44 or to challenge that.
    0:04:49 As I read your book, I said, wow, this incident at the American Canadian border, I’ll give
    0:04:52 a little bit of background for the listeners who are wondering, what the hell are these
    0:04:59 two people talking about? In about 2000 and I think 13, Chica was in a car with three
    0:05:04 other girls and then they had just finished some academic work and they were going from
    0:05:12 Toronto to Buffalo on a shopping spree. And at the American border, the American immigration
    0:05:16 agent was asking them why they’re going to America and they were explaining what their
    0:05:21 background was and their medical school students and they’re on the way to celebrate it and
    0:05:27 they’re going to Buffalo for shopping. And when the guard came to Chica in the car, they
    0:05:32 explained that she’s going to be a doctor too. And he said something like, even you,
    0:05:38 in other words, even you, a black girl, you could be a doctor. Did I get that story right?
    0:05:44 Yes. So with the minor tweakment of the detail that I actually don’t think I mentioned this
    0:05:49 in the book, but alongside me in the car were two of my friends who were of Chinese descent
    0:05:54 and then one of my friends was Guyanese. And so we were all women of colour and I think
    0:05:59 that actually brings in an even more interesting analysis because we were all women of colour.
    0:06:04 However, I was singled out and I was the only black individual in the car and he said, even
    0:06:09 you, when we had clearly stated what our ambitions were and how it was that we knew each other
    0:06:13 because he has had to guys know each other. We were all undergraduate students at McMaster
    0:06:17 University in our health sciences program. We all wanted to be doctors. And so that
    0:06:24 reflexive questioning of this dream that I’ve held since I was three years old in that moment,
    0:06:31 I was indignant, but I was also a bit scared because this was an authority figure. And so
    0:06:37 I didn’t know how to appropriately measure out and weigh my indignation against what
    0:06:44 I was taught, which is also always to be very calm and docile in the presence of authority.
    0:06:52 So are you telling me that even in Canada, black parents have the talk with their kids?
    0:06:59 Absolutely. I think because this understanding of the systems of racism are not limited to
    0:07:06 the American border. This is a ubiquitous universal experience. When we talk about anti-blackness,
    0:07:13 we see it in a global sense. And so when my parents came from Nigeria to Canada in the
    0:07:19 1980s, they experienced that racialization. They experienced that anti-blackness. And so
    0:07:25 for my parents, it was never really this sit down talk of this is what you’re going to
    0:07:31 go through. It was sprinkled throughout different conversations. It was always a touch point
    0:07:36 of you have to behave in this certain way or else certain things can happen to you.
    0:07:41 And really, and I talk about this a lot in my book, Unlike the Rest, where I say that
    0:07:45 my father and his experience is navigating his career as a pharmaceutical technician
    0:07:50 as a nurse and how anti-blackness impacted him. That when he was trying to spirit me
    0:07:56 along on this journey of medicine, he always beat into me this humility that in his mind
    0:08:02 was the way for me to be able to survive a system that also had anti-blackness in it.
    0:08:09 But then the unfortunate outcome was actually trying to make me smaller, to make me less
    0:08:15 identifiable in certain ways to really try and erase all the parts of my identity that
    0:08:22 I thought that I now know is beautiful, but to him was a bullseye. So it was always an
    0:08:24 ever present theme throughout my life.
    0:08:31 Wow. So at this point in your career, have you reached a level of accomplishment where
    0:08:37 you are simply a great doctor or great writer or great poet? And you know what? It’s not
    0:08:43 that she’s the black person there in the room. She’s just fully accomplished. Have you reached
    0:08:48 that point or do you think that point is reachable in this society?
    0:08:53 So that’s a really interesting question because I think that with writing this book especially,
    0:09:00 I viewed it as my biggest act of liberation. And what I mean by that is that I feel that
    0:09:06 once certain individuals, especially black people, black women, once we reach a certain
    0:09:12 level of accomplishment and success, that sometimes all it is that we are recognized
    0:09:19 for is how it is that we can contribute, say for example, from an EDI perspective or from
    0:09:23 certain perspectives where our blackness is at the forefront. And that is something that
    0:09:28 is always going to be so vital and critical to who I am, but I don’t want it to be the
    0:09:32 sole way in which I’m defined. And so I felt that for a long time, I was seen in almost
    0:09:38 this one dimensional analysis of my personality, of my skills, of my talents. And so writing
    0:09:45 this book for me was in many ways liberating such that I can be seen in the fullness of
    0:09:51 who it is that I am, the fullness of my humanity, a three dimensional analysis. Yes, I will
    0:09:55 always be so exceptionally proud of being a black woman and that is something I take
    0:10:01 pride in. However, I am also a doctor. I’m also a writer. I am a mother. I’m a public
    0:10:06 speaker. I’m a performer. I’m an author. There’s all of these things that I am. And
    0:10:11 the fullness of that is what I want to be celebrated.
    0:10:19 Don’t take this wrong. But if I were a racist white person, you would be my greatest fear.
    0:10:29 I don’t take that wrong because I am so aware of that. I think that our society, A, an empowered
    0:10:35 woman is something that terrifies our society. And I don’t think we need to look far to
    0:10:43 see an example of just how afraid our society can get when a woman is audacious and loud
    0:10:47 and intelligent and successful and all of the different things. But when you layer on
    0:10:53 top of that, a racialized woman, a black woman, again, we needn’t look far to see an example
    0:11:00 of this, but when you bring in these different intersections, I can see that inherently individuals
    0:11:06 are intimidated because I create and I’m aware of this. I know that there’s this creation
    0:11:11 of this cognitive dissonance. Our understanding, or at least the way in which black people
    0:11:15 have been socialized, the way in which the perceptions of black people have been embedded
    0:11:19 into our culture is that we are supposed to be less intelligent. Women are supposed to
    0:11:24 be less intelligent, less accomplished. That African individuals, again, there is all of
    0:11:30 these incredibly racist stereotypes about the intelligence of black women, especially.
    0:11:36 So then when I show up, or when other incredibly intelligent black women show up like Levy
    0:11:42 as well, and we challenge this idea, this long held idea, it creates this cognitive
    0:11:47 dissonance. And so some of the ways in which this is reconciled is through that fear. It’s
    0:11:51 through that anger, because usually you are afraid of things or you are angered by things
    0:11:57 that you don’t understand. And so I know that I evoke that emotion, and it’s something
    0:11:59 that I’ve had to contend with for a long time.
    0:12:05 I can guess the answer to this question, but I bet you were even more disappointed than
    0:12:10 I was that Kamala Harris lost the election. We have one of the most qualified candidates
    0:12:17 against one of the least qualified candidates, and she loses, and I just don’t get it.
    0:12:25 Yeah, I was devastated. And I think, you know, it’s interesting because the American political
    0:12:29 system is very fascinating because it feels like the whole world holds its breath until
    0:12:34 we know what’s happening. And I think for so many reasons, it’s understandable, especially
    0:12:39 as a Canadian. I mean, we are, we’re literally geographically so close, but even culturally
    0:12:45 in so many of the other ways in which we are reactionary, or we respond in very similar
    0:12:50 ways to what happens in the States. And so very much, I felt that a lot of Canadians
    0:12:56 and a lot of individuals worldwide were taken aback, were disappointed, devastated. I struggled
    0:13:01 immensely on that morning of the election results when it was declared who had won.
    0:13:07 And it was really devastating, as I’m sure as it was for all, for a lot of Americans
    0:13:22 and for you as well. So yeah.
    0:13:31 So can we back up for a second and just tell us the story of you figuring out that of 259
    0:13:36 students in the entering class at the University of Toronto Medical School, you are the only
    0:13:40 black one. So what was that like?
    0:13:44 To take you back to that exact moment, I would have to give a little bit of a preamble
    0:13:52 because I had gone into it with such significant expectation. I just finished my undergraduate
    0:13:57 program at McMaster University in Hamilton, which is a stone’s throw from Toronto. And
    0:14:03 I was the only black student in my graduating class in 2015 for my undergraduate program
    0:14:09 at Mac. And out of the medical schools that I’d gotten into, U of T was the only school
    0:14:13 that had a Black Medical Students Association. And so amongst all of the reasons of why I
    0:14:18 wanted to go to the University of Toronto, it was close to home. It’s an incredibly prestigious
    0:14:23 medical institution. And it had this Black Medical Students Association. I just felt
    0:14:28 that I was going to deviate from that narrative of being the only black student. And so when
    0:14:35 I arrived on the morning of my stethoscope ceremony day and I looked around and I saw
    0:14:39 that I didn’t really see any other black students. I thought, maybe they just haven’t
    0:14:44 shown up yet. It’s orientation week. It’s not really the first full week of school.
    0:14:50 And so when we got to the actual stethoscope ceremony and they were calling every single
    0:14:55 student across the stage one by one, and my last name starts with an O. And so I was
    0:14:59 fairly further on down in the alphabet. And I remember crossing the stage and thinking,
    0:15:04 I still have not seen any other black people. And then coming off the stage and sitting
    0:15:10 in the seat of the auditorium and then seeing everyone else go by and thinking, oh my gosh,
    0:15:15 as I’m holding this Hippocratic Oath and we’re reciting it and I’m thinking in the back of
    0:15:23 my head, there are no other black people in my class. 259 students in 2016 in downtown
    0:15:28 Toronto, the most culturally diverse city in this country, one of the most culturally
    0:15:36 diverse cities in the world. It was absolutely heartbreaking, I would say, but also a disillusionment.
    0:15:40 I was stunned by it, simply stunned.
    0:15:47 I read in your book, you faced various kinds of racism. And so perhaps you can explain
    0:15:51 to people because obviously I’m not black, so I haven’t experienced what you experienced.
    0:15:57 But from that patient who said, get all the non doctors out of this room and said, this
    0:16:01 black woman, she can’t be a doctor, get her out of this room. And some of the interactions
    0:16:08 you had with your teachers, just explain what kind of racism you encountered. And also for
    0:16:12 each kind of racism, what should you do?
    0:16:16 The way that I like to break down the different kinds of racism. So there’s things known as
    0:16:24 microaggressions, which are your daily racial slights, racial grievances that on the surface,
    0:16:31 maybe to a desensitized ear, you might not even recognize that it could be something
    0:16:37 that’s racially aggressive. Case in point, whenever I would meet a patient or another
    0:16:42 medical student, and I was always frequently asked, where were you born? Are you Canadian?
    0:16:48 Or are you used to the winters? Like it was just a constant assertion and the assumption
    0:16:55 that I was not of Canadian origin that I could not have been born. I must have been born elsewhere.
    0:17:00 So this is gatekeeping of the Canadian identity that constantly made me have to explain myself
    0:17:04 even at the outset of a medical encounter. And then on the opposite side of that are more
    0:17:11 macro aggressive, more intensely obvious, I guess you could say racial grievances where
    0:17:18 it was a direct challenging of my intelligence, my capacity, my ability to actually be a doctor.
    0:17:24 So as you mentioned, having a patient who had directly said that I had to leave the
    0:17:29 room, because I didn’t look like a doctor, even though being repeatedly told that I was
    0:17:34 a part of the medical team, and then still the patient actually growing more agitated,
    0:17:38 growing more aggressive, because they did not want me in the room, and bearing in mind
    0:17:43 that I did not have any training as to how I was supposed to deescalate that situation,
    0:17:47 how I was supposed to encounter that situation, although I had specifically asked for that
    0:17:55 training prior to my clerkship years. And these kinds of experiences, it really permeated
    0:18:01 my medical education, which was an exemplary medical education at the University of Toronto.
    0:18:07 However, I was still facing it from so many different angles. So from patients, sometimes
    0:18:11 from my attendings, from other medical students, and then when I eventually did my public facing
    0:18:18 advocacy, then facing it from the public, which was just an entirely different beast
    0:18:20 unto itself.
    0:18:25 Now going back to that incident where that patient asked you to or told you to get out
    0:18:31 of the room, as I recall, you left the room and you were in tears, and then it was like
    0:18:37 a very traumatic tearful thing, but looking back, should you have just stood your ground
    0:18:43 and confronted him and taken him on, or what would you do today if that happened?
    0:18:50 So I would say that firstly, I want to hold grace for where I was in my journey as a medical
    0:18:56 student, and not necessarily having had the tools or the understanding or the insight
    0:19:02 into what to do in that moment. And so I did leave the room tearfully. I truly did not
    0:19:06 know what I was supposed to do alternatively. Interestingly, I mentioned in the book that
    0:19:11 one of the older fellows, medical fellows had came out afterwards and said, “You should
    0:19:16 have stayed in the room. That’s what you were supposed to do.” And I think, as I said,
    0:19:22 I give myself grace for where I was in that journey. Now, having my MD, being a doctor,
    0:19:27 being a resident doctor, if I was in that same situation, what I would do is I would
    0:19:34 likely stay in the room, I would likely reaffirm to them and reassure them that I am a physician,
    0:19:38 I’m part of the medical team, I am here to help you. And of course, if the patient gets
    0:19:42 increasingly agitated, I would then employ the skills that I’ve since learned as to
    0:19:47 how to de-escalate that situation. I also think it helps when institutions, when hospitals
    0:19:52 have policies that we can actually reflect back to the patient. So this is a teaching
    0:19:58 hospital and in a teaching hospital, you have to be seen by the practitioner who is available
    0:20:04 and that would be myself. And if it got to the point where I felt that my safety was actually
    0:20:09 in parallel or that I was about to be physically harmed, of course, I would go and get the
    0:20:14 appropriate resources to help that’s around there as well. But I think where I am now
    0:20:19 is very different than where I was then all those years ago.
    0:20:27 You are clearly a better person than I am. There’s no question about that. I don’t know
    0:20:32 if I would have done that. I can think of a lot of things, but grace would not be the
    0:20:39 top of mind for me in that situation. So you became active after a decision to turn them
    0:20:43 down, but you changed your mind for the Black Student Application Program. Could you just
    0:20:50 explain that to me because this was something to increase the recruitment of Black students
    0:20:57 to your medical school. And I think it went from one out of 259 to 14 a year later or two
    0:21:04 years later, right? So now, what exactly? Because you made a very clear point that even if you
    0:21:11 did this Black Student Application Program, the academic rigors were the same. So what
    0:21:14 did the program do? What was the goal?
    0:21:21 So the goal in a nutshell was to increase the number of Black applicants applying into
    0:21:27 the MD stream at the University of Toronto. And what it aimed to do was to ameliorate
    0:21:34 some of the biases that were inherent within the application program system. And so what
    0:21:39 they did is that they required that the applicant write an additional essay. So the way that
    0:21:44 U of T usually works for its stream to apply to medical school is that it requires you
    0:21:50 to write a series of short essays. About eight was what I had to write when I applied to
    0:21:54 medical school. And so for this stream, they required you to answer an additional question.
    0:21:59 Now I’m unsure if that exact question has changed over the years, but what it was back then,
    0:22:05 which is why did you feel it was important for you to apply through this Boxing Application
    0:22:09 stream? And how is it that your identity may impact your medical training and things such
    0:22:14 as that? And that was incorporated, but then it was also incorporated that a Black file
    0:22:19 reviewer or a member of the Black community, Black academic community, Black medical community
    0:22:25 would be involved in reviewing your application as well as the actual interviewing process.
    0:22:31 Now that was very different for me because when I was in the process of applying to medical
    0:22:37 school, I actually vividly remember the day of my U of T medical interview, which I talk
    0:22:43 about, I write about in the book where I enter and it’s just a sea of medical school candidates.
    0:22:50 And of course, the anxiety and the sweat is like palpable in the air. And I walk in and
    0:22:56 there’s just no other Black applicants. There were no Black invigilators. There were no Black
    0:23:01 interviewers either as you went from station to station. And there’s about four stations,
    0:23:07 12 minutes per station. And so when you’re going into these spaces and nobody looks like
    0:23:12 you, you’re naturally going to just be aware of that. At least for myself, I was naturally
    0:23:16 attuned to that, especially having been in so many places before where I was only a Box
    0:23:21 student. And so what a difference it makes to actually be able to alleviate some of the
    0:23:26 implicit bias that can be present within this system. And that’s what the Boxing Application
    0:23:34 Program aimed to do and continues to do and has made a significant impact in the educational
    0:23:40 environment, not just for the Black students, but for all students, the diversity of thought,
    0:23:47 the diversity of lived experience, the diversity of culture enriches the educational and the
    0:23:50 medical educational environment for everyone.
    0:23:57 And do you think that some of the students are still thinking, oh, this is a Black student,
    0:24:02 so it was less academically rigorous. There’s a quota system. It’s unfair. It’s reverse
    0:24:06 discrimination. Do you think that still happens there?
    0:24:14 I am sure that there are individuals who may question whether or not, you know, another
    0:24:19 Black student had merited their spot. I think that is, again, a vestige of racism. And I
    0:24:24 know that as I was in medical school, I was fielding that remark constantly, constant
    0:24:30 questioning even on my very first day of medical school, day one, just the morning before my
    0:24:34 stethoscope ceremony, someone asking me, did they make it easier for you to get in here?
    0:24:38 Did you need lower grades? You’re the only Black student. So did they do something to
    0:24:45 make it easier for you? That was before BSAP was even instituted. And so I am sure that
    0:24:49 there may be individuals out there who are thinking these thoughts or feeling these thoughts
    0:24:56 because these are the thoughts that have pre-existed the BSAP program. However, I can assure you
    0:25:01 that intelligence, the tenacity, the ambition of these students, of these Black students
    0:25:07 going through, it will rival any other student who was there, any other student. And I just
    0:25:13 actually gave the convocation keynote for the class of 2024. And this was the largest
    0:25:18 class of Black medical students in Canadian history that came into the University of
    0:25:25 Toronto. And they had just graduated this past year. And guess what? The number two student
    0:25:31 out of the 260 students that got the second highest grades across all four years was a
    0:25:38 Black woman. And I think that that stands as a brilliant example of the fact that we are
    0:25:43 not diluting the collective intelligence of the class. No, no, no, no, no. These are the
    0:25:50 students who we would have lost to the American schools. And this is true. I actually, when
    0:25:55 I was doing my first year of mentorship for the BSAP program, so when I was still a second
    0:26:00 year medical student talking to these other students, encouraging them to apply through
    0:26:07 BSAP, many of them were saying, I got a scholarship to Yale. I have a scholarship to Northwestern.
    0:26:11 I have a scholarship to these places in the States that have already been doing these
    0:26:17 kinds of programs and systems, encouraging Black medical students to apply or Black students
    0:26:21 to apply to their medical school. So we were going to lose them when, in fact, now we are
    0:26:27 retaining them. We are retaining this talent, the brain drain. We’re slowing it down. And
    0:26:33 so I don’t agree at all with anyone who questions the intelligence of Black medical students.
    0:26:39 Well, just to set the record straight, didn’t you become the valedictorian of your class?
    0:26:45 I was elected. I was selected by my class to be the valedictorian of my class. And that
    0:26:53 is an honor that I wear with so much incredible pride and responsibility. And I write about
    0:26:58 this in the book as well because it was almost ironic because in literal definition, the
    0:27:02 valedictorian is supposed to reflect the class. So it was ironic because I was so different
    0:27:11 from the rest of the class that it speaks and that my being selected speaks to the transcendence
    0:27:18 of the work that I was trying to accomplish, the transcendence of who it is that I am and
    0:27:25 what I embody, which is truly embracing your audaciously authentic spirit, embracing what
    0:27:29 it means to be a physician, what it means to be an astute medical student, someone who
    0:27:34 genuinely cares for other individuals. These things are transcendent. And I’m really so
    0:27:38 grateful that my class appreciated that and saw that and that I was able to have that
    0:27:41 incredible opportunity.
    0:27:49 Speaking of transcendent, I am asking you now to tell the story of your interview and
    0:27:56 when you were in the interview and you’re prepared for every possible question except
    0:28:04 when you opened the door and told the interviewer that you participate in slam poetry and he
    0:28:12 asked you to recite a poem. I must say I’ve never heard of that in any application interview.
    0:28:14 So please tell that story.
    0:28:19 Absolutely. I feel like most people can relate to that experience when you’re entering into
