AI transcript
0:00:05 Hey there, it’s Stephen Dubner.
0:00:10 Every once in a while, we get out of our recording studio and take Freakonomics Radio on the
0:00:11 road.
0:00:16 We recently put on a live show in San Francisco at the historic Sidney Goldstein Theater.
0:00:19 If you were in the audience that night, thank you.
0:00:20 We had a blast.
0:00:21 Hope you did too.
0:00:25 If you were not there, this bonus episode is for you.
0:00:29 It is a recording of that show edited down to podcast length.
0:00:34 We have got another live show coming up in Los Angeles on February 13.
0:00:40 LA has been through so much with the wildfires, so much destruction and death and fear.
0:00:44 All of us who love that place are eager for its recovery.
0:00:48 And we are hoping to do our tiny part just by showing up.
0:00:51 A portion of our ticket sales will go to Relief Efforts.
0:00:53 I hope you’ll join us if you can.
0:00:58 You can get tickets at freakonomics.com/liveshows, one word.
0:01:01 It’s Thursday, February 13th, in Los Angeles.
0:01:05 One of our guests will be the inimitable Ari Emanuel.
0:01:10 Okay, here now is what happened in San Francisco.
0:01:12 As always, thanks for listening.
0:01:38 .
0:01:43 There are so many of you.
0:01:44 This does not seem like a fair fight.
0:01:47 There’s one of me and all of you.
0:01:55 I’m sure it’ll work out okay, but the hecklers begin.
0:01:59 So in case it’s not clear, this is not what we typically do.
0:02:01 I assume most of you know Freakonomics Radio.
0:02:07 You wouldn’t be here otherwise.
0:02:10 The show that we make is the opposite of a live show.
0:02:14 The show we make is really I’m a writer and it’s a writer’s show.
0:02:20 We come up with an idea, we do a bunch of research, we figure out what kind of people
0:02:25 to interview, then we prepare for the interviews, we do a lot of interviews.
0:02:30 We start to put together a script, a draft script, we rewrite it, we start to mix the
0:02:31 tape.
0:02:35 It takes many, many, many, many hours to make one episode and you know that’s the way we
0:02:36 like it.
0:02:39 At night, we’ve got like an hour and a half or two hours.
0:02:40 That’s it.
0:02:43 We have no pause button, we have no reconsideration.
0:02:46 It’s just us here together.
0:02:49 So if you’re up for that, I think we’re going to have a very good time together.
0:02:57 That’s the intention at least.
0:02:59 When I was a kid, I was very shy.
0:03:01 I still am, truthfully.
0:03:05 I had another problem in addition to shyness, which was that I really was curious.
0:03:07 I wanted to find out stuff.
0:03:11 In the old days, it took a lot of effort to find out stuff.
0:03:18 You’d have to go to the library or you would have to ask an adult and when you’re shy,
0:03:21 asking a stranger questions was not so easy.
0:03:27 My solution to all of that was to become a journalist, where you’re, okay, I’ve never
0:03:34 heard journalism applauded before, so thank you.
0:03:39 So becoming a writer, becoming a journalist, really solved both problems because all of
0:03:44 a sudden you have permission to ask anybody any question and you’re getting to find out
0:03:45 stuff all the time.
0:03:50 Now, in the old days, writing for newspapers and magazines and I wrote books for a while,
0:03:53 it was old fashioned fun, physical, analog labor.
0:03:59 You’d go out with people, might be writing a piece about one person over many weeks or
0:04:03 months, you’d follow them around, might be a whole scene and you’d come back after those
0:04:08 weeks or months with a whole bunch of cassette tapes that you would then transcribe yourself
0:04:09 as a writer.
0:04:10 That’s how you got to really know the material.
0:04:15 You’d come back with all these notebooks full of stuff and then you would sit down to sift
0:04:18 it and sort and write and I loved that.
0:04:20 I loved every single piece of it.
0:04:22 I still have all my notebooks.
0:04:24 I still have all those cassette tapes.
0:04:29 It was very, very labor intensive, but it was wonderful labor and my favorite part of
0:04:32 it was always just hanging out with the people.
0:04:37 A lot of it honestly was really boring, but the parts that were exciting were so exciting
0:04:38 when you really learned something.