    0:28:24 an interview. And certainly if you’re interviewing for a professional school like medicine, these
    0:28:29 interviews, you feel like you have spent your entire life working towards this one moment
    0:28:36 that feels so decisive for the trajectory of the rest of your life. And so through militant
    0:28:41 fashion in the weeks preceding this interview, I had done an archeological dig throughout
    0:28:48 my entire life. And I literally had a notebook that was very thick and it was highlighted.
    0:28:53 It had every single detail down to what was going to make me a brilliant medical student
    0:28:58 and a brilliant doctor thereafter. And so when I was in that interview room and we had
    0:29:03 spent it’s about 12 minutes per room, and we had spent maybe eight or so minutes going
    0:29:07 through my resume talking about all the different things, my research and my extracurriculars
    0:29:12 and everything. And we had a couple of minutes left and I thought, okay, now’s the chance
    0:29:17 for me like in regular interviews to then turn the tables a little bit and ask him some
    0:29:21 questions about the University of Toronto and what it’s like to be a medical student,
    0:29:27 what it’s like research within the institution. And so when I thought it was my turn to start
    0:29:32 asking some questions, and then he looks at the final line of my resume and he saw that
    0:29:37 I’d recently competed at the Canadian Festival, spoken word and was nationally ranked. I placed
    0:29:42 as one of one of the finalists with my team, the Hamilton Youth Poets. And so he looked
    0:29:47 at it and he said, Oh, you’re a performance poet. Interesting. So I’m in the company of
    0:29:53 a nationally ranked poet. Why don’t you perform something for me. And that moment, the sheer
    0:30:01 terror that just blitzed through my body of my spine. I was like, Oh my gosh, I had not
    0:30:08 rehearsed a poem in several months. That was end of January was that interview. And I had
    0:30:14 not competed or been on a stage since October of the previous year. And I’d actually put
    0:30:19 myself into semi retirement because it was so exhausting preparing for nationals that
    0:30:24 I did not want to do any poetry at all in the interval. And so in that moment, I had
    0:30:30 to make a quick calculation of am I going to share a poem because I knew I had my entire
    0:30:33 repertoire of poems memorized, you have to do that if you’re going to be a professional
    0:30:39 poet. So I knew that I could execute it. I just had to think quickly what poem would
    0:30:44 he want me to share. And he said, you know, do your best poem. And immediately I thought
    0:30:50 of my poem skin, which talks about my experiences of being in my skin as a black woman and navigating
    0:30:56 the world in my blackness and in my femininity and all the different things. And the interviewer
    0:31:03 was a senior white male cardiologist at the University of Toronto, at least on the surface.
    0:31:09 Very different from me with regard to all of those different aspects. And so I didn’t
    0:31:15 know if this was going to land with him. I had no idea what his political inclinations
    0:31:19 were. I had no idea what his value systems, I had no idea. But in that moment, I decided
    0:31:27 to take what I now call an audaciously authentic stance. And I was going to share it. So in
    0:31:33 that moment, I shared with him, my skin is like dark ebony under the blazing sun. Won’t
    0:31:38 you tell me that I’m beautiful and don’t preface it by telling me the limiting conditions
    0:31:44 of my beauty. And I remember thinking after I gave him about probably a minute or so of
    0:31:50 that poem, pausing when the bell rang out. And it was just me and him and I like came
    0:31:56 back into my body. And it was just this moment of horror of looking at him like, Oh my goodness,
    0:32:03 I can’t believe I just said all of that to you. Did I completely blow my medical dream
    0:32:11 and medical ambitions? And he was like, that was amazing. Listen to the rest of it. And
    0:32:18 it was the biggest exhale of relief I’ve ever done in my entire life, my whole life.
    0:32:23 And did you call your mom or your sister and say, guess what I just did in my interview?
    0:32:30 I had to recite skin or whatever. I called my mom because my mom was waiting with bated
    0:32:36 breath to see how my interview had gone until I called her and I said, Mommy, I got to perform
    0:32:41 in my interview and she’s perform perform. Why? Why were you performing? He asked me
    0:32:46 to perform the poem and so I performed it and he loved it. And I think that might have
    0:32:52 been my ticket into medical school. I don’t know how it is, but I think if anything, it
    0:32:58 was incredibly symbolic because I always say that being a better poet, a lifetime of being
    0:33:03 a poet, a writer has been the best preparation for me to be a doctor. And so I just think
    0:33:08 it was very symbolic that in my medical school, in a read the most decisive moment of my life,
    0:33:10 he asked me to perform poetry.
    0:33:17 So back up a second and tell me, what does being a poet have to do with being a doctor?
    0:33:25 Why is that a prep for you? It is everything that the two are so interdigitated for me.
    0:33:31 And that’s because at the basis of being a good doctor and at the basis of being a good
    0:33:37 poet is about being a good human. It’s about holding tight to your humanity. And what poetry,
    0:33:43 what a lifetime of poetry has taught me to do is to have this unflinching examination
    0:33:47 of the human experience. That’s what poets do. We always hear about the tortured poet,
    0:33:53 the sad poet, the tortured creative. And that’s because poets analyze the world, all parts
    0:33:58 of the world, even the parts that make us feel heartbroken, the parts that are devastating.
    0:34:03 That’s typically where we get the best poetry. And we have to be able to do that unflinching
    0:34:09 examination. And then on the flip side, when it comes to being a physician, what it requires
    0:34:16 of us, especially within psychiatry, is being able to sit in some of the most heartbreaking,
    0:34:21 other-stating, unbelievable situations, holding people’s hands through the darkest hours of
    0:34:27 their lives, and being able to sit with them in that, to guide them through that, to be
    0:34:32 able to continue with our critical and analytical minds throughout these kinds of situations.
    0:34:38 And so I think that poetry has been this beautiful transference of that. But then also at the
    0:34:43 same time, being a performance poet on top of that, taking my poetry and then giving
    0:34:47 it to the world, that in and of itself is an act of transcendence. That has enabled
    0:34:54 me to be able to connect with other individuals, to have conversations, much like in my medical
    0:34:58 school interview, that might be difficult to have otherwise. Some of the hardest things
    0:35:03 I’ve ever shared with the world, I can only do through poetry. And so that, again, has
    0:35:08 enabled me to build this ability to not only be compassionate, but to be vulnerable. And
    0:35:13 I take these skills and I translate them to my role as a doctor, and I truly believe that
    0:35:18 that’s what has enabled me to be the best doctor that I can be.
    0:35:22 So hundreds of girls are going to be listening to this podcast. I’m going to say I’m going
    0:35:25 to study poetry so I can be a doctor.
    0:35:32 Oh, I love that. I love that. Step one, be an amazing poet and then step two, be a doctor.
    0:35:35 Up next, on Remarkable People.
    0:35:40 My stance is still relatively unchanged from then because I know that the debate is so
    0:35:47 incredibly heated and that I do have that appreciation for patients and for families
    0:35:53 and for individuals who do believe and can see and have that perspective that there is
    0:35:59 a point where mental illness cannot be treated and there is a point where the suffering of
    0:36:28 what it is that they are experiencing should not be continued.
    0:36:34 Welcome back to Remarkable People with Guy Kawasaki.
    0:36:39 So I have to ask you a question that I have not asked any other guests and we’ve had about
    0:36:47 260 guests, which is how does one become a Barbie role model? I just need to know that
    0:36:51 just in case they call. So how do you do that?
    0:36:58 It was really interesting because I got the email from Barbie. Well, through my then agent,
    0:37:03 I was running around the hospital and I was actually a few months pregnant and then I
    0:37:10 got the email that they wanted to make a Barbie out of me for the Barbie role model and I’m
    0:37:15 still stammering because it still seems so surreal. I’ll never forget being in the hospital
    0:37:19 and seeing the title, the subject line of that email and thinking, there is no way that
    0:37:24 this is real and then realizing that no, it actually very much was real and then going
    0:37:30 through the process. So the Barbie, Mattel, Canada, they’ve gone through their very extensive
    0:37:34 vetting system and determining who would be the right candidates and I was selected to
    0:37:41 represent Canada for their healthcare heroes campaign. And so this was in 2021 and they
    0:37:47 had selected six women around the world to be Barbie role models and have Barbies made
    0:37:52 after them and I was selected to represent Canada. And so I went through the process
    0:37:57 with Mattel to actually create various prototypes of what I wanted my Barbie to look like. So
    0:38:03 I was very involved in the actual creation of it and going through different iterations
    0:38:07 and I sent them different pictures of me with different hair cells, different angles. It
    0:38:12 was really cool to see the behind the scenes and then as they continued to tweak and create
    0:38:19 different versions of the Barbie until it was just right. And then being able to unbox
    0:38:26 it and actually see it in the flesh on national TV, it was just the most surreal experience.
    0:38:31 It still doesn’t feel like it actually happens. And whenever people tell me you have a Barbie,
    0:38:37 I’m like, Oh my gosh, I do have a Barbie. It’s the most incredible thing though. I have to
    0:38:43 say that getting a Barbie doll may be more prestigious than a MacArthur Fellowship. I’d
    0:38:47 have to think about that. Although I don’t think you got paid a million dollars to be
    0:38:54 a Barbie role model. Is your doll still current? Can somebody go to Barbie.com and order the
    0:39:01 cheek of doll? I wish. So it’s actually a one of a kind Barbie doll. So I have the only
    0:39:07 chica say so real. Oh, I know. And I’ve been asked in the last three years by hundreds
    0:39:12 if not thousands of people, where can I get this Barbie? And so Barbie actually does have
    0:39:19 a black female doctor that they do sell. And so it’s not you. But no, it’s not my Barbie.
    0:39:24 I know and it makes me so sad because I wish I could give out more of the Barbie doll that
    0:39:29 I have. It’s incredible. But for now it’s, it’ll be played with by my son and my daughter.
    0:39:34 And hopefully they don’t pull her head off and torture her.
    0:39:40 It’s like getting an Olympic gold medal, right? We’ve had Olympic gold medalists on this podcast
    0:39:46 and they often tell me, I don’t even know where it is. I think it’s in my drawer or
    0:39:51 is it in the bathroom and like Brandy Chastain, where’s your Olympic gold medal? I don’t really
    0:39:52 know.
    0:40:02 I definitely know where she is because my husband who is far more not that he’s more
    0:40:08 proud of my accomplishments, but he is really, really proud of my accomplishments. And so
    0:40:16 he has encased the Barbie in this glass like cylindrical casing and has put her inside
    0:40:23 of another glass case. And so she is displayed within our kid’s playroom. So like I will
    0:40:27 always know where she is. But yeah, that is something that for me, like I guess you could
    0:40:33 say that’s my Olympic gold medal is my Barbie doll.
    0:40:37 And when you get selected, do you have to go on a national tour or is like being Miss
    0:40:41 America or something? Or what do you have to do?
    0:40:46 So it was interesting because this was also during the pandemic like this was when I received
    0:40:53 the Barbie, it was August, early August of 2021. So I don’t know if things would have
    0:40:59 been different if it wasn’t right in the thick of things. And I was also five months pregnant
    0:41:05 when I received the Barbie. And so luckily I went to a few new stations and because I’m
    0:41:13 in Toronto, everything was broadcasted nationally from Toronto. And then a whole blitz of media
    0:41:18 came to my home, which I felt very fortunate for being five months pregnant and just being
    0:41:22 able to, you know, walk down the stairs and oh, the media is here. I don’t have to go
    0:41:26 too far. But it was an incredible experience. And so it was definitely cross country and
    0:41:32 then also international because I got to do some bigger media and reach out to different
    0:41:36 countries. And so people from all over the world were hearing this story. And that was
    0:41:39 a really phenomenal experience.
    0:41:46 So in the final model of this doll, how was your hair styled?
    0:41:55 So I wanted to ensure that the Barbie was as authentic as I was and that she had a big,
    0:42:02 beautiful afro, afro textured afro. And I wanted to ensure that it was as a booming and voluminous
    0:42:06 as possible. And so if you look at the Barbie, it’s three times the size of the Barbie’s
    0:42:13 head, which is hilarious. And when I do have my afro out, my afro really is quite voluminous
    0:42:18 and beautiful. And so I wanted to ensure that the Barbie was a reflection of that. And it
    0:42:19 certainly was.
    0:42:25 Oh, I love that. If you think about it, and if you can remember, please send us a picture
    0:42:31 of that Barbie doll so we can use it when we promote this episode. Because this is such
    0:42:33 a great story.
    0:42:41 Absolutely. I can send you the official Barbie photo.
    0:42:45 So someday if they make a Barbie doll out of Madison, we’ll be fully prepared to know
    0:42:46 what to do.
    0:42:53 Yes, I can show her the Barbie ropes, the plastic ones. I can show her all of that.
    0:43:00 I have one really serious question. And then I have one more question and you’ll be done
    0:43:06 with me and you can go back to saving lives and writing poetry. So the serious question
    0:43:14 is, you talk about a time where the students had to have a debate about the moral issues
    0:43:20 of medical assistance in dying for the mentally ill. And I would love to hear what you have
    0:43:28 to say about that. Having practiced psychiatry, should the mentally ill have the access to
    0:43:31 medical assistance in dying?
    0:43:37 So that is a very serious question for sure. And I wrote about this in the book, as you
    0:43:44 mentioned, and this was actually for my residency interview day. We had to write about this.
    0:43:48 And I shared in the book an experience, now this character is fictionalized to protect
    0:43:55 patient confidentiality, but I share about the experience of a woman who I had met who
    0:44:06 had faced a lifetime of serious treatment resistant mental illness, such that the point in which
    0:44:12 they perceived their life was no longer one that was sustainable. And I wrote about that
    0:44:18 experience when I talked about this question that we were posed with, whether or not someone
    0:44:24 with mental illness should be granted access to maid. And in that stance, I talk about if
    0:44:32 we want to treat mental health as serious, and as potentially devastating as ailments
    0:44:40 within physical health, then does it not require us as physicians to then realize that there
    0:44:45 can be mental illnesses that reach a point that are beyond treatment? And at what point
    0:44:52 do we recognize our responsibility as doctors is not always ultimately to extend a life
    0:44:57 but to actually protect the sanctity and the dignity of the individual who is experiencing
    0:45:03 this illness. And I say all of that to say that I guess my stance is still relatively
    0:45:09 unchanged from then because I know that the debate is so incredibly heated, and that I
    0:45:16 do have that appreciation for patients and for families and for individuals who do believe
    0:45:22 and can see and have that perspective that there is a point where mental illness cannot
    0:45:27 be treated. And there is a point where the suffering of what it is that they are experiencing
    0:45:33 should not be continued. And so I can appreciate that perspective. And then I can also see
    0:45:39 the ways in which as psychiatrists that the field of psychiatry as a psychiatry resident
    0:45:44 as a future psychiatrist, also the argument that it is our job to continue to extend the
    0:45:49 life of individuals. It’s our job to continue to try and always improve the mental illness
    0:45:54 of certain individuals that it might be a fleeting moment in which you believe your life is no
    0:45:59 longer worth living, but can we potentially explore other options? And so I say all of
    0:46:03 that to say that I don’t know if I’ve necessarily landed on a concrete answer, but it is something
    0:46:08 that I do reflect on and have reflected on very deeply for a long time.
    0:46:17 Okay. I lied. I actually have one more question after my final question. So my final question
    0:46:24 and I want you to talk about your book and all that stuff, but pretend that you are addressing
    0:46:31 young girls and they’re listening to this podcast and just give them the best advice
    0:46:34 that you can based on your life experiences.
    0:46:45 Oh, I love this question. What I would say to them is to never forget the power of your
    0:46:55 voice and to use it even if your voice shakes, even if it’s a whisper, to never forget the
    0:47:02 power of your voice and that you get to define who it is that you are, the strength that you
    0:47:09 possess, the journey that you are on, and not to let anyone else grab the pen from your
    0:47:15 hand and write the story of your life. You will always be the author. And so to continue
    0:47:21 on that journey is so incredibly important and it starts with recognizing the beauty
    0:47:28 of what your voice is. And so that’s the message I would love to relate to any young woman
    0:47:29 listening to this podcast.
    0:47:35 My God, you are just a fountain of poetry. I could ask you what time is it in Toronto
    0:47:44 and it would come out as a poet. My God. Okay, promise you, this is the last thing. This
    0:47:50 is the last thing. So we interview about 52 people a year. So we’ve done this for about
    0:47:57 five years. So we’ve interviewed 250, 260 people. I’ve read a lot of books. I’ve seen
    0:48:05 a lot of videos, but you had a line in one of your videos and I want to hear you say
    0:48:11 it. Now, okay, I sure hope you remember this line because it was so memorable to me. I
    0:48:16 hope you can remember it, but I’ll give you the gist of the line. The gist of the line
    0:48:25 is that no need to reply. My hope is only to edify. And I thought, oh my God, that is
    0:48:33 such a great statement. So as the last thing you do for us, could you just say that line
    0:48:37 that stanza that I hope you haven’t memorized?
    0:48:44 Yes, I do. It’s actually from my poem, Love Letters from My Body, which was a very vulnerable
    0:48:50 and raw exploration of my experience with disordered eating from the ages of 19 to about
    0:48:55 23. And I talk about that once again in the book, but this poem explores that. And so
    0:49:00 the stanza is from that. So I can absolutely recite that line and maybe a line or two after
    0:49:04 that. I’m just going to bring this as your medical into it.
    0:49:05 Yay, really?
    0:49:07 And I’m asking you to perform.
    0:49:14 Yes. Okay. Dear Chica, she wrote, no need to reply. My hope is only to edify the wonders
    0:49:20 that you are. When you search for meaning amidst the twilight stars, I hope you know
    0:49:24 that the answers were always at your fingertips. You were equipped with a mind that could
    0:49:30 steer ships lips that could part the seas promise me that you’ll never forget that you’re nothing
    0:49:36 short of a miracle. And when you move your feet, it is lyrical. So keep dancing like
    0:49:42 no one is watching. And if you feel the need to syncopate your joy, I will deploy a series
    0:49:48 of letters, scented with lilac written in gold detailing the light that you hold from
    0:49:56 me to you to us, trust that all you need to do is listen to this body.
    0:50:01 Oh my God. Holy shit.
    0:50:08 Sorry, I just needed to get into it. I knew I had it with me. Thank you for my…
    0:50:15 You’re a Barbie doll and I’m not my among other reasons. But yeah, that was just remarkable.
    0:50:22 Thank you so much for being on our podcast and you definitely have brought a great deal
    0:50:27 of joy and light and laughter to me today. And I’m sure everybody listening to this.
    0:50:31 So thank you so much. Oh, just tell us the name of your book because we want people to
    0:50:34 read your book. I read it and I loved it.
    0:50:39 Oh, thank you. And I just want to say that it has been an absolute joy and pleasure to
    0:50:47 speak with you today and my book is called Unlike the Rest, a Doctor’s Story by me, Dr.
    0:50:53 Chica Stacey Oriwa, and it is available wherever books are sold and also at your favorite online
    0:50:54 retailer.
    0:51:03 See, even your sales job is a poet. I’m going to have you do like marketing for me and my
    0:51:11 books. I would love that. I’m going to get you and lovey and I’m going to own the Nigerian
    0:51:12 market.
    0:51:19 If you can introduce me to lovey, that would be the coolest day ever.
    0:51:26 Listen, like I said, I only know two Nigerians, you and lovey. And based on that rather statistically
    0:51:29 invalid sample, oh my God.
    0:51:36 I will say we are pretty cool people. We are pretty remarkable people. You’re sample size,
    0:51:41 although very small and it’s still pretty.
    0:51:47 And John M. Chu, if you’re listening to this and you make a movie called Crazy Rich Nigerians,
    0:51:51 you credit me for that idea, okay.
    0:51:52 Absolutely.
    0:51:59 All right, so this has been Remarkable People. I’m Guy Kawasaki. I hope you enjoyed this episode
    0:52:05 as much as I did. And you learn about racism and dealing racism and reducing racism and
    0:52:07 hopefully eliminating racism.
    0:52:11 And if you’re a patient and you see a black woman come in to treat your room, you should
    0:52:19 thank your lucky stars. That’s the doctor. That’s clearly what I learned today.
    0:52:24 So I just want to thank the rest of the Remarkable People crew. That is, of course, the Remarkable
    0:52:30 Matters and Nysemer producer and co-author Jeff C. and Shannon Hernandez, who are doing
    0:52:32 all our sound design.
    0:52:37 And finally, Tessa Nysemer, our ACE researcher, who helped me find all these great questions
    0:52:39 for Chika.
    0:52:43 And now we’re going to let you go and we’re going to let you go to your kids and your
    0:52:50 husband and your patients and your poems and all that. And congratulations for a life well
    0:52:55 lived. And you’re so young. Oh my God. Someday when you’re a prime minister or whatever
    0:52:58 it is of Canada, you’ll remember me. Okay.
    0:53:01 Thank you, Guy. This has been a hard time.
    0:53:03 We’ll go to Tim Hortons and have breakfast.
    0:53:07 Yes, I will treat you. I’ll treat you to a breakfast better than Tim Hortons. But yes,
    0:53:09 I will treat you.
    0:53:17 All right. Take care. Bye bye.
    0:53:19 This is Remarkable People.

    Step into a world where poetry meets medicine and authenticity breaks barriers. Guy Kawasaki shares an unforgettable conversation with Dr. Chika Oriuwa, a groundbreaking physician, poet, and advocate who made history as the only Black student in her class of 259 at the University of Toronto Medical School. Together, they explore her journey from being a nationally ranked slam poet to becoming a pioneering doctor and Barbie role model. Dr. Oriuwa shares powerful insights about transforming medical education, embracing authentic leadership, and using poetry to enhance patient care. Discover how she’s reshaping healthcare while championing diversity and inclusion in medicine.

    Guy Kawasaki is on a mission to make you remarkable. His Remarkable People podcast features interviews with remarkable people such as Jane Goodall, Marc Benioff, Woz, Kristi Yamaguchi, and Bob Cialdini. Every episode will make you more remarkable.

    With his decades of experience in Silicon Valley as a Venture Capitalist and advisor to the top entrepreneurs in the world, Guy’s questions come from a place of curiosity and passion for technology, start-ups, entrepreneurship, and marketing. If you love society and culture, documentaries, and business podcasts, take a second to follow Remarkable People.

    Listeners of the Remarkable People podcast will learn from some of the most successful people in the world with practical tips and inspiring stories that will help you be more remarkable.

    Episodes of Remarkable People organized by topic: https://bit.ly/rptopology

    Listen to Remarkable People here: **https://podcasts.apple.com/us/podcast/guy-kawasakis-remarkable-people/id1483081827**

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  • Keith Ferrazzi: Why Great Leaders Never Lead Alone