0:04:43 It makes me think of what the physicist Richard Feynman, who’s been a hero of mine for a long
0:04:47 time, what Feynman called the pleasure of finding things out.
0:04:50 It was just so pleasurable that I never stopped.
0:04:56 What we do now with the radio show may seem different because it’s audio and yada yada,
0:04:58 but it’s really the same thing.
0:05:04 Coming up with ideas, putting yourself in position to have interesting conversations with people
0:05:10 who are smart or weird or maybe all of the above.
0:05:16 I think if we were to go back 20 or 30 years to when digital everything was really starting
0:05:23 to explode, I don’t know if any of us would have thought that we’d have so much communication
0:05:27 as we do and so little conversation.
0:05:34 I feel like because everyone is able to publish and be their own bullhorn, that in a way we’ve
0:05:38 sort of forgotten how to talk to each other.
0:05:45 By now I’ve probably interviewed, I don’t know, 5,000, 10,000 people in my life and
0:05:52 I can’t think of a single one where afterward I didn’t feel like my brain grew a little
0:05:55 bit or my heart grew a little bit.
0:05:59 It’s an unbelievably valuable human trait that we overlook, this ability of ours to
0:06:04 have language and have a conversation where we can learn about each other, move each other
0:06:05 and so on.
0:06:07 Really tonight, that’s what I want to do.
0:06:09 I just want to have some good conversations.
0:06:15 We’ve lined up some people I think are going to be excellent for you and me to hear about.
0:06:16 We’ll get started.
0:06:21 Does anyone have any complaints before we begin?
0:06:27 I get your emails, I know who you are.
0:06:29 We’re going to have some good conversations.
0:06:33 Our first one, I think you will enjoy quite a bit.
0:06:34 Would you please welcome our first guest?
0:06:41 She is the mayor of San Francisco, London Breed.
0:06:49 How’s things?
0:06:57 Well, freedom is fast approaching right now, so it’s almost like I dropped thousands of
0:06:59 pounds.
0:07:00 So you call it freedom.
0:07:04 For those who don’t know, you’ve got just a few days left.
0:07:06 You must have some wild s*** planned.
0:07:13 Oh, yes, pull out those phones because you guys are going to see a different mayor breed.
0:07:17 Let me start with, I hate to say it, a lot of people think of San Francisco as kind of
0:07:18 a failed state.
0:07:24 Not quite Haiti or Libya, but the stuff they see, they see the worst of the word.
0:07:25 That’s what the media does.
0:07:27 The media is really good at that.
0:07:30 And then it becomes a political weapon as well.
0:07:32 I mean, COVID was really hard.
0:07:38 You personally seem to have done the shutdown, handled that really well, aggressively, early
0:07:39 and so on.
0:07:41 But tell me how the city is recovering.
0:07:47 Well, it has been a rough ride, but I’m really excited about where we are now as a city.
0:07:52 The city has been more fun than it has been in a long time because you said more fun.
0:07:57 We have closed down streets to have night markets, first Thursdays, events, entertainment
0:08:01 zones, because we need some joy.
0:08:05 The city has been a place of no, you can’t do fun things.
0:08:10 And we turned it into a city of yes, we have helped over 20,000 people exit homelessness.
0:08:17 We have had a significant decline in our crime rate and one of the lowest homicide rates
0:08:18 since the 1960s.
0:08:23 I mean, this is the work that we’re doing, but we also know there’s more to be done.
0:08:24 It’s a major city.
0:08:29 Cities have challenges, but we are finally in a place where we build the capacity.
0:08:30 We change the laws.
0:08:32 We made the hard decisions.
0:08:34 And I just believe that the best is yet to come.
0:08:38 The biggest thing that we do struggle with is the perception.
0:08:42 So we need people to come to San Francisco or people who live here to tell their own
0:08:44 story of San Francisco.
0:08:49 So driving in, I mean, it’s a cliche, like, you know, you talk to a taxi driver, Uber
0:08:52 driver, you drive in from the airport, and I realize I’m not really seeing the city.
0:08:54 You didn’t take a waymo where you didn’t have anybody to talk to?
0:08:58 I have to say, I’m a little bit scared of the waymos so far.
0:08:59 How do you feel about them?
0:09:01 Well, it’s interesting.