    Keith Ferrazzi: Why Great Leaders Never Lead Alone

    AI transcript
    0:00:09 [MUSIC]
    0:00:10 Good morning, everybody.
    0:00:14 This is Guy Kawasaki, and this is the Remarkable People podcast.
    0:00:18 And as you know, we’re on a mission to make you remarkable.
    0:00:23 So we go out and we find the most remarkable people we can to inspire you and inform you.
    0:00:27 And of course, today we hit it out of the ballpark.
    0:00:28 We have Keith Ferrazzi.
    0:00:31 Can it get any more remarkable than that?
    0:00:38 Many of you may remember him for this great book that he wrote called Never Eat Alone.
    0:00:41 And wow, that was a fantastic book.
    0:00:46 And now he’s with us for the second time because he’s got another great book.
    0:00:51 And now instead of not eating alone, we’re going to talk about not leading alone.
    0:00:53 Right, Keith?
    0:00:55 Guy, it’s extraordinary to be here.
    0:00:57 And I’ll just mirror right back to you.
    0:00:59 You are remarkable, my friend.
    0:01:01 It’s been amazing to watch all that you give to the world.
    0:01:03 No, I don’t know about that.
    0:01:05 You probably tell that to every podcaster.
    0:01:06 I don’t actually.
    0:01:09 Nobody else has called the Remarkable podcast.
    0:01:13 So this was my unique opportunity.
    0:01:16 So I have kind of a weird question to start off.
    0:01:22 I read the forward of your book and I thought, do you ever wonder, and this is true for me too,
    0:01:29 do you ever wonder where would we be if our parents were rich?
    0:01:29 Oh, my God.
    0:01:32 Because you came from a poor family and I did too.
    0:01:34 So and I’m not trying to say that we would be better off.
    0:01:39 I’m saying maybe we would be worse off if we came from a rich family.
    0:01:39 It’s interesting.
    0:01:43 There’s somebody out there with a name similar to yours that wrote this book, Rich Dad, Poor Dad.
    0:01:46 And I’ve had the chance to talk to him a bit about this.
    0:01:49 I thought you were going somewhere else with a question, which I’ll come back to.
    0:01:55 I’m obviously blessed to have the drive, the inspiration, the desire to make an impact
    0:02:00 in this world that was infused in me in a very early age from my father.
    0:02:06 And also the gumption that it took for me to get where I am today and the resilience
    0:02:10 as a result of coming from real abject poverty in the United States.
    0:02:13 My old man was unemployed and it gave me that drive and ambition.
    0:02:18 Not only did it give me a drive and ambition to be successful and to dig out of the economic
    0:02:24 hole we were in, but it also gave me a mission, which is we grew up in southwestern Pennsylvania
    0:02:26 in the crash of the steel industry.
    0:02:32 And I saw how poor management made families destitute.
    0:02:39 And that’s what I’ve been on for 20, 30 years is that desire to try to make sure the corporation
    0:02:45 stay ahead of the pack so that families like ours all over the world can thrive.
    0:02:45 Yeah.
    0:02:46 But thanks for that question.
    0:02:48 You know where I thought you were going to go with it, by the way.
    0:02:53 I thought you were going to go with it as if we knew when we were younger what we know now.
    0:02:57 I wish I was the leader that led this way all my life.
    0:03:02 And that was the big lesson for me, which is writing this book and researching this book
    0:03:05 and woken me up to my own leadership needs.
    0:03:06 And you know what?
    0:03:10 I would make the case that it’s better late than never, first of all.
    0:03:16 But also it may take 50 or 60 or 70 years to figure out what’s in that book.
    0:03:19 I don’t think you can figure that out at 20.
    0:03:19 No, you’re right.
    0:03:25 In fact, I wrote Never Eat Alone and it was about my life and how I achieved success through
    0:03:30 and with opening doors and relationships, networking, one might speak.
    0:03:34 And then I kept on that relationship thread and I started doing more and more research
    0:03:38 about how small groups of people support each other through transformation,
    0:03:42 which really evolved my passion for high performing teams.
    0:03:46 So for 20 years now, I’ve been researching how does a small group
    0:03:50 of people perform disproportionately more than others?
    0:03:54 And that’s, it has been 20 years of research, 20 years of coaching some
    0:03:58 of the most extraordinary turnarounds like at General Motors, some
    0:04:00 of the fastest growth unicorns now, even governments.
    0:04:06 We’re working with the country of Bhutan to infuse the principles of co-elevation
    0:04:12 and teamship in how they govern as they double their GDP and keep their happiness index.
    0:04:14 It’s been 20 years of work.
    0:04:19 So first of all, could you define for the audience your concept?
    0:04:22 I think you invented this word “teamship.”
    0:04:24 I love the word “teamship.”
    0:04:27 So what does it mean from Keith Farrasi?
    0:04:27 Well, I want to give you credit.
    0:04:32 It was one of my teams actually, one of my teammates that designed the word “teamship”
    0:04:34 and woke that up for me.
    0:04:38 A “teamship” is the recognition and I feel, I know this is going to sound heretical.
    0:04:44 I think we’ve over-indexed on leadership, under-indexed on “teamship.”
    0:04:48 Now, leadership of course is important and I think it deserves all the credit it’s been getting.
    0:04:50 How do you be a great leader?
    0:04:56 But there were no guidebooks out there on what to expect from a high-performing team.
    0:05:02 Lencioni’s book “20 Years Old Now” was a book about what are the dysfunctions of a team.
    0:05:07 I wanted to give a very prescriptive roadmap on how a team becomes exceptional.
    0:05:13 And what we did was we recognized that if you look at a good leader, they give feedback.
    0:05:16 But a great team gives each other feedback.
    0:05:20 If you look at a good leader, make sure that the team has good energy.
    0:05:22 A great team makes sure each other has energy.
    0:05:25 A great team holds each other accountable.
    0:05:32 A great team is responsible for each other’s resilience, is responsible for each other’s ideas and fortitude.
    0:05:40 And giving them what I call “co-elevation,” a purposeful mission, but forcing to lift each other up in the process.
    0:05:46 Now, if a leader can unleash that, it is asymptotic in terms of what can be achieved.
    0:05:50 I was about to ask you what are the tells of a lack of “teamship.”
    0:05:54 But you just listed them there, is there anything you left out?
    0:06:01 No, I did. The book is, what we found, our research is a 3,000 team dataset over 20 years.
    0:06:03 And that’s what you get when you get this book.
    0:06:10 And what we’ve done is we’ve broken it down into 10 critical shifts that a team needs to make.
    0:06:14 Each chapter is a shift. Each chapter starts with a hero’s story.
    0:06:20 And then right after that, around that particular shift, real simple practices that the team can try on.
    0:06:24 The intention is to use it as a book club and the book becomes your coach.
    0:06:30 I wanted to put myself into every team out there in the world that I couldn’t get to using the book.
    0:06:33 And so there are 10 shifts, and I just mentioned a few that are really important.
    0:06:40 One of them is candor and the willingness for a team to move from conflict avoidance to real courage.
    0:06:46 Another one is very purposeful bonding and having each other’s back, the connectivity of a team.
    0:06:48 Those two are very important.
    0:06:56 I would say of the 10 shifts, there’s probably three or four that I can say are disproportionately predictive of a team’s outcomes.
    0:07:07 So back up for a second for me. Let’s say I’m listening to this and I even bought the book and I just want to give me the gist of how do I conduct team diagnostics?
    0:07:11 How do I assess the level of teamship on my team?
    0:07:13 Yeah, let me just use one chapter.
    0:07:21 So the first two chapters are the forward to the book and the awakening that you should expect more from a team that’s chapters one and two.
    0:07:27 But let me dive right into a practical chapter three and chapter three has a couple of questions that you ask your team.
    0:07:34 One of them is a diagnostic question that I have done with thousands of teams and it’s a simple question.
    0:07:42 Do we challenge each other in the room when it’s risky to do so, even when it’s outside of our swim lanes or areas of expertise?
    0:07:48 So that’s a complicated question, but the bottom line is do we challenge each other actively here, even when it’s risky?
    0:07:54 Now, the average team on a scale of zero to five is actually only about two or less than two.
    0:07:56 I can give you a couple of simple practices.
    0:08:00 One practice is actually called a candor break.
    0:08:06 Put onto your agendas of your meetings a simple line that says we’re going to do a candor break.
    0:08:13 It’s when you stop in the middle of the meeting and you ask the team what’s not being said in here that needs to be said.
    0:08:16 Now, you don’t just do it in an open forum with eight people.
    0:08:20 You have them go into groups of two and you have them chat for even 30 seconds.
    0:08:24 What’s not being said that should be said, then you restart the conversation.
    0:08:31 In that small group of two, psychological safety goes up by 85% and people will begin to have a very different conversation afterward.
    0:08:36 That’s one of four of the practices in chapter three called a candor break.
    0:08:42 Now, there are a few others and we can get into them if you’d like to because they’re really useful for your listeners to dive into.
    0:08:50 But the first thing you do is you diagnose where you are, you do a couple of the practices and then a couple of months later, you diagnose again.
    0:08:57 And I promise you that what we find is the average candor score of a team is usually in the low twos, high ones.
    0:09:04 And then that goes up to the low threes in less than a few months and it goes up into the high threes, low fours within six months.
    0:09:06 If you do the practices regularly.
    0:09:12 So the intention is you do the practices, you change your culture and you get different outcomes.
    0:09:15 I understand what these teammates are doing.
    0:09:22 But now what kind of mental framework does the leader have to ensure the success of a teamship?
    0:09:24 Yeah, there’s a phrase I love to use.
    0:09:28 I might have used the last time we together, but it’s we’re behavioral scientists.
    0:09:30 We just study practices.
    0:09:35 I don’t I’m just like I said, I think we’ve over indexed on leadership.
    0:09:38 I’m going to say I think we over indexed on mindsets.
    0:09:41 I believe that you don’t think your way to a new way of acting.
    0:09:43 You act your way to a new way of thinking.
    0:09:49 I don’t need a leader to adopt a different mindset in order to read my book and start to practice it.
    0:09:53 I just want a leader to have the courage to try a few of the practices.
    0:10:01 And if you try a few of the practices, you’ll wake up and realize how much pent up value is in your team that you’re letting sit there.
    0:10:05 So there’s one of the practices is called it is called a stress test.
    0:10:11 So a stress test, a lot of us do these things called report outs in our team meetings.
    0:10:15 We show somebody will show up and they’ll say, worst case, they’re going through a 20 page deck.
    0:10:16 Here’s where we are in this day.
    0:10:17 Oh my God, it’s horrible.
    0:10:19 I’m sure you’ve never seen that before, right?
    0:10:27 So you would instead we go through something called a stress test where the person shows up and on one page says, here’s what I’ve achieved.
    0:10:31 Here’s where I’m struggling and here’s where I’m going.
    0:10:39 Now, everybody knows what each other is doing anyway, but this initiative is now summarized this way and you pause and you once again go into small groups of two or three.
    0:10:45 And in those groups, you open up a Google doc and in the Google doc, you write, here’s where I challenge you.
    0:10:47 You might be missing this.
    0:10:48 Here’s an idea.
    0:10:51 I’m going to give you and here’s some support.
    0:10:56 I’d like to offer a simple assignment has now rebooted your culture.
    0:10:59 I wrote an article about this in Fortune magazine a couple of weeks ago.
    0:11:07 If you want to just go look at my name and fortune, you’ll see this article and it talks about how one simple practice can totally reboot a culture.
    0:11:15 This stress testing, if you regularly practice stress testing and every associate shows up and is willing to get feedback from the team directly.
    0:11:23 You’re priming the pump to open up the value that this team can give each other without you always being the hub and spoke.
    0:11:31 And in this world, does all of this have to be done in person or can we use digital collaboration?
    0:11:46 Chapter six, chapter six recognizes that the tools that we have been sitting on Microsoft Teams, Google, WebEx, Zoom, there’s a robust set of tools now having AI complement those tools.
    0:11:59 Your teammates are now expanded to include AI and these collaborative tools that are available to us are extraordinary project management software, knowledge management software, the stuff that Drew Halston’s doing over at Dropbox is amazing.
    0:12:05 Now, I want to make sure that we start to become what I call 21st century collaborators.
    0:12:09 Stop using damn meetings as the primary form of collaboration.
    0:12:15 If you’re a leader that that sees a problem and actually there’s a wonderful example of this.
    0:12:24 I don’t know if you ever met Gil West, who was at United Airlines went over to Cruz, the self driving car company.
    0:12:25 He went over there and he was looking around.
    0:12:27 He’s, you know what? I see a problem here.
    0:12:28 Let’s have a meeting on it.
    0:12:38 And these kids out of Stanford, which is where most of these kids that that bird these companies, they looked at Gil this western or this guy from the south, the southerner.
    0:12:40 And he said, Gil, how do we have a meeting on it?
    0:12:42 We haven’t collaborated yet.
    0:12:46 So these kids collaborate in the cloud, multiple cycles.
    0:12:53 They figure out what the big problems are we’re trying to solve, what the big barriers are, what innovation innovative solutions we have.
    0:12:57 Then they have meetings to land the plane if they need it, right?
    0:13:04 So we’ve got to do what I call meeting shifting, where we ignore this idea that meetings are the primary form of our collaboration.
    0:13:09 This book has been able to reduce the number of meetings by 30% in most teams.
    0:13:15 I’m almost afraid to ask, what do you think of these companies who are mandating return to office then?
    0:13:24 Okay, look, I’ve got some very good friendships with some of these executives who very well known right now for bringing everybody back to the office.
    0:13:26 So here’s what I’ll say.
    0:13:31 I don’t want to have a dog in the hunt as to whether or not we need to be in the office or out of the office for a moment.
    0:13:33 But here’s what I can tell you.
    0:13:40 I’m going to use two folks you probably know, Drew Houston, Matt Mullenweg, Drew from Dropbox, Matt Mullenweg from WordPress.
    0:13:51 The two of those folks during the pandemic found that they were feeling that their companies were suffering from a drain in energy relationships.
    0:13:55 They sensed that the culture was eroding because they were virtual.
    0:14:02 Now, some CEOs, when they felt that their natural reaction was, let’s get everybody back to the office as soon as we can.
    0:14:06 And what I’m going to put words in their mouth, they’re not saying this, but it’s how they’re acting.
    0:14:14 They’re basically saying, let’s get everybody back to the office to practice serendipity bonding, which is how that we build our culture.
    0:14:16 We want people to bump into each other in hallways, etc.
    0:14:21 Drew and Matt decided to say, you know what we’re going to do?
    0:14:23 We’re going to not practice serendipity bonding.
    0:14:25 We’re going to practice purposeful bonding.
    0:14:28 Every week, we’re going to do energy checks.
    0:14:35 These energy checks are going to act as a safety net where everybody’s going to go around and say, here’s what’s draining my energy.
    0:14:39 On a scale of zero to five, here’s where I am and here’s what’s draining my energy.
    0:14:48 These energy checks, the average relationship score of a team prior to the pandemic when they were doing serendipity bonding was in the mid to high twos.
    0:14:53 When you went into the pandemic, it went down into the low twos because people didn’t see each other.
    0:14:59 When you started practicing purposeful bonding, it ended up going up into the mid to high threes.
    0:15:07 The point that I would make is if you’re going to be virtual or hybrid, which any global company is anyway, right?
    0:15:14 Then you need to use 21st century collaboration and you need to use purposeful cultural building tactics and practices.
    0:15:17 That will actually get you on a steady state.
    0:15:27 You can actually do a better job in a hybrid virtual world than you did just using accidental serendipitous ways of connecting and collaborating.
    0:15:35 If you want to bring everybody back into the office because there’s an extra spriticore and you can recruit people who want to be in that office and still have that kind of an energy.
    0:15:38 I would still recommend you read chapter six.
    0:15:48 You still build that sort of purposeful collaboration tools and you build in chapter four those purposeful bonding skills and you’ll crush it either way.
    0:15:54 The people that I know that are being forced to return to office.
    0:15:57 It’s not this spirit of serendipity.
    0:16:07 It’s more we’re going to check your badge on the way in and we’re going to know exactly when you came and when you left and you need to be there for such and such many days per week per minute.
    0:16:11 It’s like a it’s like punching a time clock for knowledge workers.
    0:16:14 I wouldn’t say there’s anything to do with serendipity.
    0:16:17 I’ll riff for a moment and I do in the book.
    0:16:24 One of the things that I realized when I finished writing the book as I looked back on all the heroes that I celebrated in the book.
    0:16:35 Almost all of them were engineers and it made me realize something and that was that the people who put their mind to reengineering ways of working.
    0:16:45 Ended up thriving as leaders versus those who left the ways of working to be more accidental or legacy oriented.
    0:16:47 I’ll say it a slightly different way.
    0:16:54 When the pandemic hit we looked over at the HR department and we said it’s your job to figure this work thing out.
    0:17:00 And so HR people like governance people put a hat on around policy.
    0:17:06 So it was about checking the boxes of being in the office or how much zoom time do you actually have.
    0:17:12 Could we possibly measure how much fingers are on keyboards during the day.
    0:17:15 It was policy and auditing for it right.
    0:17:18 But there was another group of people that said wait a second.
    0:17:20 We’re in a different world today.
    0:17:22 We have technologies we didn’t have before.
    0:17:26 We have opportunity and potential to reinvent working.
    0:17:29 What would that look like if we reinvented collaboration.
    0:17:31 And that’s what I’ve documented here.
    0:17:33 And I and that’s an engineering.
    0:17:34 That’s a reengineering.
    0:17:37 Ask yourself in the average company who is reengineering work today.
    0:17:38 Whose job is it.
    0:17:41 Software engineers did agile.
    0:17:44 Manufacturing engineers did six sigma and TQM.
    0:17:48 Both of those were new ways of working that got reengineered.
    0:17:52 Now we need to reengineer collaboration in white color teaming.
    0:17:56 How and I and look I started out my life as an industrial engineer.
    0:17:59 That’s what I’m trying to bring as a behavioral scientist as an engineer.
    0:18:03 New ways of working new ways of teaming that will help us crush it.
    0:18:05 Correct me if I am wrong.
    0:18:09 But in reading your book and even just listening to you now.
    0:18:17 It seems that the concept of this lone genius this superstar visionary cowboy.
    0:18:21 The obvious examples are Steve Jobs and Elon Musk.
    0:18:25 I don’t remember much team ship in the Macintosh division.
    0:18:33 So are these two people just outliers or should they be our heroes or anti heroes.
    0:18:38 I love that question and I earnestly ask that question myself.
    0:18:45 And because I went through and what I did was I studied people like to rank over at Elf Beauty.
    0:18:53 Who has been absolutely crushing it against the this is a small organization that is now eating market share significantly.
    0:18:58 Against the big beauty companies and its entire culture is bred from team ship.
    0:19:00 It was chapter 10 and I can share a little bit more about it.
    0:19:07 But I just went and looked at companies that were crushing it and extracted their practices and I found team ship was embedded.
    0:19:09 I started doing the same thing for Elon Musk.
    0:19:13 About six months ago I put a research team our research institute.
    0:19:19 I signed a research team of two people to really go and scour.
    0:19:23 What are the practices of Elon Musk and why he’s been successful.
    0:19:28 I finished that research and was ready to actually consider writing a book on it because I thought it was really intriguing.
    0:19:35 And I found out that a friend of mine Dennis Neil is also just releasing a book and was already going to press on the exact same subject.
    0:19:37 What makes this man exceptional.
    0:19:39 And I do think that we can do both.
    0:19:46 The social contract at a place like Elf Beauty from Terrang is come here.
    0:19:47 You will thrive.
    0:19:53 You will grow faster and further than you ever have your but you have to be willing to let your team push you higher.
    0:19:55 Your team needs to give you feedback.
    0:19:57 Your team needs to lift you up.
    0:20:01 You’re going to you’re going to love on each other and you’re going to grow and we’re going to kick ass.
    0:20:04 That’s the Terrang social contract at Elf Beauty.
    0:20:12 The social contract over at you know at a place like SpaceX or anywhere else that Elon Musk is prevailing is come here.
    0:20:17 You’re going to get your ass kicked and we’re going to do extraordinary fucking things.
    0:20:17 Right.
    0:20:20 It’s that’s a social contract that some people buy into.
    0:20:25 But I think you’re quite limited to the number of people who want to be in that social contract.
    0:20:30 If you want to scale if you want to create extraordinary products.
    0:20:38 Yes. You could have an extraordinary visionary like Elon or like or like jobs and you can count on them to dictate the answer.
    0:20:45 Or we can start looking at innovations and crowdsourcing of insights where we can get inspired from diverse inputs.
    0:20:53 Like things like XPRIZE and our friend Peter Diamandis espouses which is the wisdom of the crowds to inspire in great innovation.
    0:20:56 There’s two different philosophies and I think there’s things we can learn from.
    0:21:17 I’m going to ask you a question that maybe you don’t want to answer.
    0:21:33 So let’s say that Donald Trump’s nominations all go through and Donald Trump’s chief of staff calls you up and says Keith.
    0:21:38 I want you to help me make a team ship out of this cabinet.
    0:21:39 Yeah.
    0:21:41 I don’t know how and what do you do.
    0:21:45 Did you just pull that out of the air or did you do some research.
    0:21:47 OK. Interesting.
    0:21:51 And I mean what kind of research do you need to do to ask that question.
    0:22:01 The research is that at the beginning of the Biden administration exactly this time at the transfer of power from the prior administration to the Biden administration.
    0:22:11 I wrote an article in Fast Company which is my advice to the Biden administration for how he should run his cabinet and how his cabinet should treat the hill.
    0:22:14 Now they took none of it and I didn’t get any calls.
    0:22:17 But I’ll tell you look very interesting.
    0:22:23 I did study this and as a result of writing this piece you can go back and find it in Fast Company four years ago.
    0:22:31 And what would I recognize was the cabinet is a bunch of very high powered billion people and whether you like their politics etc.
    0:22:32 They are what they are.
    0:22:35 And each of those individuals run their domains.
    0:22:39 There is no interdependency among that group of people.
    0:22:42 The simple practice of stress testing.
    0:22:53 Imagine Dr. Oz showing up in that cabinet and asking here’s where I here’s my analysis so far of what I think Medicare and Medicaid has got to do.
    0:22:57 Here’s where I’m struggling to figure this out and here’s where I’m planning to go.
    0:23:03 And then the team the cabinet would go into small groups and say here’s what you’re missing.
    0:23:05 Here’s an idea.
    0:23:07 Call me here if you’d like some help.
    0:23:12 That simple practice of stress testing would make that group so much more effective.
    0:23:17 Then the next question is and this is the first thing I ask in this book is who’s your team.
    0:23:24 Look the reality of government and the reality of business is that our teams have nothing to do with org charts.
    0:23:27 If you want to get something done you need the people up on the hill.
    0:23:29 You need the bureaucrats.
    0:23:31 You need the congressman the senators.
    0:23:38 They’re your team and yet we think and we treat each other as the silos in business and in government.
    0:23:50 The work that I’m doing with the country of Bhutan is interesting because in Bhutan you’ve got a very small country that is revered by people all over the world for being one of the happiest places in the world.
    0:23:58 They’re looking to make leaps forward in their economic growth and like every other government they were traditionally thinking about it in silos.
    0:24:00 You’ve got the secretaries.
    0:24:07 You’ve got the ministers one politic one bureaucrat very separate and then you’ve got the private sector.
    0:24:20 We’re looking at how those groups can come together as one team one team which allows the government officials to truly what I call teaming out and crush it in terms of innovative new ideas that they would have never never been able to do before.
    0:24:34 So the answer to your question is if I got that call I would be surprised but if I got that call of course I grew up as a kid wanting to make a difference in this world when the steel industry was crashing.
    0:24:42 I wanted to be a politician and I wanted to grow up and be governor of Pennsylvania president United States and fix American manufacturing.
    0:24:50 I’m doing it from a different lens today. I’m doing it from the perspective of thought leadership and the perspective of behavioral science around teams.
    0:24:53 I would of course serve my country in any way that I could.
    0:25:04 So you would say yes I would say yes and I would just invite me when you tell Dr. Oz to have this conversation with I don’t know.
    0:25:10 I can’t say Matt Gates anymore because he dropped out but that would have been a conversation I would like to hear.
    0:25:17 I can’t say that these practices are easy to implement everywhere.
    0:25:31 If you’ve got if you’ve got a tin-eared narcissistic leader that is unwilling to open themselves to critique and open dialogue which I have sometimes seen in my career.
    0:25:35 It’s more difficult to get the team to be psychologically safe to do this.
    0:25:43 Although I remember a leader of a large telecom company international telecom company that that was exactly that kind of person.
    0:25:50 And what ended up happening is the team applied these principles out of salvation for themselves.
    0:26:00 The leader was narcissistic difficult challenging and the team rallied together to be the kind of leaders that they were all were asking for for each other.
    0:26:09 They were able to I would say not thrive because it was difficult but they were certainly able to co-elevate as a team.
    0:26:13 But imagine if the leader embraces that journey.
    0:26:16 Okay I’ll let you off the hook now.
    0:26:19 Don’t you have in mind you can ask anything my friend.
    0:26:22 Love it.
    0:26:31 Would you explain the difference between candor and conflict because I think many people don’t differentiate the two.
    0:26:32 It’s actually a great question.
    0:26:44 And I think that there’s conflict avoidance which I find right in most companies which is why this score about can we challenge each other when it’s risky to do so is low.
    0:26:49 I think a lot of people think of conflict as disrespect where there’s disagreement.
    0:26:52 I think healthy conflict is necessary.
    0:26:56 I believe I would be curious if you go back in the Macintosh days.
    0:27:02 Was there ever a healthy conflict where people pushed in each other with or I don’t know if they felt psychologically safe to do that.
    0:27:06 That’s obviously a ground foundation that you’ve got to give.
    0:27:08 There’s two ways to get to psychological safety by the way.
    0:27:12 You can hire for it where Ray Dalio does that.
    0:27:14 I think Amazon tries to do that.
    0:27:20 You hire for people that are resilient and capable of arguing and challenging each other.
    0:27:26 Not disrespectfully but just able to be stressful in their interaction sometimes even competitive.
    0:27:29 But it actually gets to a higher order product.
    0:27:31 That’s one solution.
    0:27:37 There’s another solution which is you build it through a sense of trust empathy and care for each other.
    0:27:43 One people one place in most conflict avoidance companies would say I’m not going to challenge our peers.
    0:27:45 That would be throwing them under the boss.
    0:27:48 Others would say course I’m going to challenge my peers.
    0:27:51 I wouldn’t dare let them fail right.
    0:27:57 So this perspective of care and commitment conflict does not mean disrespect.
    0:28:01 Conflict is healthy to get to a better answer.
    0:28:09 I would always bet on a company that had healthy and even sometimes unhealthy conflict at its core.
    0:28:16 Then a nice company that has political talking behind each other’s backs the meeting after the meetings the conflict avoidance.
    0:28:26 I would much prefer and that’s a lot of the Midwest nice companies that are mediocre and getting disrupted by these companies coming out of out of our area in the Bay.
    0:28:33 And how do you convince people that it’s OK to be candorous if that’s the right.
    0:28:38 How do you take them out of being avoiding and into candor and so easy.
    0:28:40 I just I introduce a practice.
    0:28:47 Literally when I say to a team here’s what we’re going to do before the meeting which I know is going to be contentious.
    0:28:49 Here’s a topic we’re going to discuss.
    0:28:54 But before we go in to discuss it I’m going to open a Google Doc and I’m going to have you all write down.
    0:28:57 What do you think there is the real problem we’re trying to solve here.
    0:28:59 And what do you think is a bold solution.
    0:29:03 And I don’t want any of you to to be conflict avoidant about it.
    0:29:07 We need to have this on the table so we can have a good conversation and get to the root of it.
    0:29:09 So that’s the pep talk I would give right.
    0:29:13 Now what I do know is you might still have some people holding back a little bit.
    0:29:17 But if you’re in meeting conversation if you had started the conversation in the meeting
    0:29:24 the average meeting would be a two in terms of its candor and its willingness to be courageous and challenge.
    0:29:28 This exercise increases psychological safety by 85 percent.
    0:29:35 And it puts people into a position where they’ve got time to think and be thoughtful and they write into the document.
    0:29:39 And now we have a much more candid dialogue that happened asynchronously.
    0:29:41 That’s just one example.
    0:29:44 The other thing is you have these and that’s a practice it’s called meeting shifting.
    0:29:49 Another practice is the candor break where you’re just telling people I want you to be candid.
    0:29:53 I’m going to turn what I want in my culture which isn’t present in most companies.
    0:29:55 I’m going to turn it into a simple assignment.
    0:29:59 Go talk in groups of two be candid to each other come back.
    0:30:03 You may not get 100 percent but you’ll get 80 percent and that’s the powerful shift.
    0:30:08 So the answer again is I don’t need to change your mindsets.
    0:30:10 I don’t need to help you grow a pair.
    0:30:12 I just need to have you do a simple practice.
    0:30:17 We’ve got all the practice is delineated in the book and it will bring the results you’re looking for.
    0:30:20 You use this word mindsets a couple of times.
    0:30:26 Are you saying that you believe that the work of Carol Dweck and the growth mindset is fundamentally wrong?
    0:30:32 Or are you just saying that the way to get to the mindset changes to do these simple practical things?
    0:30:33 Exactly. Exactly.
    0:30:37 Look, if you want a growth mindset, one of the things to do a great mindset is you need to be curious
    0:30:39 and you need to open yourself for new inputs.
    0:30:41 You need to mean more diverse.
    0:30:47 Well, in chapter one of the book, we teach you that your team is no longer your chart.
    0:30:51 So if you’re sitting in the marketing department or you’re sitting in a division or sales department
    0:30:56 and you used to collaborate just with yourselves, you’re not being very curious.
    0:30:57 You don’t have a growth mindset.
    0:31:03 But if you adopt a practice, which is reengineering and asking yourself, who is our real team here?
    0:31:07 Who’s our core team and who is our extended engaged team?
    0:31:09 In other words, who do we need to get the job done?
    0:31:13 And that all of a sudden becomes the team that you call the team.
    0:31:19 Then now you’ve just done a practice that opens you up to be more inclusive.
    0:31:23 And that practice will build that growth mindset because you’re going to start getting input.
    0:31:24 You’re like, wow, that was amazing.
    0:31:26 I never thought of that.
    0:31:27 Now, I want more of that input.
    0:31:33 And now we can use asynchronous collaboration and go ask for more of this input in documentation.
    0:31:39 Instead of meetings, now I can have faster, more inclusive, more innovative, bolder collaboration
    0:31:41 in a shorter period of time.
    0:31:45 And that is exactly what you would teach in the growth mindset.
    0:31:48 I’m just underlying the practices underneath it.
    0:31:57 Do you think that an AI chatbot could be part of this collaboration team that you’re talking about
    0:32:01 opening up Google Docs and letting people commenting into it?
    0:32:06 Could a chatbot be one of the team members and participate?
    0:32:09 Yeah, I don’t have a tool that does this.
    0:32:11 But here’s what I might imagine would happen soon.
    0:32:18 Somebody would take this book and it would actually open up and suggest to a team.
    0:32:23 If in the agenda, there’s a report out, it would say, why don’t we do this as a stress test?
    0:32:30 Or one might recommend prior to a meeting, hey, the last time you were together in this meeting,
    0:32:34 John, you spoke 80% of the time.
    0:32:41 Maybe this time before the meeting, it might be a good idea that you open yourself to hear other people’s points of view.
    0:32:43 And voices in this coming meeting.
    0:32:45 These are things AI can do.
    0:32:52 And I do believe that very soon we’re going to have AI coaches that will be just here on our shoulder at all times.
    0:32:55 So now let’s say I bought into this team ship concept.
    0:33:03 And I want you to explain how is hiring and onboarding and compensation different in a team ship?
    0:33:05 Yeah, it’s very interesting.
    0:33:11 In one of the chapters where I was talking to Enrique, the CEO of Hewlett Packard,
    0:33:15 he had a wonderful point of view, which is we need to hire for culture.
    0:33:17 We need to hire for diversity.
    0:33:22 And for people who say the slate isn’t really available to us to do that.
    0:33:25 They’re just being lazy and they’re not waiting long enough.
    0:33:27 Wait to build the right slate.
    0:33:34 Now, I think the interview tactics are going to different next week on the third of doesn’t matter what month it is because I’m not sure when this will air.
    0:33:39 But next week, I most likely I will have had a meeting by the time you hear this.
    0:33:46 And it’s I’m having 80 executives, half for CIOs and half for CHROs.
    0:33:54 And I’m bringing them together in New York City to talk about how that partnership of technology and people has to change.
    0:34:01 And one of the things I’m going to try to infuse in this group is folks, you need to be curious with an engineering mindset to rethink work.
    0:34:10 And neither of you is really bringing the partnership between technology, engineering work and human capital into a partnership as a group of three.
    0:34:15 One of the things we’re going to look at is what are the new skill sets that executives need to do all of this?
    0:34:22 And obviously, I’m giving out my book team ship because the idea is they have to team differently.
    0:34:35 Like this idea that the three of these individuals, the actual work business engineers, the IT professionals and the human capital professionals, we need to change our practices in how we collaborate.
    0:34:40 And that’s going to be a really important area that I think I hope this is my evangelization.
    0:34:47 This is why I’m not having lunch right now, but I’m here talking to you because I want to get out into the world.
    0:34:52 This call to action that it’s about time that we change work. We really do.
    0:34:57 It’s about time that we change work and stop dragging ourselves through the old ways of working.
    0:35:05 So if I’m the chief recruiting officer of a company that has bought into team ship and I say to you, Keith, OK, so tell me, what am I looking for?
    0:35:09 Am I looking for Ivy League background, relevant work experience?
    0:35:14 And what am I looking for to foster the success of a team ship?
    0:35:17 I might say start with this is too easy.
    0:35:24 Start with somebody who has thrived in team sports athletics, somebody who has an experience in it.
    0:35:32 Not somebody who was a runner or an individual sports, you know, enthusiast, try to find team sports enthusiasts.
    0:35:35 I would also might suggest that you find people who have been in the military.
    0:35:42 I understand the perspective of hierarchy in the military, but the military engineers for team ship,
    0:35:47 if the sergeant is killed in battle, I’m going to butcher the analogy here.
    0:35:52 But if the leader is killed in battle, the team steps up and the team knows how to step up.
    0:35:58 I’ve often been told by General McChrystal that you don’t take a you don’t take a hill for your country.
    0:36:01 You take a hill for your buddy who’s next door to you, standing next to you.
    0:36:10 This is the sense of team ship is implicit in getting the most out of a group of young men and women where, you know, everything is at stake.
    0:36:14 So I feel like there’s experiences that you would look for.
    0:36:16 Interestingly enough, I didn’t have those.
    0:36:17 I was a wrestler all my life.
    0:36:22 But starting in fifth grade in Pittsburgh, all throughout school, I was a wrestler.
    0:36:25 And and I felt that I had to do a lot myself.
    0:36:29 I was just that pull up by the bootstraps, believe in the American dream.
    0:36:32 And I’ve had to unpack a lot.
    0:36:35 My research is far out ahead of my natural instincts.
    0:36:43 My natural instincts is to be much more hub and spoke, control oriented kind of a leader, and I have to fight it all the time.
    0:36:45 Up next on Remarkable People.
    0:36:54 If you’re the CEO and you’ve got shareholders that you’re responsible to having a goal of doubling shareholder value.
    0:36:59 I don’t think the shareholders that you have to be accountable to are going to call it in SIPPET.
    0:37:05 Thank you to all our regular podcast listeners.
    0:37:08 It’s our pleasure and honor to make the show for you.
    0:37:15 If you find our show valuable, please do us a favor and subscribe, rate and review it even better.
    0:37:19 Ford it to a friend, a big mahalo to you for doing this.
    0:37:24 Welcome back to Remarkable People with Guy Kawasaki.
    0:37:32 It’s very funny because we have a lot of overlap data.
    0:37:39 When I was a CEO, I hired two people from the Stanford wrestling team and you’re right.
    0:37:48 That’s not a quote team sport, but I got to tell you, when you hire a wrestler, you know you’re getting somebody who’s gritty.
    0:37:58 Because even if you’re on a division one wrestling team, it’s not like you’re going to get a professional wrestling contract and it’s not like basketball or baseball or football, right?
    0:38:02 It’s pure grit and wrestlers never give up.
    0:38:10 I was just going to say the sense that the one thing that I can say about myself as a wrestler and as a leader is I never give up.
    0:38:14 And people will say that the resilience and the grit like you’re just judging.
    0:38:17 But the other thing is I remember when I was a wrestler, I was the kid.
    0:38:26 That if our heavyweight was sick or out, they put me in that’s like four weights above my weight class.
    0:38:29 They would put me in because they knew I would never get pinned.
    0:38:33 I would rather dislocate my shoulder that get pinned.
    0:38:42 And that’s the kind of individual that I think wrestler wars, but it’s different, by the way, than somebody who learns how to pass the ball to win.
    0:38:45 And that’s the difference in teamship.
    0:38:49 As we’re let’s stay on the sports analogy for one more time.
    0:38:50 You’re going to lose me.
    0:38:59 I think when people I love sports analogies, when you say this uses sports team analogy, I just want to be clear for people.
    0:39:02 You’re not referring to the quarterback, right?
    0:39:04 You’re more referring to the offensive line.
    0:39:07 I would think what I what I’m referring to.
    0:39:09 So a friend of mine owns a couple of teams.
    0:39:15 His name is Peter Goober and he owns he’s one of the owners of the Warriors and he’s one of the owners of the Dodgers.
    0:39:19 And and what I and by the way, anyway, that’s a riff.
    0:39:28 But what I can say is that it’s when I’ve talked to him and I’ve talked to his players, what happens in the locker room at halftime?
    0:39:37 Not from what the coach does, but what the team does, what happens in the huddle and how the team gives feedback on plays and where they’re going.
    0:39:38 It’s extraordinary, right?
    0:39:40 So that’s what I’m talking about.
    0:39:48 We don’t, you know, I was talking to the woman who led to victory, the women’s soccer team a few years ago.
    0:39:57 And just this idea of taking a group of exceptional individual talent and turning it into a team that won’t let each other fail.
    0:40:04 There’s a phrase that I use in the book, crossing the finish line together to make a group of people realize that we don’t win until we all win.
    0:40:09 And that’s a different mindset than a lot of what companies have and a lot of teams have.
    0:40:11 And we need to instill that.
    0:40:15 You mentioned the name Stanley McChrystal.
    0:40:15 Yeah.
    0:40:19 And I take it you hold him high if guard.
    0:40:20 I just know him.
    0:40:22 I remember walking.
    0:40:27 I remember he had just exited or been exited from the military and he was at the Ted conference.
    0:40:33 I think he might have even been speaking and and he and I and my heart was touched by what he had gone through.
    0:40:35 I always like underdogs.
    0:40:40 I not I just always love people who are suffering through their remorse and I like to be of service.
    0:40:45 So he and I went for a long walk and he was talking about starting a professional services firm, etc.
    0:40:49 And I learned a lot from him and I’ve learned a lot from people in the military.
    0:40:54 But anyway, I do have a affinity to him, but you may have a different perspective.
    0:40:55 No, no, absolutely.
    0:40:57 And did you read his book risk?
    0:40:58 Yeah.
    0:41:00 Yeah, I love that book.
    0:41:03 I think it was like Peter Drucker quality book.
    0:41:04 I loved his book.
    0:41:05 He’s a brilliant guy.
    0:41:12 And you know, like you can see his strategic mind put to to business.
    0:41:14 Yeah, I’m a huge fan.
    0:41:20 I think if you read risk and you read never late alone, you’d pretty much be covered.
    0:41:24 You don’t need to read any more leadership books.
    0:41:25 I appreciate that.
    0:41:27 But I’m going to we’re going to excerpt just that.
    0:41:31 We’re going to just that you can quote me.
    0:41:32 We’re going to that’s a great quote.
    0:41:34 That’s a great quote.
    0:41:35 I got two more questions for you.
    0:41:41 So first question is, how do you get people to break out of silos?
    0:41:48 Yeah, it’s using this tool that I mentioned before not to be stuck too much on it of asynchronous
    0:41:51 collaboration and redefining team.
    0:41:53 So you put those two things together.
    0:41:57 So look, the average I was the other day at a big insurance company and they were going
    0:41:59 through a massive transformation.
    0:42:04 They were hoping to double their share price in less than five years and they’re on their
    0:42:05 way to doing that.
    0:42:09 But they felt like there was some stuck in the wheels.
    0:42:10 And I stood in front of this large group of folks.
    0:42:15 I said, pick one critical initiative that you believe will help significantly advantage
    0:42:17 the growth of this business.
    0:42:21 And I want you to ask yourself, and this is an initiative that you think you could make
    0:42:23 impact on.
    0:42:25 First question is, who’s your team?
    0:42:30 And I really coach them to think about team, not as an order chart, not as silos.
    0:42:31 Just who’s your team?
    0:42:33 Now, I was physically with this group.
    0:42:35 I said, tonight, do me a favor.
    0:42:40 I want you to find somebody outside of your organization who is a critical teammate that
    0:42:42 you haven’t been treating as a teammate.
    0:42:46 I want you to go up to them at dinner tonight and I want you to let them know what the passion
    0:42:52 you have for this project and invite them in, not to your team, but invite them in to
    0:42:56 a co-creation, invite them into their team with you.
    0:43:01 Invite them into their team and say, this initiative could be something, but we’re not
    0:43:04 going to get from here to there without you.
    0:43:06 And invite them into a different team.
    0:43:10 And when you do that, you give people that path.
    0:43:12 It just starts breaking down silos.
    0:43:13 People are lazy.
    0:43:14 I mean, they’re busy.
    0:43:15 I shouldn’t say lazy.
    0:43:16 People are busy.
    0:43:17 They’re preoccupied.
    0:43:20 And the natural reaction is, we’re going to work in all ways of working.
    0:43:22 I’m going to work in my silo.
    0:43:25 I’m going to plug it in and it’ll plug into something, some other silo.
    0:43:29 And when there’s a problem that silos aren’t working together, then I’m going to be resentful
    0:43:31 and I’m going to try to get what I want.
    0:43:34 But if I don’t get it when it was run, it’s going to turn into bad behavior.
    0:43:35 That’s old ways of working.
    0:43:38 And we got to just simple new practices.
    0:43:43 We’ll break down old traditional things that are crushing our organizations today.
    0:43:44 Now, I think AI is going to help.
    0:43:51 I really do think that I’m very hopeful that AI is going to change our lives, including
    0:43:56 take this book and engineer it into our work process as coaches.
    0:44:01 I’m going to back up about five minutes and ask you a question here, Sol.
    0:44:07 You started off this example about this company and they said that they wanted to double their
    0:44:10 share price as the goal.
    0:44:14 So do you ever hear a goal like that and you say, that’s the wrong kind of goal?
    0:44:16 The goal is not doubling your share price.
    0:44:20 The goal is, I don’t know, excellence or leadership or something.
    0:44:25 Do you ever push back on that kind of, seems to me, insipid goal?
    0:44:32 If you’re the CEO and you’ve got shareholders that you’re responsible to having a goal of
    0:44:37 doubling shareholder value, I don’t think the shareholders that you have to be accountable
    0:44:39 to are going to call it insipid.
    0:44:44 But that said, and also I’m newly a venture partner at a VC called Lightspeed.
    0:44:48 And I sit in these meetings now, these partner meetings that I’d never been, had exposure
    0:44:52 to with such deep respect for what it takes to be a VC.
    0:44:58 A lot of my friends are VCs, but they’re not, they’re just rich people spending money.
    0:45:02 That’s different than a real VC, like the rigor of these organizations like Lightspeed
    0:45:03 that I see.
    0:45:07 But look, engineering value creation is important.
    0:45:14 But that said, what I can say is the same organization has had a vision of being, like
    0:45:18 they’ve said, we want to be the envidia of insurance.
    0:45:19 Okay.
    0:45:20 Now, what does that mean?
    0:45:21 How do you engineer a product?
    0:45:26 How do you engineer a level of customer experience and satisfaction and how do you re-engineer
    0:45:28 the business?
    0:45:32 And I literally spent an entire afternoon with these folks asking a simple question.
    0:45:37 How does AI transform the customer experience and create extraordinary value?
    0:45:42 And of course, following that path, you’ll get to shareholder value, but it really is
    0:45:43 about the customer experience.
    0:45:48 I would say that if any of these companies have a goal of re-engineering shareholder
    0:45:52 value, but they’re looking at it only from finance, not looking at it from a perspective
    0:45:55 of re-engineering the customer experience, then I think you’re right.
    0:45:56 That’s insipid.
    0:45:57 Okay.
    0:45:58 So we’re both right.
    0:46:00 I think we’re both in the same target.
    0:46:01 Yeah.
    0:46:02 Okay.
    0:46:07 So I’m going to read you a quote from your book, and I just, when did you write this
    0:46:08 book?
    0:46:09 And like a year ago?
    0:46:11 I shipped it a year ago, right?
    0:46:14 But I was writing it for the last 20 years.
    0:46:15 It’s funny.
    0:46:18 When I wrote my first book, “Nevered Alone,” people said, “How long did it take you to
    0:46:19 write that book?”
    0:46:21 I said, “Well, 35 years.”
    0:46:23 I tell people that too.
    0:46:24 Yeah.
    0:46:25 Go ahead.
    0:46:26 But what was the quote?
    0:46:32 So this quote is, “The most innovative teams relish and build greatness out of diverse
    0:46:34 perspectives.”
    0:46:40 So basically you’re supporting DEI, but DEI doesn’t seem to be so popular anymore.
    0:46:44 I mean, what’s the deal here?
    0:46:46 You can’t say that in Florida.
    0:46:47 Yeah.
    0:46:48 Now it is funny.
    0:46:50 I was actually just in Florida the other day and had to ask myself, am I allowed to say
    0:46:52 this on stage here?
    0:46:55 So here’s what I did, and I love this.
    0:47:00 Lencioni’s book inspired me 20 years ago to study the subject, five dysfunctions of
    0:47:01 a team.
    0:47:05 But today, 20 years later, there’s a lot of difference about teams.
    0:47:12 And one of the things I wanted to ask myself was, where is the DEI journey in teams today?
    0:47:13 What does it look like?
    0:47:18 So I went out and I asked 26, I was at Davos a few years ago, and I started this research
    0:47:19 there.
    0:47:22 I asked 26 heads of DEI, a simple question.
    0:47:28 If you had a team that you were responsible for coaching for the next six months, what
    0:47:34 would you do with that team to make them a shining emblem of DEI for your organization,
    0:47:37 for shareholder value, for the customer experience, for employee engagement?
    0:47:38 What would you do?
    0:47:43 None of them had an answer, because not right away, because that’s not the lens that they
    0:47:44 look at the world.
    0:47:48 DEI looked at the world in terms of enterprise equity.
    0:47:49 They looked at policies.
    0:47:54 They looked at so many different things, but I was asking you to look at what the value
    0:47:57 creation opportunity was of DEI at the team level.
    0:47:59 I found out a few things.
    0:48:03 I’d already written most of the book when I was having this conversation, and I found
    0:48:10 out that the diversity is born into chapter one when we really are asking ourselves, who
    0:48:15 is the real team and what voices do we need to have heard?
    0:48:19 What diverse set of voices do we need to have heard that will give us a more exponential,
    0:48:22 a more breakthrough set of thinking?
    0:48:23 Equity.
    0:48:28 The equity that I got, the lesson that I heard from Enrique, the CEO of Hewlett Packard,
    0:48:32 is listen, people say that you can’t get a diverse slate, bullshit.
    0:48:36 You wait until you have a diverse slate that’s exceptional and inspires you.
    0:48:39 That’s why their equity is what it is.
    0:48:42 Inclusion, I found it peppered throughout the whole book.
    0:48:46 If you make sure every voice is heard in a meeting, if you make sure that asynchronous
    0:48:51 collaboration is the primary form of collaboration, if you’re reaching out to diverse, breaking
    0:48:56 down silos, getting inputs, all of that crushes it on the inclusion.
    0:49:01 What we found was most of the DE&I agenda is marbled into this book.
    0:49:05 Then we added a chapter when I really interrogated to them, I was like, “What about this thing
    0:49:06 called belonging?
    0:49:07 How do you get people to feel like belonging?”
    0:49:11 Well, that’s chapter four when it comes to the intimacy and connection of having each
    0:49:12 other’s back.
    0:49:14 How about otherness and sameness?
    0:49:20 So I really got into it, and I marbled those in practices, and I do believe that anybody
    0:49:26 who wants to embrace a diverse and equitable agenda can find the roadmap in here, but it’s
    0:49:29 not about checking a box.
    0:49:35 It’s about making the work better because it is listening to a diverse set of inputs
    0:49:38 that will inspire us to have better outputs.
    0:49:40 That’s how I want to end.
    0:49:46 No, actually, I know you’re going to do a world-class one of these, so I’m going to
    0:49:52 ask you to do this, not just for your own benefit, but so people can hear what a world-class
    0:49:54 thing you’re going to do.
    0:50:01 You’re on deck, and I want you to just summarize and pitch your book to my listeners.
    0:50:02 This is it.
    0:50:03 Go for it, Keith.
    0:50:04 All right.
    0:50:06 I want to see your evangelism in action.
    0:50:07 All right.
    0:50:08 Thank you, brother.
    0:50:14 Look, I believe we’ve over-indexed on leadership, and we’ve under-indexed on team-ship.
    0:50:21 The potential of asking a team to step up and meet you as a leader in the leadership.
    0:50:25 I think it’s great that a leader gives feedback, but I want the team to give each other feedback.
    0:50:27 I want the team to hold each other accountable.
    0:50:29 I want the team to lift each other’s energy.
    0:50:33 The principle of team-ship will allow you to achieve things you’ve never been able to
    0:50:39 achieve before because the team will be giving you so much more, and it’s not just a roadmap
    0:50:40 for a leader.
    0:50:41 It’s a roadmap for the team itself.
    0:50:42 Wow.
    0:50:45 How’d I do?
    0:50:48 How’d I do?
    0:50:51 That is definitely a remarkable moment there.
    0:50:52 It’s a key.
    0:50:55 Thank you very much for giving up your lunch for me.
    0:50:59 I appreciate this very much.
    0:51:04 I am so honored and grateful to be back here with you and love following your journey and
    0:51:05 all the work that you do.
    0:51:06 Thank you very much.
    0:51:08 You’re too kind.
    0:51:13 You’ve just got through listening to Keith Farazzi, and his new book is called Never
    0:51:17 Lead Alone, and I promise you, it’ll make you more remarkable.
    0:51:20 This is the Remarkable People podcast.
    0:51:21 I’m Guy Kawasaki.
    0:51:27 My thanks to Madison Nizmer, the producer and co-author of my book, Tessa Nizmer, who
    0:51:33 is our ACE researcher, Jeff C., and Shannon Hernandez, who’s our audio team.
    0:51:37 That’s the Remarkable People team, and thank you, Keith.
    0:51:42 Until the third time we bring you back, just let us know what we can do.
    0:51:43 Thank you very much.
    0:51:50 Mahalo and Aloha.
    0:51:52 This is Remarkable People.