0:09:07 They become a tourist attraction in our city, but you just said people do a lot of communication,
0:09:08 but not conversation.
0:09:10 So I don’t know if I’m going to take a waymo.
0:09:11 Because you want someone to talk to you?
0:09:12 I want somebody to talk to you.
0:09:13 Yeah.
0:09:14 All right.
0:09:15 Well, stick with me.
0:09:16 Okay.
0:09:21 I will say driving in from the airport, what I saw mostly were billboards for AI companies,
0:09:23 which I don’t see in New York.
0:09:28 And then I get to the tenderloin and I feel like I’m in a Hieronymus Bosch painting.
0:09:31 It is wild and it’s heartbreaking.
0:09:36 I know it’s been there forever and I know it predated you, but, you know, I just wonder
0:09:37 how much the perception hurt you running.
0:09:38 Okay.
0:09:40 Let me just ask the question I really want to ask.
0:09:41 Why did you lose?
0:09:43 You stood for reelection.
0:09:45 I’m going to say this with a lot of pride.
0:09:49 There was over $20 million spent on my race to unseat me.
0:09:50 Is this all Levi’s money?
0:09:53 I don’t know where the money came from, but there was a lot of money.
0:09:58 I think that things were not happening as quickly as people wanted to see them happen.
0:10:04 And that is something I take full responsibility for because this government and how bureaucracy
0:10:07 works, it is not designed to make things move quickly.
0:10:10 When you say bureaucracy, do you mean mostly the board of supervisors?
0:10:15 I think I do mean a lot of the board of supervisors.
0:10:16 And now this new mayor is getting a good board.
0:10:20 I’m just so mad about it.
0:10:23 People say, oh my goodness, your response to the pandemic was amazing.
0:10:26 And yeah, it’s because we cut bureaucracy.
0:10:32 We had emergency authority to make decisions without the bullcrap that gets in the way
0:10:35 of trying to make things move.
0:10:39 And then we go back to a post-pandemic world after we come out of that.
0:10:45 We needed to be able to act quickly, dealing with the rise in fentanyl overdose tests and
0:10:48 the emptying of our shelter beds and the need to build more houses.
0:10:53 We had all these things we needed to do and could not move fast enough.
0:10:58 And the good news is we work very hard to build our capacity to make the necessary changes,
0:11:03 to use technology, and to really help combat these issues.
0:11:07 And think about it, our crime rates have consistently been dropping.
0:11:11 I mean, even car break-ins are lower than 10,000.
0:11:13 And this is a major city.
0:11:14 It hasn’t been that low since 2015.
0:11:19 Let’s talk about the major city thing, because I come from New York.
0:11:20 And things happen.
0:11:22 Things happen in all major cities.
0:11:26 But that’s my problem is I don’t think of you as a major city.
0:11:36 I think of you as a very, very nice…
0:11:39 Now you understand why I don’t do this live thing.
0:11:44 But don’t you think of San Francisco as a major city?
0:11:50 Okay, Stephen, you better watch out what restaurant you eat in.
0:11:52 Somebody might put something in your food.
0:11:57 Well, that’s not a nice way to make friends with the out-of-towners.
0:11:58 But no.
0:12:00 But where was I now?
0:12:03 Major city, I’m going to skip that question.
0:12:05 You lost some population during COVID.
0:12:10 I did read you say something about how you had fewer people die here per capita than
0:12:12 any other big city in America.
0:12:16 But I was wondering, okay, but wait a minute, wait, save you applause because you’ll boom
0:12:17 in a second.
0:12:23 But I wondered if that’s just because everybody left and they were dying elsewhere.
0:12:25 Listen, let me just say this.
0:12:26 We shut down early.
0:12:29 We made really hard decisions.
0:12:30 It was not easy.
0:12:34 And the people in San Francisco really came together to try and save lives.
0:12:38 I was really proud of how people went grocery shopping for folks.
0:12:43 Folks showed up to work in the hospitals and people sacrificed to make that happen.
0:12:44 And so I’m very proud of that.
0:12:49 A lot of people did leave and they were talking a lot of crap when they were leaving San Francisco.
0:12:51 But you know what?
0:12:58 Many of those people are back because this is $34 billion in venture capitalist investment
0:13:02 of the top 20 AI, artificial intelligence companies in the world, eight are right here
0:13:09 in San Francisco, 5 million square feet of office lease sign in San Francisco, 70% of
0:13:13 the new office space is by new companies in AI.
0:13:17 People are coming back to San Francisco because they know this is where they’re going to
0:13:21 be successful despite what people try to say about the city.
0:13:23 It is still where people want to be.
0:13:24 I’m really glad to hear that.
0:13:29 I do love your city by saying I didn’t think it was a major city mean to imply that I didn’t
0:13:30 love it.
0:13:31 But it has less than a million people.
0:13:32 So I totally understand that.
0:13:33 This makes me think.
0:13:39 I live in New York and we lived there during the 9/11 attack and it was scary, very different
0:13:40 event obviously in COVID.
0:13:44 And I have a sister who lives in Buffalo who called us up and she was very worried about
0:13:45 our family.
0:13:49 She said, Steve, you know, you should really pick up and my kids were very young, pick
0:13:51 up and move to Buffalo.
0:13:52 And I didn’t even think it was so terrible what I said.
0:13:59 I said, Beth, you know, I’d rather die in New York and live in Buffalo.
0:14:04 And to be fair, Buffalo is a wonderful major city.
0:14:05 So let me ask about you.
0:14:09 You grew up hard in public housing, raised by your grandmother.
0:14:10 All kinds of stuff around.
0:14:11 There was crime.
0:14:16 There was drugs, your own family suffered from all that.
0:14:20 And the thing that I really want to know about you, you know, we have this idea when there
0:14:25 are people in the public eye, we just think they’re invincible.
0:14:30 Everybody always has challenges and it’s how they overcome them that really defines us.
0:14:38 So with you, I can’t figure out how you got to where you got with the odds that you faced.
0:14:44 And I’m not asking you for advice necessarily or if you have a superpower, but can you just
0:14:50 describe what it took not just to survive, but to thrive with those barriers.
0:14:52 There are so many different things that happen.
0:14:56 Last time when we talked on the podcast, I talked about my brother who’s incarcerated
0:14:59 and how we both went to the public school system.
0:15:02 He didn’t even graduate from high school and I did.
0:15:07 It’s hard to finger point where the issue happened, but I feel really honored and grateful
0:15:14 to God for just the strength to overcome so many of those obstacles and to get my education
0:15:20 and to want to go back to the community and make a difference.
0:15:21 Obviously you worked hard.
0:15:26 Obviously you were disciplined and all that, but how much do you think is just temperament?
0:15:31 I don’t know if I would say that I have the best temperament because I have a temper, but
0:15:36 I will say that I have remained true to who I am as a person.
0:15:41 But the whole reason why I got involved in public service in the first place is because
0:15:49 a violent crime in my community where people were dying, where our homicide rates were significant
0:15:57 in the 90s and it is just amazing to see us in a better place than we’ve ever been before.
0:16:01 And I have always said it is always the will of the voters that I’m going to respect and
0:16:10 be grateful that I had the opportunity to serve.
0:16:14 Do you feel that you were treated differently than the mayors who came before you who came
0:16:16 from more traditional backgrounds?
0:16:19 I think so a little bit, yeah.
0:16:23 I didn’t talk about it much, but when the mayor calls you and not return the mayor’s
0:16:29 call, that was pretty offensive or to sit in a meeting with me and to look at my chief
0:16:32 of staff and talk to him and not talk to me directly.
0:16:34 How do you handle that in the moment?
0:16:37 In the moment, I’m like, hi, I’m right here.
0:16:42 Nice smile and I’m the one who makes the decision and then I move on from it.
0:16:46 I didn’t come from money, I come from the hood, I didn’t have built-in relationships
0:16:52 with a lot of these people, but I did do what I could to try and reach out to people and
0:16:56 develop those relationships and make sure that my door was always open.
0:17:00 So even if someone opposed me, which, you know, I had a member on the board of supervisors
0:17:03 who was just the worst person to work with.
0:17:04 That person’s name was what again?
0:17:11 Well, here’s the interesting part is somehow once that person decided they wanted to work
0:17:16 with me, we developed a tight, really good working relationship.
0:17:21 And so what I’ve always said is, look, I may not like you, I don’t have to like you, but
0:17:22 I will work with you.
0:17:24 I’ve heard you say that.