    Join Guy Kawasaki for an enlightening conversation with Keith Ferrazzi, pioneering thought leader and bestselling author. In this episode of Remarkable People, they explore the groundbreaking concept of “teamship” and why traditional leadership models need to evolve. Ferrazzi shares powerful insights from his decades of research on high-performing teams and introduces practical methods for transforming group dynamics. Discover how to unlock your team’s full potential through candor, psychological safety, and purposeful collaboration.

    Guy Kawasaki is on a mission to make you remarkable. His Remarkable People podcast features interviews with remarkable people such as Jane Goodall, Marc Benioff, Woz, Kristi Yamaguchi, and Bob Cialdini. Every episode will make you more remarkable.

    With his decades of experience in Silicon Valley as a Venture Capitalist and advisor to the top entrepreneurs in the world, Guy’s questions come from a place of curiosity and passion for technology, start-ups, entrepreneurship, and marketing. If you love society and culture, documentaries, and business podcasts, take a second to follow Remarkable People.

    Listeners of the Remarkable People podcast will learn from some of the most successful people in the world with practical tips and inspiring stories that will help you be more remarkable.

    Episodes of Remarkable People organized by topic: https://bit.ly/rptopology

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  • Terry Sejnowski: ChatGPT and the Future of AI

    Terry Sejnowski: ChatGPT and the Future of AI

    AI transcript
    0:00:02 (upbeat music)
    0:00:10 – Hi, everybody, it’s Guy Kawasaki.
    0:00:13 This is the Remarkable People podcast.
    0:00:15 And as you well know,
    0:00:17 I’m on a mission with the rest of the team
    0:00:19 to make you remarkable.
    0:00:22 And today we have a really special guest.
    0:00:23 His name is Terry Sainowski.
    0:00:26 And I gotta tell you, our topic is AI
    0:00:29 and nobody likes AI more than I do.
    0:00:31 And he has just written a book,
    0:00:34 which I found very useful.
    0:00:38 It’s called “Chat GPT and the Future of AI.”
    0:00:42 Now, Terry has one of the longest titles
    0:00:45 I have ever encountered in this podcast,
    0:00:47 so I gotta read it here.
    0:00:51 Terry is the Francis Crick Chair
    0:00:55 at the Salk Institute for Biological Studies
    0:00:57 and Distinguished Professor
    0:01:00 at the University of California at San Diego.
    0:01:03 And that’s your LinkedIn page must be really something.
    0:01:05 So thank you very much, Terry.
    0:01:07 Welcome to the show.
    0:01:08 – Oh, great to be here.
    0:01:10 Thanks for inviting me.
    0:01:12 – There’s nothing we like more
    0:01:14 than to help authors with their new books.
    0:01:18 So we’re gonna be making this mostly about your book.
    0:01:21 And I think that the purpose is
    0:01:23 people listen to this episode
    0:01:25 and at the end they feel compelled to buy your book.
    0:01:28 And if you just stop listening right now,
    0:01:32 you should just trust me and buy this book, okay?
    0:01:34 I have a question from left field.
    0:01:36 So I noticed something.
    0:01:38 At the end of chapter one,
    0:01:41 you ask like a series of questions
    0:01:44 about to help you understand chapter one.
    0:01:46 And the 10th question is, let me read.
    0:01:49 Who is Alex the African Gray Parrot?
    0:01:53 And how does he relate to the discussion of LLMs?
    0:01:55 And I read that, Terry.
    0:01:58 And I said, where did he ever mention Alex,
    0:02:00 the African Gray Parrot?
    0:02:02 So I went back and I searched and searched
    0:02:05 and I could not find the pronoun Alex anywhere.
    0:02:08 And then so I bought the Kindle version
    0:02:11 so I could search digitally and I searched for parrot.
    0:02:14 And there’s like one sentence that says,
    0:02:17 critics often dismiss LLMs by saying
    0:02:21 they are parroting excerpts from the vast database
    0:02:23 used to train them.
    0:02:26 So that’s the only reference
    0:02:28 that people were supposed to get.
    0:02:30 Alex, the parrot, was that a test
    0:02:32 to see how careful people read?
    0:02:36 – Well, first of all, it’s in the footnotes,
    0:02:38 at the end notes at the end of the book.
    0:02:41 So it’s in that chapter if you look at it.
    0:02:46 And Alex the Gray Parrot was a really quite remarkable parrot
    0:02:49 that was taught to speak English.
    0:02:51 Irene Pepperberg, I don’t know if you know her,
    0:02:53 but she taught it not just to speak English,
    0:02:57 but to tell you the color of, say, a block of wood
    0:02:59 and how many blocks are there
    0:03:00 and what’s the shape of the block?
    0:03:03 Is it square or is it sort of unbelievable?
    0:03:08 And it shows how remarkable some animals are.
    0:03:09 We can’t speak parrot,
    0:03:11 but some of them can speak English, right?
    0:03:15 – So in a sense, it’s like when Jane Goodall
    0:03:17 discovered that chimpanzees had social life
    0:03:19 and could use tools, right?
    0:03:21 – Well, it’s exactly the same.
    0:03:23 I think humans are very biased
    0:03:26 against the intelligence of other animals
    0:03:28 because they can’t talk to us.
    0:03:32 Now, the irony is that here comes chat GPT
    0:03:34 and all the large language models.
    0:03:37 It’s as if an alien suddenly arrived here
    0:03:40 and could speak to us in English.
    0:03:42 And the only thing we can be sure of is it’s not human.
    0:03:45 And so if it’s not human, what is it?
    0:03:48 And now that we have this huge argument going on
    0:03:52 between the people who say they’re stochastic parrots,
    0:03:56 they’re just parroting back all the data they were trained on.
    0:04:00 Without understanding that you can ask questions
    0:04:03 that were never asked or never in the world database,
    0:04:06 the only way that it can answer it
    0:04:08 is if it generalize from what’s out there
    0:04:10 or not what exactly is out there.
    0:04:10 So that’s one thing.
    0:04:13 But the other thing is that they say that,
    0:04:15 okay, it seems to be responding,
    0:04:17 but it doesn’t really understand what it’s saying.
    0:04:22 And what it has shown us is we don’t understand
    0:04:23 what understanding is.
    0:04:25 We don’t understand how humans understand.
    0:04:27 So how are we going to say?
    0:04:29 – So in other words, people should give parrots
    0:04:31 more credit than they might.
    0:04:34 – That’s for sure.
    0:04:36 I’m convinced of that.
    0:04:38 And I think it’s not just that.
    0:04:39 I think it’s a lot of animals out there.
    0:04:44 The orcas and chimps and a lot of species
    0:04:46 really are very sophisticated.
    0:04:48 Look, they all had to have survived in their niche, right?
    0:04:50 And that takes intelligence.
    0:04:52 – All right, you will be able to see this more and more
    0:04:55 as we progress, but I really enjoyed your book.
    0:04:57 And I did a lot of things that you said to try.
    0:05:00 So I’m gonna give you an example.
    0:05:05 So I asked ChatGPT, should the Bible be used as a text
    0:05:09 in public elementary schools in the United States?
    0:05:12 And ChatGPT says, using the Bible as a text
    0:05:14 in public elementary schools in the US
    0:05:18 is a contentious issue due to the following considerations.
    0:05:21 And I won’t read every word, but constitutional concerns,
    0:05:26 educational relevance, community values, legal precedent.
    0:05:29 So my question from all of this is like,
    0:05:34 how can an LLM have such a cogent answer
    0:05:37 when people are telling me,
    0:05:41 oh, all an LLM is doing is statistics and math
    0:05:43 and it’s predicting what’s the next syllable
    0:05:45 after the previous syllable.
    0:05:47 It looks like magic to me.
    0:05:51 So can you just explain how an LLM could come up
    0:05:53 with something that cogent?
    0:05:56 – So you’re right, that it was trained
    0:05:57 on an enormous amount of data,
    0:06:01 trillions of words from the internet, books,
    0:06:05 newspaper, articles, computer programs.
    0:06:08 It’s able to absorb a huge amount of data.
    0:06:13 And it was trained simply to predict the next word
    0:06:14 in the sentence.
    0:06:18 And it got better and better and better and better.
    0:06:21 And here’s, I think what’s going on.
    0:06:23 We really don’t know for sure what’s going on
    0:06:26 inside this network, but we’re making some progress.
    0:06:30 So words are ambiguous, they often have multiple meanings.
    0:06:32 And the only way you’re gonna figure that out
    0:06:34 is the context of the word.
    0:06:36 That means previous words,
    0:06:38 what’s the meaning of the sentence.
    0:06:39 And so in order to get better,
    0:06:43 it’s going to have to develop internal representations.
    0:06:47 By representation, I just mean a kind of a model
    0:06:49 of what’s happening in the sentence.
    0:06:53 But it’s gotta have a semantic information, meaning.
    0:06:54 It has to be based on meaning.
    0:06:56 It also has to understand syntax, right?
    0:06:58 It has to understand the word order.
    0:07:01 And that’s very important in linguistics.
    0:07:05 And so all of that has to be used as hints, as clues,
    0:07:08 as to how to predict the next word.
    0:07:11 But now that you have it trained up
    0:07:14 and you give it a question,
    0:07:17 now it’s gotta complete the next word,
    0:07:19 which is gonna be the answer to the question.
    0:07:21 And it gets the next word.
    0:07:23 It’s a feed forward network, by the way.
    0:07:25 But then it loops back to the input.
    0:07:29 So it now knows what its last word was.
    0:07:30 And then it produces the second word
    0:07:33 and it goes over, over again and again,
    0:07:36 until it reaches some stop.
    0:07:38 That is, I don’t know how they program that.
    0:07:40 ‘Cause sometimes it goes on for pages,
    0:07:42 depending on what you ask it to do.
    0:07:44 – I understand what you just said.
    0:07:48 Every day, it’s just magic to me.
    0:07:51 I am, in a sense, like a lot of people are concerned
    0:07:56 that we don’t know how exactly an LLM did that.
    0:07:58 But then my counter argument to them would be,
    0:08:01 how well do we understand the human brain?
    0:08:02 That doesn’t upset you so much.
    0:08:04 Why is it so upsetting
    0:08:07 that you don’t know how an LLM thinks?
    0:08:11 – And also the complaint is this chat GDP is biased.
    0:08:13 And the same argument that you just gave
    0:08:15 is that humans are biased too.
    0:08:19 And then I ask, okay,
    0:08:22 do you think it’s gonna be easier to fix the LLM
    0:08:23 or the human decision?
    0:08:26 (laughing)
    0:08:29 – I think we know the answer to that question.
    0:08:35 I often talk in front of large tech audiences
    0:08:37 and AI is often the topic.
    0:08:40 And when these skeptics come up
    0:08:44 and they say that LLM is gonna cause the nuclear wars
    0:08:46 and all that, I ask them this question.
    0:08:50 I say to them, let’s suppose that you have to have
    0:08:52 something control nuclear weapons.
    0:08:55 Let’s take it as a given we have nuclear weapons.
    0:09:00 So who would you rather have control nuclear weapons?
    0:09:05 Putin, Kim Jong-un, Netanyahu or chat GPT.
    0:09:08 And nobody ever says, oh yeah,
    0:09:09 I think Putin should do it.
    0:09:12 So last night I asked chat GPT this question
    0:09:16 and it says, I wouldn’t choose to launch a nuclear weapon.
    0:09:20 The use of nuclear weapons carry severe humanitarian
    0:09:22 and environmental consequences.
    0:09:25 And the global consensus is to work towards disarmament
    0:09:29 and ensure such weapons are never used.
    0:09:30 That is more intelligent answer
    0:09:32 than any of those people I listed.
    0:09:35 – It is remarkable at the range.
    0:09:38 It’s not just giving sensible answers.
    0:09:41 It often says things that make me think twice.
    0:09:44 And also, I don’t know if you’ve tried this,
    0:09:47 but it turns out that they also are very good at empathy,
    0:09:48 human empathy.
    0:09:50 In the book that I had this little excerpt
    0:09:54 from a doctor whose friend had cancer
    0:09:55 and he didn’t know quite what to say.
    0:09:59 So he got some advice from chat GPT
    0:10:02 and he was so much better than what he was going to say.
    0:10:05 And then at the end, it’s been back to chat GP
    0:10:07 and said, oh, thank you so much for that advice.
    0:10:09 It really helped me.
    0:10:11 And he said, you are a very good friend.
    0:10:15 You really helped her, it’s like starting to console him.
    0:10:18 And where does that come from?
    0:10:22 It turns out that human empathy is magic,
    0:10:27 but it is embedded indirectly in lots of places
    0:10:31 where humans are like writing about their experiences
    0:10:34 or biographies or just novels
    0:10:37 where doctors are empathizing.
    0:10:38 I don’t know, no one really knows exactly,
    0:10:40 but they must be there somewhere.
    0:10:43 – It’s kind of blown away the Turing test, right?
    0:10:46 You mentioned in your book,
    0:10:49 this concept of the reverse Turing test
    0:10:52 where instead of a human testing or a computer
    0:10:54 is testing a human.
    0:10:58 And Terry, I think that is a brilliant idea.
    0:11:03 Couldn’t you have a chat bot interview a job applicant
    0:11:07 and decide if that job applicant is right for the job
    0:11:10 better than a human could?
    0:11:13 – I think it would need a little bit of fine tuning,
    0:11:16 but I’m sure it could do a good job.
    0:11:18 And a lot of companies actually are using it,
    0:11:19 but here’s the problem.
    0:11:24 The problem is that if a company wants the best employee
    0:11:27 based on all the database from the company
    0:11:30 of people who have done well and people who haven’t,
    0:11:32 but what if there are some minorities
    0:11:35 that haven’t done very well for various reasons?
    0:11:38 There’s gonna be a bias against other minorities.
    0:11:40 Well, you can in fact put in guardrails
    0:11:43 and prevent that from happening.
    0:11:46 In fact, if that is a goal that you have is diversity,
    0:11:48 you should put that into the cost function.
    0:11:51 Or actually they call it a loss function,
    0:11:55 but it’s really waiting the value of what is it
    0:11:57 that you’re trying to accomplish.
    0:12:00 Has to be told explicitly, you just can’t assume.
    0:12:04 – But if a chat bot was interviewing a job prospect,
    0:12:07 I would think that the chat bot doesn’t care
    0:12:09 about the gender of the person,
    0:12:11 doesn’t care about the skin color,
    0:12:14 the person may have an accent or not.
    0:12:17 There’s a lot of things that humans react to
    0:12:20 that would not affect the chat bot, right?
    0:12:24 – Okay, okay, so actually I was slightly different.
    0:12:26 I was giving you the scenario
    0:12:28 where a company is trying to hire somebody
    0:12:30 and they have specific questions they ask.
    0:12:33 But if you just have a informal chat,
    0:12:36 you’re absolutely right that the large language model
    0:12:40 doesn’t know ahead of time who it’s talking to.
    0:12:43 And it doesn’t even know what persona to take
    0:12:44 ’cause it can adopt any persona.
    0:12:47 But with time, with answering questions,
    0:12:50 it will get a sense for what level of answer is expected
    0:12:54 and what the intelligence of the interviewer is.
    0:12:57 But, and there’s many examples of this in my book,
    0:13:00 you could use that, somebody could take that.
    0:13:02 And then, in fact, I even tell people,
    0:13:06 I said, look, here’s four people who have had interviews
    0:13:11 and I want you to rate the intelligence of the interview
    0:13:13 and how well it went.
    0:13:15 And it was really quite striking
    0:13:18 how the more intelligent the questions,
    0:13:20 the more intelligent the answers.
    0:13:24 – So in a sense, what you’re saying is that
    0:13:27 if an LLM has hallucinations,
    0:13:29 it might not be the LLM’s fault
    0:13:33 as much as the person who created the prompts.
    0:13:33 – I would say not.
    0:13:35 I think hallucinations are a little bit different
    0:13:38 in the sense that it will hallucinate
    0:13:40 when there’s no clear answer.
    0:13:43 It feels compelled to give you an answer.
    0:13:44 I don’t know why.
    0:13:46 And it will make one up.
    0:13:48 But it doesn’t make up a trivial answer.
    0:13:51 It’s very detailed, it’s very plausible.
    0:13:53 Like they’ll give a reference to a paper,
    0:13:54 it doesn’t exist, right?
    0:13:58 That’s really taking a large effort
    0:14:02 to try to convince you that it’s got the right answer.
    0:14:05 So hallucinations are really, again,
    0:14:08 something that humans, people hallucinate.
    0:14:13 And it’s not just because they’re trying to lie.
    0:14:16 Our memory is reconstructing the past.
    0:14:18 It doesn’t memorize things.
    0:14:20 And it will fill in a lot of blanks
    0:14:23 with things that are plausible.
    0:14:25 And I think that’s exactly what’s happening here.
    0:14:29 I think that when it arrives at something
    0:14:31 where it doesn’t know the answer,
    0:14:33 it hasn’t been trained to tell you that, right?
    0:14:37 It hasn’t been trained, it could be.
    0:14:39 But in the absence of that, it does the best it can.
    0:14:42 (upbeat music)
    0:14:55 – You had a section in your book
    0:14:58 where you asked via these very simple prompts,
    0:15:01 like who holds the record for walking from,
    0:15:02 I don’t know, whatever you said,
    0:15:04 England to Australia or something.
    0:15:06 And the first answer was, yeah,
    0:15:09 they gave a name and a which Olympics and all that.
    0:15:13 So I went back last night and I asked a similar question,
    0:15:17 like who first walked from San Francisco to Hawaii?
    0:15:21 And the answer was no one has walked from San Francisco
    0:15:23 to Hawaii as it is not possible
    0:15:26 to walk across the Pacific Ocean.
    0:15:28 The distance between San Francisco and Hawaii
    0:15:31 is over 2,000 miles, primarily over open water.
    0:15:33 However, many people have traveled this route
    0:15:35 by airplane or boat.
    0:15:38 So are you saying that between the time you wrote your book
    0:15:41 and the time I did the tests
    0:15:44 that LLMs have gotten that much better?
    0:15:46 – First of all, that first question was asked
    0:15:48 by Doug Hofstadter,
    0:15:52 who’s a very clever cognitive scientist, computer scientist.
    0:15:55 But he was trying to trip it up, clearly.
    0:15:58 And I think that it probably decided
    0:15:59 it would play along with him
    0:16:01 and just give a silly answer, right?
    0:16:03 Silly question gets a silly answer.
    0:16:06 And I think that with you,
    0:16:08 it probably sized you up and said,
    0:16:10 wow, this guy’s a lot smarter than I think.
    0:16:12 There’s a smart answer.
    0:16:15 – You’re saying I’m smarter than Doug Hofstadter.
    0:16:17 – Your prompts were smarter.
    0:16:22 – I can stop the interview right there.
    0:16:29 So, I mean, there are just these jewels in your book
    0:16:31 and you drop this jewel
    0:16:34 that it takes 10 hours to become a good prompt.
    0:16:36 I call it baller.
    0:16:38 So you can be a baller with prompts in 10 hours.
    0:16:41 And that’s a thousand times faster
    0:16:44 than Malcolm Gladwell’s 10,000 hours.
    0:16:46 So can you just give us the gist?
    0:16:48 Like people are listening, say, okay,
    0:16:52 so how do I become a great prompt writer?
    0:16:54 – It does take practice.
    0:16:57 And the practice is you learn the ropes,
    0:17:00 just the way you learn to do drive a car
    0:17:02 or anything that for which you need skills
    0:17:03 or playing tennis, right?
    0:17:08 You have to know how to adjust your responses
    0:17:10 and to get what you want.
    0:17:12 But there are some good rules of thumb
    0:17:15 and in the book, I actually have a bunch
    0:17:18 that I was able to get from people
    0:17:20 who have had a lot of experience.
    0:17:23 And here’s one, this is from a tech writer
    0:17:26 who decided that she would use it for a whole month
    0:17:29 to write her papers or tech tech reports.
    0:17:33 And she said that instead of just having one prompt
    0:17:36 or prompt to ask for one example,
    0:17:38 you give it a question,
    0:17:41 but you should ask for 10 different answers.
    0:17:43 And now what you can do,
    0:17:45 because otherwise you’re gonna have to iterate
    0:17:47 to get to the direction you wanna take it.
    0:17:49 But if you now have 10, you can say,
    0:17:52 ah, the third one is much better than all the others,
    0:17:54 but I want you to do the following with it.
    0:17:57 And then that will help it learn
    0:18:00 to understand what you’re looking for.
    0:18:02 But a bunch of other things that came out of it,
    0:18:06 which are quite remarkable was first she said that
    0:18:09 she had, at the end of the day, really exhausted.
    0:18:11 It was just exhausting
    0:18:12 ’cause you’re always interacting with a machine
    0:18:14 and it’s not always giving you a one.
    0:18:19 And so at the end of the day, it was a chore for her.
    0:18:20 But she said she’s gonna go on and do it.
    0:18:23 But then at one point,
    0:18:25 she realized that I don’t have this problem
    0:18:27 when I’m talking to people.
    0:18:28 (laughing)
    0:18:30 So she started being more polite.
    0:18:32 She said, oh, please give me this.
    0:18:34 Oh, that’s such a wonderful answer.
    0:18:37 I really thought that was great.
    0:18:39 And it perked up.
    0:18:40 And it actually, she said,
    0:18:42 it was just like talking to somebody.
    0:18:44 And if you’re polite, you get better answers.
    0:18:46 And at the end of the day, I wasn’t exhausted.
    0:18:49 I just felt like I just had this long discussion
    0:18:50 with my friend.
    0:18:52 (laughing)
    0:18:53 Who would have guessed that?
    0:18:53 That’s amazing.
    0:18:56 – Wait, I just wanna make this perfect clear.
    0:19:00 You’re saying if you have those kind of human interactions,
    0:19:04 human nuances, you get better answers from a machine.
    0:19:05 – Yes.
    0:19:07 Yes, that’s her discovery.
    0:19:09 And that’s my experience too.
    0:19:14 Look, it learned from the whole range of human experience
    0:19:17 and humans interact with each other, dialogues and so forth.
    0:19:20 So it understands a lot about that.
    0:19:22 And it will adapt.
    0:19:24 If you put it into that frame of mind,
    0:19:25 if I could use that term,
    0:19:29 it will continue to interact with you that way.
    0:19:31 And I think that that’s really quite remarkable.
    0:19:33 – I have often wondered,
    0:19:36 because I write a lot of prompts every day,
    0:19:40 wouldn’t it be better for the LLM if it recognized,
    0:19:44 you know, things like capitalization of proper nouns
    0:19:49 or air quotes or question marks or exclamation marks
    0:19:51 that have these really basic functions
    0:19:53 in written communication.
    0:19:55 But it seems like whether you’re asking a question
    0:19:58 or making a statement, the LLM doesn’t care.
    0:20:02 Wouldn’t it help the LLM if I’m asking a question
    0:20:04 as opposed to making a statement
    0:20:08 and Apple is the company not Apple the fruit?
    0:20:10 – Oh, no, no, it knows.
    0:20:12 If you put a question mark there, it knows it’s a question.
    0:20:12 – It does?
    0:20:15 – I can assure you, yes, absolutely.
    0:20:17 So what happens is that all of the words
    0:20:19 and punctuation marks are given tokens.
    0:20:21 In fact, some words have more than one token,
    0:20:23 like if it’s a Pertmanto word.
    0:20:26 And it treats all of those as being hints
    0:20:29 or giving you some information about the meaning
    0:20:30 of the sentence.
    0:20:32 And if it’s a question, it’s a very different meaning.
    0:20:34 So yeah, it will definitely take that into account.
    0:20:36 At one point, actually, not for me,
    0:20:40 but for someone else, it started giving emojis as output.
    0:20:45 So it must know what an emoji is.
    0:20:48 – I learn something every day.
    0:20:50 Thank you for clearing that up for me.
    0:20:55 With this, just the beauty and magic of LLMs,
    0:21:00 what does, how would you define learning going forward?
    0:21:06 Because is it scoring high on an SAT?
    0:21:08 Is it memorization of mathematical formulas?
    0:21:12 Or is it the ability to get a good answer via a prompt?
    0:21:14 What is learning anymore?
    0:21:17 – So it was taught, it was pre-trained.
    0:21:21 That’s the P in GPT.
    0:21:26 And it was trained on an enormous amount of facts
    0:21:29 and tests of various sort.
    0:21:32 And so it internalized a lot of that.
    0:21:36 It knows what kind of a question that you’re asking,
    0:21:39 ’cause it’s seen millions of questions.
    0:21:42 This is something still very mysterious.
    0:21:46 It turns out there’s something called learning in context.
    0:21:48 That is to say, if you have a long enough interview,
    0:21:51 ’cause it keeps adding word after word,
    0:21:54 it will go off in a certain direction
    0:21:56 as if it has learned from what you’ve just told it,
    0:21:59 as if that’s building on what you just told it.
    0:22:00 And that’s of course what happens with humans.
    0:22:03 You’re humans that you have a long conversation
    0:22:07 and you will take into account your previous discussion
    0:22:09 and where that went and it can do that.
    0:22:11 And that’s another thing that is very strange,
    0:22:13 is that no one expected that.
    0:22:16 The thing is that when they train these networks,
    0:22:18 they have no idea what they’re capable of.
    0:22:22 Step back a few years before chat GDP.
    0:22:24 These deep learning models,
    0:22:27 the learning took place in typically
    0:22:31 a feed forward networks and it had a data set
    0:22:33 and it was given an input
    0:22:34 and it was trained to give an output, right?
    0:22:37 And so that is supervised learning.
    0:22:39 And you can do speech recognition that way,
    0:22:41 object recognition, language translation,
    0:22:45 a lot of things, but each network is dedicated to one task.
    0:22:48 What is amazing here is you train it up on self-supervised
    0:22:49 just to predict the next word
    0:22:52 and it can do hundreds and thousands of different tasks.
    0:22:55 But you can ask it to write a poem.
    0:22:58 By the way, that’s where hallucination is very useful.
    0:23:00 (laughing)
    0:23:03 And haiku, it’s not a brilliant poet,
    0:23:05 but it does a pretty good job.
    0:23:06 And I have a couple of examples in my book,
    0:23:09 but it has a wide range of talents,
    0:23:12 that language capabilities,
    0:23:14 that again, no one programmed, no one told it,
    0:23:19 or to summarize a long document in a paragraph.
    0:23:24 It does a really good job of that, it’s just not a show.
    0:23:26 – But I mean, if you think about it, do you have children?
    0:23:27 – I don’t.
    0:23:29 – Okay, well, I have four children.
    0:23:32 And many times they come up with stuff
    0:23:36 that I have no idea how they came up with that.
    0:23:40 So in a sense, you think exactly what your child is learning
    0:23:43 and you think you’re controlling all the data
    0:23:44 going into your child,
    0:23:47 so you can predict what they’re gonna come up with.
    0:23:51 And they absolutely like just knock you off your feet
    0:23:51 with something that,
    0:23:54 how the hell did you come up with that idea?
    0:23:58 What’s the difference between not knowing
    0:24:00 how your child works
    0:24:03 with not knowing how an LLM works, same thing, right?
    0:24:07 – Very, that’s actually a very deep insight
    0:24:10 because human beings are picking up things
    0:24:13 in a very similar way in terms of the way
    0:24:15 that we take experience in
    0:24:18 and then we codify it somehow in our cortex
    0:24:20 in such a way that we can use it
    0:24:23 in a variety of other ways later on.
    0:24:26 And they could have picked up things they heard,
    0:24:28 for example, that you and your wife talking about
    0:24:32 or they could have been playing with kids outside.
    0:24:34 I mean, and the same thing with Chatchity to be,
    0:24:37 who knows where it’s getting all of that ability.
    0:24:39 – Okay.
    0:24:42 I’m gonna read you, and this isn’t a question.
    0:24:44 This is just a statement here.
    0:24:47 I have two absolute favorite quotes from your book.
    0:24:50 This is one of them, quote,
    0:24:54 “Usefulness does not depend on academic discussions
    0:24:55 of intelligence.”
    0:25:00 Oh my God, that’s like, I use LLMs every day.
    0:25:02 And they’re so useful for me.
    0:25:03 I don’t give a shit.
    0:25:06 What do you say about the academic learning model?
    0:25:09 What do I care? It’s helping me, right?
    0:25:12 – It’s a tool, and it’s a very valuable tool.
    0:25:16 And all of these academic discussions are really beyond,
    0:25:20 it is really a reflection of the fact
    0:25:23 that we don’t really understand if experts argue
    0:25:26 about whether are they intelligent or they understand.
    0:25:28 It means that we really don’t know the meaning
    0:25:29 of those words.
    0:25:33 We just don’t understand at any real level of scientific.
    0:25:37 – Okay, let me ask you something, writer to writer.
    0:25:42 So if you provided the PDF of your book
    0:25:47 and you gave it to OpenAI and they put it into ChatGPT,
    0:25:52 would you consider that ripping off your IP
    0:25:56 or would you want it inside ChatGPT?
    0:25:57 – I would be honored.
    0:25:59 – Me too.
    0:26:01 – I would brag about it.
    0:26:02 – Me too.
    0:26:04 (laughs)
    0:26:09 – No, I think that there is some concern about the data.
    0:26:13 Where are these companies getting the data from?
    0:26:15 Is there proprietary information that they used?
    0:26:16 And so forth.
    0:26:18 That’s all gonna get sorted out.
    0:26:23 But my favorite example is artists.
    0:26:26 They say, oh, you’ve used my paintings to train up
    0:26:30 the Dolly or your diffusion model.
    0:26:32 And I deserve something for that.
    0:26:33 Then my question is,
    0:26:37 when you were learning to be an artist, what did you do?
    0:26:38 – You copied other artists.
    0:26:40 – You looked at a lot of other artists
    0:26:45 and your brain took that in and it didn’t memorize it,
    0:26:49 but it formed features that then later,
    0:26:51 you’re depending on all that experience you’ve had
    0:26:53 to create something new.
    0:26:55 But this is the same thing.
    0:26:57 It’s creating something new from everything that it’s seen.
    0:27:01 So it’s gonna have to be settled in court.
    0:27:03 I don’t know what the right answer is.
    0:27:05 There’s something interesting that’s happened recently.
    0:27:07 And by the way, I have a sub-stack
    0:27:09 because the book went to the printer in the summer.
    0:27:11 So there’s all kinds of new things that are happening.
    0:27:14 So in the sub-stack, what I do is I fill in the new stuff
    0:27:18 that’s happened and put it in the context of the book.
    0:27:20 It’s brains and AI.
    0:27:22 What’s happened is that,
    0:27:25 Mistral and several other companies have discovered
    0:27:28 that if you use quality data, in other words,
    0:27:32 that’s been curated or comes from a very good source,
    0:27:34 and you may have to pay for it.
    0:27:37 And math data, for example, Wolfram Research,
    0:27:40 Steve Wolfram, who founded Mathematica,
    0:27:44 has actually sold a lot of the math that they have.
    0:27:46 But with the quality data, it turns out
    0:27:48 that you get a much better language model,
    0:27:52 much better in terms of being able to train
    0:27:55 with fewer words and a smaller network
    0:27:58 having performance that’s equal or better.
    0:28:00 So that’s the same thing true as a humans, right?
    0:28:02 I think what’s going to happen is that the models
    0:28:04 will get smaller and they’ll get better.
    0:28:06 – Another author-to-author question.
    0:28:08 I’ll give you a negative example.
    0:28:10 So I believe back in the ’70s,
    0:28:12 Kodak defined themselves as a chemical company
    0:28:16 and we put chemicals on paper, chemicals on film.
    0:28:19 The irony is that engineer inside Kodak
    0:28:21 invented digital photography.
    0:28:24 But Kodak kept thinking we’re a chemical company,
    0:28:26 we’re not a preservation of memories company.
    0:28:29 If they had repositioned their brains,
    0:28:31 they would have figured out we preserve memories,
    0:28:35 it’s better to do it digitally than chemically.
    0:28:38 So now, as an author, and you’re also an author,
    0:28:40 I think what is my business?
    0:28:41 Is it chemicals?
    0:28:43 Is it writing books?
    0:28:46 Or is it the dissemination of information?
    0:28:49 And if I zoom out, then I say it’s dissemination
    0:28:51 of information.
    0:28:52 Why am I writing books?
    0:28:57 Why don’t I train an LLM to distribute my knowledge
    0:29:01 instead of forcing people to read a book?
    0:29:04 So do you think they’re gonna be authors in the long run
    0:29:07 because a book is not that efficient
    0:29:09 a way to pass information?
    0:29:13 – Interesting, and this is already beginning to happen.
    0:29:16 So you know that you could train up an LLM
    0:29:19 to mimic the speech of people
    0:29:23 if you have enough data from them, movie stars.
    0:29:28 And also it turns out that you can not only mimic the voice,
    0:29:32 but someone fed in a lot of Jane Austen novels.
    0:29:36 I gave a little excerpt in the book.
    0:29:40 You can ask it for advice and it will start talking
    0:29:43 as if you’re talking to Jane Austen from that era.
    0:29:46 And there’s actually interesting,
    0:29:51 potentially important way, if you have enough data
    0:29:56 about an individual, a videos, writing and so forth,
    0:29:58 if that could all be downloaded,
    0:30:00 you’re right into a large language model.
    0:30:04 It would, in some ways, it would be you, right?
    0:30:08 If it has captured all of the external things
    0:30:10 that you’ve said and done.
    0:30:12 So it might, who knows.
    0:30:14 – Terry, I have a company for you.
    0:30:17 There’s a company called Delphi.ai.
    0:30:22 And Delphi.ai, you can control what goes into the LLM.
    0:30:27 So KawasakiGPT.com is Delphi.ai.
    0:30:31 And I put in all my books, all my blog posts,
    0:30:34 all my substacks, all my interviews,
    0:30:38 including this interview will go in shortly, right?
    0:30:42 So you can go to KawasakiGPT and you can ask me
    0:30:46 and 250 guests a question.
    0:30:51 And I promise you that my LLM answers better than I do.
    0:30:55 And in fact, since you talked about substack,
    0:30:59 every week Madison and I put out a substack newsletter.
    0:31:02 And the procedure is we go to KawasakiGPT
    0:31:04 and we ask it a question like,
    0:31:07 what are the key elements of a great pitch
    0:31:09 for venture capital?
    0:31:12 And five seconds later, we have a draft.
    0:31:13 And we start with that draft.
    0:31:15 And I don’t know how we would do that
    0:31:17 without KawasakiGPT.
    0:31:22 So that ability to create an LLM for Terry is already here.
    0:31:25 And Delphi.ai has this great feature
    0:31:28 that you can set the parameter.
    0:31:31 So you can say very strict.
    0:31:35 And very strict means it only uses the data you put in
    0:31:37 or can be creative and it can go out
    0:31:39 and get any kind of information.
    0:31:44 So if somebody came to TerryGPT and asked,
    0:31:46 how do I do wing suiting?
    0:31:47 If you had it set to strict,
    0:31:49 assuming you don’t know anything about wing suiting,
    0:31:52 it would say, this is not an area
    0:31:55 but my expertise you’re gonna have to look someplace else.
    0:31:58 Which is, that’s like better than hallucination, right?
    0:31:59 You gotta try that.
    0:32:02 – I will, I will, I had no idea.
    0:32:04 And is this open to the public?
    0:32:08 – Yes, and I pay $99 a month for this.
    0:32:12 And you can set it so it subscribes to your sub-stacks,
    0:32:15 subscribes to your podcasts,
    0:32:17 you can make a Google Drive folder
    0:32:20 and whenever you write something, you drop it in the drive
    0:32:22 and then it keeps checking the drive every week
    0:32:24 and just keeps inputting.
    0:32:26 And I feel like I’m immortal, Terry.
    0:32:27 What can I say?
    0:32:32 – Yes, it really has a transformative potential
    0:32:34 for who would have guessed
    0:32:36 that this could even be possible a couple of years ago.
    0:32:39 – No one, I think it’s really a transition.
    0:32:43 – But you know, just before you get too excited by this,
    0:32:48 I don’t think that there is a market for people’s clones
    0:32:50 because I’m pretty visible
    0:32:54 and I only get five to 10 questions a day.
    0:32:55 It’s a nice parlor trick.
    0:32:59 Oh, we can ask Guy what he thinks about everything.
    0:33:02 But after the first hour, six months later,
    0:33:05 are you gonna remember there’s Kawasaki GPT?
    0:33:06 – I doubt it.
    0:33:11 So what you would probably go to is chat GPT and say,
    0:33:13 what would Guy Kawasaki say
    0:33:16 are the key elements of a pitch for venture capital?
    0:33:18 And chat GPT will give you an answer
    0:33:21 almost as good as Kawasaki GPT
    0:33:25 and you’ll never go back to my personal clone again.
    0:33:27 – Yeah, I think your children might, somebody.
    0:33:31 – Well, why would that be true?
    0:33:33 They don’t ask me anything now.
    0:33:37 – Oh, that’s interesting.
    0:33:39 A lot of times when someone dies,
    0:33:42 they’re offspring and close friends say,
    0:33:45 oh, I wish I had asked them that question.
    0:33:48 I really wish, it’s too late, it’s too late.
    0:33:52 No, if they have something, you’re there to ask the question.
    0:33:55 – Okay, I did it for my kids then.
    0:33:56 – Yeah.
    0:33:59 – Up next on Remarkable People.
    0:34:00 – You can push it around.
    0:34:00 It can do either.
    0:34:03 It has the world’s literature that on both sides
    0:34:05 and this is exactly the problem,
    0:34:07 is that it is reflecting you.
    0:34:08 It’s a mirror hypothesis,
    0:34:13 reflecting your kind of stance that you’re taking.
    0:34:16 And it’s very, in some ways,
    0:34:19 it has the ability like a chameleon, right?
    0:34:21 It will change its color depending on
    0:34:22 how you’re pushing it.
    0:34:32 – Thank you to all our regular podcast listeners.
    0:34:35 It’s our pleasure and honor to make the show for you.
    0:34:37 If you find our show valuable,
    0:34:39 please do us a favor and subscribe,
    0:34:41 rate and review it.
    0:34:44 Even better, forward it to a friend,
    0:34:46 a big mahalo to you for doing this.
    0:34:51 – Welcome back to Remarkable People with Guy Kawasaki.
    0:34:55 – I’m gonna get a little bit political on you right now.
    0:34:58 It seems to me that people can try this
    0:35:01 or listening, go to chat, J.B.T., and ask,
    0:35:03 should we teach the history of slavery?
    0:35:04 Ask questions about,
    0:35:07 should we have a biblically based curriculum
    0:35:08 in public schools?
    0:35:09 Go ask all those kind of questions.
    0:35:11 You’re gonna be amazed at the answer.
    0:35:14 So my question for you is,
    0:35:17 don’t you think that in the very near future,
    0:35:22 red states or let’s say a certain political party,
    0:35:25 they’re gonna block access to LLMs?
    0:35:26 Because if LLMs are telling you,
    0:35:29 “Yes, we should teach the history of slavery,”
    0:35:32 I can’t imagine Ron DeSantis is wanting people
    0:35:35 to ask chat, J.B.T., that question.
    0:35:38 – So now we’re getting into hot water here.
    0:35:39 (laughing)
    0:35:40 – You’re tenured, right?
    0:35:42 – And it’s not just chat, J.B.T.,
    0:35:45 we’re talking about all of these high-tech websites
    0:35:48 that repository of knowledge and information
    0:35:50 that you can search.
    0:35:52 They have a double of a time trying to figure out
    0:35:55 should they have thousands of people actually doing this?
    0:35:58 They’re constantly looking at the hate things
    0:36:01 that are said on Twitter or whatever.
    0:36:04 That has to be scrubbed.
    0:36:06 Now, the problem is who’s scrubbing it?
    0:36:09 And what do they consider bad?
    0:36:13 And if humans can’t agree,
    0:36:17 how can you possibly have a rule
    0:36:20 that is gonna be good for everybody if there isn’t any?
    0:36:21 I think it’s an unsolved problem
    0:36:24 and I think it’s reflecting more the disagreements
    0:36:26 that humans have than the fact that chat,
    0:36:29 J.B.T. can’t decide what to say.
    0:36:30 – But it’s interesting,
    0:36:32 you can probably push it in certain directions, right?
    0:36:34 I think that people have tried that.
    0:36:38 They’ve tried to break it one way or another.
    0:36:43 – It may be that many Republicans have never tried LLM,
    0:36:45 but I’m telling you, if they tried it,
    0:36:47 they would say LLMs are woke
    0:36:50 and we gotta get all this woke stuff out of the system.
    0:36:52 I can’t imagine.
    0:36:56 – Okay, my guess is that you’ll get a woke person
    0:36:58 talking at coming to the conclusion
    0:37:02 that this is flaming a conservative here.
    0:37:04 In other words, you can push it around.
    0:37:05 It can do either.
    0:37:08 It has the world’s literature that on both sides
    0:37:09 and this is exactly the problem,
    0:37:11 is that it is reflecting you.
    0:37:12 It’s a mirror hypothesis,
    0:37:17 reflecting your kind of stance that you’re taking.
    0:37:20 And it’s very, in some ways,
    0:37:23 it has the ability, like a chameleon, right?
    0:37:24 It’ll change its color,
    0:37:27 depending on how you’re pushing it.
    0:37:28 – That’s no different
    0:37:31 than what people do in a conversation.
    0:37:32 – That’s right.
    0:37:34 And also people are polite.
    0:37:36 They generally stay away from things
    0:37:38 that are controversial and yeah,
    0:37:40 we need that in order to be able to get along
    0:37:41 with each other, right?
    0:37:42 It would be terrible if all we did
    0:37:44 was argue with each other.
    0:37:46 – About a year or two ago,
    0:37:50 there was this, I won’t prejudice your answer.
    0:37:54 There was this idea that we would have a six-month
    0:37:59 kind of timeout while we figure out the implications of AI.
    0:38:01 Is that the stupidest thing you ever heard?
    0:38:03 How do you take a timeout from AI?
    0:38:06 Let’s just like timeout and figure out what we’re gonna do.
    0:38:11 – That was done by, I think, 500 machine learning
    0:38:15 and AI people that decided that in their wisdom
    0:38:18 that we have to, you’re right, it was a moratorium.
    0:38:23 And I think it was specifically on these very large GPT models
    0:38:26 that we shouldn’t try to train them beyond where they are
    0:38:29 because there might be super intelligent
    0:38:31 and they may have to actually take over the world
    0:38:32 and wipe out humans.
    0:38:34 This is all science fiction, right?
    0:38:36 That we’re talking about.
    0:38:38 And in the book, I came across an article
    0:38:41 on the economists where they had super forecasters
    0:38:44 who had a track record of being able to make predictions
    0:38:49 about catastrophic events, wars, and technologies,
    0:38:55 nuclear technology, better than the average person.
    0:38:58 And then they also compared the predictions with experts.
    0:39:02 And it turns out that experts are a factor
    0:39:04 of 10 times more pessimistic in terms of
    0:39:05 whether something’s going to happen
    0:39:08 or when it’s going to happen than the super forecasters.
    0:39:09 And I think that’s what’s happening,
    0:39:13 is that they think that their technology is so dangerous
    0:39:16 that it needs to be stopped.
    0:39:18 – When I read that section of your book,
    0:39:20 I had to read it about two or three times
    0:39:24 because it’s exactly opposite of what I thought
    0:39:28 it would be that super forecasters would be Armageddon
    0:39:31 and the technical people would say, no, it’s okay.
    0:39:33 Like how do you explain that?
    0:39:34 – There’s a simple explanation.
    0:39:37 I think though that everybody thinks
    0:39:42 that what they are doing is more important than it might be.
    0:39:44 – In terms of its impact.
    0:39:46 (laughing)
    0:39:49 Actually, this is funny.
    0:39:51 When Obama was elected president,
    0:39:55 the local newspaper interviewed a lot of academics
    0:39:57 about, you know, he said that he was going to support science
    0:39:58 and that was wonderful.
    0:40:01 And so the newspaper asked, what areas of science
    0:40:03 do you think the government should support?
    0:40:07 And almost every person said, what I’m doing.
    0:40:07 (laughing)
    0:40:12 – It’s the most important area to fund, you know?
    0:40:14 Because they’re the closest to it.
    0:40:16 And of course, they’ve committed their life to it.
    0:40:18 So it must be the most important.
    0:40:22 – I mentioned that I had two absolute gems
    0:40:25 that I love those quotes in your book.
    0:40:27 And I’m coming to the second one.
    0:40:29 And the second one is not necessarily a quote,
    0:40:34 but I want you to explain the situation when you say
    0:40:39 that Sam Altman had, shall I say symptoms of toxoplasma
    0:40:46 gondi, that the brain parasite that makes rodents
    0:40:49 unafraid of cats and more likely to be eaten.
    0:40:53 So why did you say that about Sam Altman?
    0:40:56 – Okay, so first of all, this is a biological thing
    0:41:01 that happens in the brain of the poor mouse or rat.
    0:41:04 So there was a time when he would go to Washington
    0:41:06 and not just testify before Congress,
    0:41:09 but he would actually go and have dinners
    0:41:12 with Congress people and talk to them.
    0:41:15 And the history is that Bill Gates gets pulled in
    0:41:19 and he gets grilled in a congressional testimony
    0:41:20 and they gave a diversion.
    0:41:24 So here’s the skies going in and not just going for testimony
    0:41:28 but actually going and trying to be a part
    0:41:30 of their social life.
    0:41:35 So it just seemed that he was being contrary
    0:41:39 to the traditional way that most humans would deal
    0:41:42 with people who are out to regulate you.
    0:41:45 But actually somewhere later in the book,
    0:41:48 I think identified another explanation,
    0:41:52 which is that the regulation is an interesting thing
    0:41:55 because it basically puts up barriers, right?
    0:41:58 It turns out if you have lots of lawyers,
    0:42:02 you can find loopholes, it’s always a loophole, right?
    0:42:04 And if you’re rich, you can afford lawyers
    0:42:05 to find the loopholes for you.
    0:42:08 And of course, the big corporations,
    0:42:11 high tech, Google and OpenAI, they have the best lawyers.
    0:42:15 They can hire the best lawyers to get around any regulation,
    0:42:18 whereas some poor startup, they can’t do that.
    0:42:21 So it’ll give the big companies an advantage
    0:42:23 to have regulations out there.
    0:42:28 Couldn’t a scrappy, small undercapitalized startup
    0:42:34 ask an LLM what are the loopholes in this regulation?
    0:42:35 It would find them.
    0:42:36 – Ah, okay.
    0:42:40 Well, so now you’re saying that in fact,
    0:42:41 they could use their own,
    0:42:44 because they’re not gonna be able to make their own LLM,
    0:42:45 they’re gonna have to use the other,
    0:42:48 the big ones that are already out there.
    0:42:50 And it could be that these companies
    0:42:54 are actually democratizing lawyers.
    0:42:56 (laughing)
    0:42:59 By the way, it’s not just lawyers and laws,
    0:43:01 it’s also reporting.
    0:43:03 In other words, there’s a tremendous amount
    0:43:05 of what they wanna do is somehow,
    0:43:10 if the companies have to have tests and lots of examples,
    0:43:14 they’re gonna require a lot of FAA before you,
    0:43:18 airplane is allowed to carry passengers,
    0:43:21 it’s gotta go through a whole series of tests
    0:43:25 and very stringent,
    0:43:28 you have to be put into the worst weather conditions
    0:43:31 to make sure it’s stressed, a stress test.
    0:43:34 And again, all of that testing is basically
    0:43:37 for a large company, they have lots of resources to do that.
    0:43:40 And it may not be easy for a small company,
    0:43:42 so it’s complicated.
    0:43:46 But in any case, I think that what’s happening right now
    0:43:49 is that the Europeans have this AI law
    0:43:53 that is 100 pages with very strict rules
    0:43:55 about what you can and cannot do,
    0:44:00 like you can’t use it for interviewing future employees
    0:44:01 for companies.
    0:44:03 – We just advocated for that.
    0:44:07 – Yeah, we’ll see what happens in the US,
    0:44:08 ’cause right now it’s not prescriptive,
    0:44:12 it’s suggestive that we follow these rules.
    0:44:15 – And what would be the thinking that you can’t use it
    0:44:17 to interview employees in Europe?
    0:44:19 What are they worried about?
    0:44:21 – Oh, bias, bias.
    0:44:23 – Bias, as opposed to human bias,
    0:44:27 like a male recruiter falls for an attractive female candidate.
    0:44:30 – Okay, that’s also a bias, I guess.
    0:44:32 (laughing)
    0:44:36 There probably is some law there, I don’t know.
    0:44:41 Not only are we biased, but we’re biased in our biases.
    0:44:43 (laughing)
    0:44:46 Who we talk to, things like that.
    0:44:48 – All right, I gotta tell you one more part
    0:44:51 I really loved about your book is when you had
    0:44:54 the long description of legalese,
    0:44:58 and then you had the LLM Simplify a contract,
    0:45:00 and that was just beautiful.
    0:45:03 Like why do terms of service have to be so
    0:45:05 absolutely impenetrable?
    0:45:08 And you showed an example of how it could be
    0:45:10 done so much better.
    0:45:12 – That is happening right now,
    0:45:15 I think in a lot of places that is,
    0:45:18 and this is a big transformation that’s occurring
    0:45:20 within companies now.
    0:45:22 They are, the employees are using these tools
    0:45:25 in order to be able to help.
    0:45:27 First of all, keep track of meetings.
    0:45:28 You don’t have to have someone there taking notes
    0:45:30 because the whole thing gets summarized
    0:45:32 at the end of the meeting.
    0:45:34 It’s really good at that, and speech recognition.
    0:45:36 – Well, you also mentioned that when doctors
    0:45:38 are interviewing patients that instead of looking
    0:45:40 at the keyboard and the monitor,
    0:45:43 they should be just listening and let the recording
    0:45:44 take care of all that, right?
    0:45:48 – Yes, that’s a huge benefit because looking
    0:45:51 at the patient carries a lot of information.
    0:45:54 There are expressions, the color of their skin,
    0:45:57 all of that is part of being a doctor,
    0:45:58 and if you’re not looking at them,
    0:46:02 you’re not really being a good doctor.
    0:46:06 – Okay, this is seriously my last question.
    0:46:09 I love the fact that the first few chapters at the end,
    0:46:13 they had these questions that probably ChatGPT generated.
    0:46:16 Why didn’t you continue that through the whole book
    0:46:19 so every chapter ends with questions?
    0:46:22 – I don’t know, I hadn’t talked about it.
    0:46:25 I’ll tell you, I wrote the book over a course of a year,
    0:46:27 and I think that it must have been the case
    0:46:30 that by the time, I do use it throughout the book.
    0:46:32 I have sections, and I actually set them apart
    0:46:36 and say this is ChatGP, at the end there’s this little sign
    0:46:40 opening the eye sign, and I ask it to summarize parts.
    0:46:42 And at the beginning, I actually ask it to,
    0:46:47 sometimes I ask it to come up with say five questions
    0:46:49 from this chapter, and that’s where Alex the parrot
    0:46:50 popped out.
    0:46:53 (laughing)
    0:46:56 – Am I the first person to catch the fact
    0:46:59 that Alex the parrot was not mentioned in the text
    0:47:00 except for the footnote?
    0:47:03 – You are the first person, and I suspect there are others
    0:47:05 that notice that.
    0:47:08 But actually it’s good to have a few little parcels
    0:47:12 in there that you have a little detective story
    0:47:13 for who is Alex the parrot.
    0:47:17 – All right, how about I give you like,
    0:47:19 I really want you to sell a lot of copies of this book.
    0:47:22 So how about I give you like, just unfettered,
    0:47:26 give us your best shot promo for your book.
    0:47:29 – Everything you’ve always wanted to know
    0:47:32 about large language models and ChatGPT,
    0:47:34 and we’re not afraid to ask.
    0:47:36 – That’s a good positioning.
    0:47:38 I like that.
    0:47:43 It’s like that book way in my past.
    0:47:45 It was a book called everything you wanted to know
    0:47:48 about sex, but was afraid to ask, right?
    0:47:52 – Yeah, it was a take off, a ball rip off.
    0:47:54 – As I learned from Steve Jobs,
    0:47:55 you gotta learn what to steal.
    0:47:58 That’s a talent in and of itself.
    0:48:00 – You’re paying homage to the past,
    0:48:02 but I wrote this for the public.
    0:48:05 I thought that the news articles were misleading
    0:48:08 and all this talk about super intelligence was,
    0:48:11 although it’s a concern, it’s not an immediate concern,
    0:48:14 but we have to be careful, that’s for sure.
    0:48:17 And it helps, I’m trying to help people.
    0:48:19 When I give talks, they ask, well, I lose my job.
    0:48:23 And I say, you may not lose your job, but it’s gonna change.
    0:48:24 And you have to have new skills
    0:48:27 and maybe that’s gonna be part of your new job
    0:48:29 is to use these AI tools.
    0:48:31 – Well, as you mentioned in your book,
    0:48:34 when we started getting farm equipment,
    0:48:36 there are a lot less farmers.
    0:48:41 You could manage thousands of acres at one person, right?
    0:48:42 – Yes, that’s true.
    0:48:45 That’s true, but the children went to the cities
    0:48:46 and they worked in factories.
    0:48:47 And so they had a different job,
    0:48:50 but it wasn’t working to get food.
    0:48:54 It’s working to make cloth and automobiles and things.
    0:48:56 – And LLMs eventually.
    0:48:58 (laughs)
    0:49:00 Yes, eventually, for some of us.
    0:49:02 – I just wanna thank you, Terry, very much.
    0:49:04 I found your book very, very,
    0:49:08 not only interesting and informative.
    0:49:13 There were places where I was just busting out laughing
    0:49:15 and I’m not sure that was your intention,
    0:49:18 but when I read that thing about Sam Altman’s brain,
    0:49:21 has that thing that make rodents less afraid of cats.
    0:49:24 I’m like, oh my God, this guy is a funny guy.
    0:49:27 – So I thought I’d make it entertaining
    0:49:30 so that people can appreciate.
    0:49:33 In some way, we’re two purchase people,
    0:49:34 I’m serious about that.
    0:49:35 Let’s have some fun.
    0:49:37 – One of my theories in life is that
    0:49:40 a sense of humor is a sign of intelligence.
    0:49:41 (laughs)
    0:49:41 – Oh, good.
    0:49:44 Actually, I’ll tell you, if this is interesting,
    0:49:46 who gets the Academy Awards?
    0:49:49 It’s the actor who’s in some terrible drama
    0:49:51 where something bad happens and so forth.
    0:49:55 And then they overlook all the fantastic comedians.
    0:49:57 It turns out it’s much more difficult
    0:50:00 to be a comedian and be somebody who has angst.
    0:50:04 And they’re not giving the same respect.
    0:50:07 I had no idea that you’ve read the whole book
    0:50:09 ’cause most of the people who interviewed me,
    0:50:11 they’ve read some parts,
    0:50:13 but it sounds like you know the whole book.
    0:50:17 – I could, do you know the story
    0:50:20 of the chauffeur and the physicist?
    0:50:22 Okay, this is along the lines
    0:50:24 of what you just said that I read the whole book.
    0:50:27 So this physicist is on a book tour.
    0:50:29 Let’s say it’s Stephen Wolfram or Neil deGrasse Tyson.
    0:50:32 So anyway, they’re on this book tour
    0:50:34 and they’re gonna make four stops in the cities
    0:50:38 and the chauffeur takes them from stop to stop.
    0:50:40 So the chauffeur sits in the back
    0:50:42 and listens to the first three times
    0:50:44 the physicist gives the talk.
    0:50:46 At the fourth time, the physicist says,
    0:50:48 “I am exhausted.
    0:50:50 “You heard me give this talk three times.
    0:50:52 “You go give the talk.”
    0:50:54 And the chauffeur says, “Yeah, I can do it.
    0:50:56 “I heard you three times.”
    0:50:58 The chauffeur goes up, gives the talk,
    0:51:00 but he ends early.
    0:51:04 And so the MC, the host of the event, says to the chauffeur,
    0:51:06 “Oh, we’re lucky we ended early.
    0:51:10 “We’re gonna take some Q&A from the audience.”
    0:51:12 So the first question comes up and it’s about physics
    0:51:14 and the chauffeur has no idea.
    0:51:17 And he says, “This question is so simplistic.
    0:51:20 “I’m gonna let my chauffeur sitting in the back answer.
    0:51:21 (laughing)
    0:51:22 “So I’m your chauffeur.”
    0:51:26 (laughing)
    0:51:27 Oh, that’s wonderful.
    0:51:28 All right, Terry, thank you.
    0:51:29 Well, thank you.
    0:51:31 I truly enjoy this.
    0:51:32 I did too.
    0:51:33 All right, all the best to you.
    0:51:36 (jazz music)
    0:51:38 This is Remarkable People.