0:17:25 I really like that.
0:17:30 I want to steal that because I think most of us, it’s hard to do when you don’t like
0:17:33 someone, but you need to work productively with them.
0:17:34 So what do you do?
0:17:35 Do you picture him?
0:17:36 Nate, what do you do?
0:17:43 No, I just think when I wake up in the morning, I’m the mayor of San Francisco.
0:17:51 Like I’m the mayor of San Francisco.
0:17:52 So come right in.
0:17:57 Look, sometimes it shows on my face, but I’m a grown up here.
0:18:03 And I have to be better than somebody who’s petty because you don’t particularly care
0:18:04 for someone.
0:18:09 I mean, you know what’s in your head, but the business of the people is the most important.
0:18:13 I can’t just support or work with the people who voted for me.
0:18:17 I can’t just talk to the people that I want to talk to.
0:18:22 And it’s what anybody in elected office should be if you are here for the right reasons to
0:18:24 get the business done for the people.
0:18:29 And I’ve been able to accomplish a lot because I’ve always kept the door open.
0:18:34 As we speak, you have a few days left in office, and I want to know what you’re planning next
0:18:35 if you have plans.
0:18:40 And I also want to know the Democrats got crushed this year coast to coast.
0:18:44 And there’s an election in about a month from now for DNC chair.
0:18:47 Was that something that you’ve poked around at by any chance?
0:18:55 So under the law, I can’t look at other opportunities until I actually leave office.
0:19:02 And so I will be having a lot of meetings once I leave office because I need a job.
0:19:07 Let’s just pretend that you’re elected DNC chair in a month, whatever it is.
0:19:12 What would you say, considering the shellacking that the party had, what’s the thing or two
0:19:17 that you think the Dems need to do to put themselves in position to win some more elections?
0:19:22 I think that the biggest thing we need to do is cultivate young, new talent.
0:19:25 I mean, my race is a perfect example.
0:19:31 I am a perfectly capable, qualified Democrat who runs a major city.
0:19:38 And when you have young Democrats, you guys like that, huh?
0:19:43 When you have people in these various positions, whether it’s mayor or board of supervisors
0:19:51 or other places, we have to invest the resources into helping to grow our talent pool to ensure
0:19:53 that we have a pipeline.
0:19:55 Do you think the Republicans have done that well?
0:20:00 Or do you think that they’re, because look, Trump is no one’s idea of an ideal candidate.
0:20:03 And yet one by a lot, you could read that a few ways.
0:20:06 A lot of people like Trump a lot, which is plainly the case.
0:20:10 And or the Democrats were really unpopular.
0:20:13 I’m just curious, and I know you faced it yourself.
0:20:15 Your far left hit you very, very hard.
0:20:19 You had to deal with a lot of things as ultimately a centrist Dem.
0:20:24 So I’m just wondering if the big tent needs to be reconfigured for the Dems.
0:20:26 I think that the tent needs to be open.
0:20:28 Again, I come from nothing.
0:20:33 So I’ve only mostly volunteered and helped people in their campaign.
0:20:35 So it’s significant that I’m mayor.
0:20:41 So how do we capitalize on that in order to ensure that people like me don’t get lost
0:20:48 by the party, but really does start with, how do you get more people choosing to register
0:20:51 as a Democrat rather than decline to state?
0:20:53 How do you feel about open primaries?
0:20:58 I would be open to it, but I’m not 100% sure that that’s the right route to go.
0:20:59 Because why?
0:21:00 What’s the advantage?
0:21:03 I mean, there are a lot of good arguments for why a two-party system is not as bad as
0:21:04 we always say it is.
0:21:08 Because when you look at the alternatives, there are many countries with five, 10 parties
0:21:11 and they’re in worse chaos, honestly.
0:21:15 I mean, it’s politics and you got to remember politics is never going to be nice and wrapped
0:21:16 into a neat little bowl.
0:21:18 It’s going to be something you have to fight for.
0:21:23 The reason why I struggle with the open primary has a lot to do with, I want to see the Democrats
0:21:30 united and I want us to do the work to get behind the candidate, whether we agree with
0:21:35 that person or not to really fight for that candidate and also to listen to people as
0:21:38 to why they might want something different.
0:21:42 We may see something or hear something and we say, “Oh, they don’t know what they’re
0:21:43 talking about.”
0:21:45 But you know what?
0:21:50 If you listen closely and you hear what they’re saying, you have to think about, “Well, how
0:21:55 do we appeal to the people who we believe may not know what they’re talking about?”
0:22:00 I just think you have to be a little bit more open-minded and not just toss someone to the
0:22:06 side just because their beliefs aren’t 100 percent of what you think our value system
0:22:12 should be because clearly we got a lot of work to do and we have to understand all those
0:22:15 different states differently than we have in the past.
0:22:17 That’s really, really nicely said.
0:22:20 Congratulations on your career, everything.
0:22:24 Thank you for coming out tonight.
0:22:29 We will be back with more from our live show in San Francisco right after this.
0:22:41 Okay, back now to our recent live show in San Francisco.
0:22:46 All right, I’m having a good time.
0:22:47 Are you?
0:22:53 Are we okay?
0:22:58 You may be wondering why we are here at this big theater in San Francisco on this rather
0:23:00 awkward date.
0:23:02 It’s January 3rd, I guess.
0:23:08 Nobody does events this week, the week of New Years, but we’re here because this week
0:23:14 in San Francisco is the annual meeting of the American Economics Association.
0:23:20 The AEA is, as you can imagine, it’s a huge gathering of economists from all over the
0:23:25 world and it really is as exciting as that sounds.
0:23:29 And then you ask, “Well, why would they hold it now in the week of New Years when everything
0:23:32 is dead, everybody’s traveling and so on?”
0:23:39 And the reason is because economists are really cheap and when they’re booking these conferences
0:23:45 every year in a different city, they want the cheapest week for the hotels and the conference
0:23:50 center and therefore they hold it immediately after New Years.
0:23:58 And so when we heard it was coming to San Francisco this year, major city, we decided we go to
0:24:03 these AEA conferences to scout stories and to see our economists friends and to look
0:24:07 for new economists friends for the sake of Freakonomics Radio and so on.
0:24:10 But then we also decided this year, because we would be in a major city, that we would
0:24:13 put on this live show at the same time.
0:24:19 So we had the mayor, which is fantastic, but we have another couple of guests that we were
0:24:24 able to wrangle because the AEA was here.
0:24:26 We’ve got two more economists to come.
0:24:27 Let’s welcome the first one.
0:24:31 Please give a warm hand to Mr. Coleman Strumpf.
0:24:38 Coleman, come on out.
0:24:40 [applause]
0:24:46 Coleman, here are a few things I know about you.
0:24:51 As a kid, you got into trouble bringing candy bought at retail to school and selling it
0:24:53 at a very high markup, correct?
0:24:54 Yep.
0:24:55 My introduction to crime.
0:24:58 Introduction to crime or introduction to thinking like an economist?
0:24:59 Maybe they’re not so different.
0:25:00 Maybe they’re not so different.
0:25:02 I’ve been saying that a long time.
0:25:03 Nobody believed me.
0:25:09 I also know that as a child, you appeared in a TV commercial for Tang, the astronaut beverage,
0:25:10 is that true?
0:25:16 I, in fact, did with the rest of my family and I only say if you spend a whole day drinking
0:25:20 Tang, if you even know what that is, you will not feel so good the next week.
0:25:21 All right.
0:25:25 You’re now an economist at Wake Forest and most of your research that I’m familiar with
0:25:31 at least has been about what I would characterize as illicit and taboo activities.
0:25:34 Would you name a few that you’ve looked into over the years?
0:25:35 Yeah.
0:25:40 Sports betting, not the stuff you do on your phone, but the guy in the corner.
0:25:45 I’ve done some work on cannabis, which we might talk a little bit more about.
0:25:46 File sharing.
0:25:49 File sharing like stealing digital products.
0:25:51 You’re an empirical economist.
0:25:52 You work with data.
0:25:55 How do you get the data when you’re dealing with illicit goods?
0:25:56 It’s not as hard as you’d think.
0:25:58 I’ll tell you about sports betting.
0:26:04 I was very interested in sports betting and I one time went to Las Vegas, which was about
0:26:08 the only place you could do sports betting and I tried to wrangle up with one of the
0:26:09 bookmakers.