    In this episode of Remarkable People, Guy Kawasaki engages in a fascinating dialogue with Terry Sejnowski, the Francis Crick Chair at the Salk Institute and Distinguished Professor at UC San Diego. Together, they unpack the mysteries of artificial intelligence, exploring how AI mirrors human learning in unexpected ways. Sejnowski shatters common misconceptions about large language models while sharing compelling insights about their potential to augment human capabilities. Discover why being polite to AI might yield better results and why the future of AI is less about academic debates and more about practical applications that can transform our world.

    Guy Kawasaki is on a mission to make you remarkable. His Remarkable People podcast features interviews with remarkable people such as Jane Goodall, Marc Benioff, Woz, Kristi Yamaguchi, and Bob Cialdini. Every episode will make you more remarkable.

    With his decades of experience in Silicon Valley as a Venture Capitalist and advisor to the top entrepreneurs in the world, Guy’s questions come from a place of curiosity and passion for technology, start-ups, entrepreneurship, and marketing. If you love society and culture, documentaries, and business podcasts, take a second to follow Remarkable People.

    Listeners of the Remarkable People podcast will learn from some of the most successful people in the world with practical tips and inspiring stories that will help you be more remarkable.

    Episodes of Remarkable People organized by topic: https://bit.ly/rptopology

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