0:26:13 I was like, “Can you give me some information about what you guys do?”
0:26:15 And he laughed at me.
0:26:21 So maybe as a way of getting revenge on the guy, I ended up making a friend in Brooklyn’s
0:26:26 district attorney’s office and now I have a bunch of records on illegal bookmakers.
0:26:31 So I still don’t know a lot about what the guys in Las Vegas do, but I can tell you about
0:26:32 a lot of guys in New York.
0:26:34 So you blackmail people essentially, huh?
0:26:36 I get a little revenge.
0:26:40 The reason I wanted to have you on the show tonight is you appeared in an episode we made
0:26:46 back in I guess the fall, not long before the election talking about betting markets, prediction
0:26:52 markets which are sometimes the same as betting markets, some legal but mostly kind of illegal.
0:26:54 Also you helped us out with a later episode.
0:26:58 We did a series on the economics of cannabis and you had a lot of data that nobody else
0:27:02 had about legal and illegal weed shops.
0:27:09 How can you tell an illegal from a legal weed shop, let’s say in California, other than
0:27:13 maybe you go sample door-to-door, I don’t know how that works?
0:27:18 Those of you who in the audience who are interested in cannabis might know a website.
0:27:22 Should we turn the house lights on and have a show of hands or something?
0:27:28 You might know an app called, you might know an app called Weed Maps.
0:27:32 Those of you who have never used it, it’s maybe like Yelp for pot.
0:27:35 Fired up on your phone, put on the GPS, tells you all the stores near you.
0:27:41 So I saw this app and I said, hmm, it’d be kind of cool if you could just get everything
0:27:44 that’s on that site and stockpile it.
0:27:49 And if you spend a little time kicking around in the background, you can figure out a way
0:27:50 of doing that.
0:27:55 So I always have a lot of computers running and a bunch of computers for several years
0:27:57 just pulling stuff off this site.
0:28:00 So I have a list of all the stores.
0:28:04 Now how do I know who’s legal and how do I know who’s illegal?
0:28:08 So the state of California publishes a list of the legal stores.
0:28:12 So I could start using that, but the information’s a little bit incomplete.
0:28:19 So I had to look at different online sources, including Google Maps to see stores magically
0:28:25 turning from a kid’s store into a weed store in Los Angeles and you can kind of figure
0:28:29 out through a lot of sweat, which ones are legal and which ones are not.
0:28:33 Now when they’re listed on the site, whether it’s the weed map site or the California data,
0:28:35 there’s a license number, I assume, right?
0:28:37 That’s what makes a legal shop legal.
0:28:39 Do the illegal shops just make up a number?
0:28:44 Yeah, they either make up a number, go down the street, look at the legal store, take
0:28:46 a picture of that and use that number.
0:28:50 Or sometimes they just put up stuff that isn’t even a valid number.
0:28:55 Now the thing that blows me away is when in a place like California, let’s take LA versus
0:28:56 San Francisco.
0:29:01 In LA, you told us something like 70% of the weed shops are illegal.
0:29:03 So can you explain how the economics of that works?
0:29:05 Why do they proliferate?
0:29:09 Obviously, it’s cheaper because you’re unlicensed, but why are they allowed to proliferate?
0:29:11 Yeah, that’s a great question.
0:29:16 There’s not a lot of, I guess, will among policymakers to do it.
0:29:21 The people who would be doing the enforcement, the police, think about how hard this job
0:29:22 is.
0:29:27 If I say, arrest people who are doing some activity, well, I just see somebody doing
0:29:28 this activity.
0:29:35 Now you need to say, not just as somebody selling cannabis, but as somebody who’s licensed
0:29:36 or unlicensed.
0:29:37 They’re literally doing the exact same thing.
0:29:40 Some people are doing it legally, some people are not doing it.
0:29:41 It’s not so easy.
0:29:46 But I would imagine that, let’s say you and I teamed up and we said, you know what, alcohol
0:29:50 is pretty cheap to make, if you think about it, just to ferment some stuff and you put
0:29:56 it in a bottle, then you brand it, and then you can sell it for like 20, 30, 50, 80, $100.
0:29:58 And we know there’s a lot of tax associated with that.
0:30:02 So let’s say that you and I could either fake it or get the real stuff a little bit cheaper
0:30:06 and just open a liquor store without having to pay any of the taxes and regulation stuff.
0:30:08 Why do we never see that?
0:30:13 In the wake of prohibition, actually, you did see things like that for 15 years.
0:30:19 Through the 1950s, you would have lots of arrests of people having illicit stills and
0:30:20 things of that sort.
0:30:25 Today, in cannabis, the illegal people are pretty sophisticated.
0:30:30 So one of the things in this weed maps data I have is I have a list of all the products.
0:30:31 What are some of your favorites?
0:30:33 Well, I like to observe.
0:30:36 Honestly, I’m a little out of date on them.
0:30:37 Is that true?
0:30:38 Yes.
0:30:39 You’re not a big…
0:30:40 I took you for a big…
0:30:41 Yeah, I definitely have that.
0:30:42 Yeah.
0:30:44 But at any rate, so I am familiar with some of the big brands.
0:30:47 The good news is, apparently Tang is not a gateway drug then.
0:30:48 Yeah, right.
0:30:53 Well, maybe it’s a gateway drug to being an economist, but I don’t really know.
0:30:59 But at any rate, if you’re wanting to sort of pretend you’re running a legitimate place,
0:31:02 you’ll take a name brand and you’ll just switch a letter.
0:31:06 And they literally get old containers or wrappers from legal stuff, and they’ll put
0:31:08 it around the legal stuff.
0:31:13 Also, one thing you told us was that in San Francisco, there are many fewer illegal shops,
0:31:15 which has to do with the way that they run their programs.
0:31:18 So I don’t know if Mayor Breed had anything to do with setting up that program.
0:31:22 We actually interviewed the guy who did that, but something like 20% of the shops here are
0:31:25 illegal versus LA about 70, right?
0:31:26 That’s what your data says.
0:31:30 Yeah, and these are from a few years back, but I would say the number is probably still
0:31:31 about holding.
0:31:37 But I would think that the illegal shops benefit further by having legality because that drives
0:31:40 the price up with the licensing and it makes their stuff, which might be identical, much
0:31:41 cheaper, yeah?
0:31:44 And on top of that, there’s the social norm.
0:31:49 I live in North Carolina where it’s not so different from what I remember growing up.
0:31:55 In New York, in San Francisco, all California, the norm about how acceptable is cannabis
0:31:59 as a thing to be using, much more accepted today than it used to be.
0:32:01 And it’s going to spill over to the illicit side as well.
0:32:05 So I would argue demand is probably much higher.
0:32:06 We could talk a long time about cannabis.
0:32:08 It’s a very interesting economy.
0:32:10 Also, the elections this year were interesting.
0:32:14 It got voted down in Florida, I think North and South Dakota.
0:32:18 But it’s interesting that we’re talking about what people used to call vices, right?
0:32:23 It’s betting, but it’s now mostly legal in the US, cannabis, mostly legal in the US.
0:32:26 What about betting on elections?
0:32:27 You know a lot about that.
0:32:33 Do you think that will become fully legal in the US in the next, you know, five, 10 years?
0:32:37 I usually, when I try to make a forecast, I look at these markets to answer the question
0:32:40 rather than try to answer it on my own.
0:32:46 Things look pretty promising, but everything is going to be governed by what a judge will
0:32:48 maybe say about these things.
0:32:51 There was a lot of enthusiasm about these markets this time.
0:32:54 They did a pretty good job at forecasting the election.
0:32:57 You argue they do, on average, better than polling.
0:32:58 Yes.
0:32:59 Yeah, definitely.
0:33:03 There’s a fundamental difference between polls and these markets.
0:33:07 The way a poll works, which is probably what most people in the audience are familiar with,
0:33:14 is you talk to a bunch of people, the representative of all voters, and you see what they’re thinking.
0:33:16 These markets are supposed to work in a totally different way.
0:33:21 You could step outside your own experience and say, look, my goal presumably is to make
0:33:23 some money at forecasting the election.
0:33:26 Well, that has nothing to do with what I think in terms of who I like.
0:33:29 I’m trying to guess what other people like.
0:33:31 Where’s the information coming from?
0:33:32 Everywhere and anywhere.
0:33:33 Right.
0:33:35 So why would it, on average, be more accurate than polling?
0:33:39 Look, we’ve learned this election and past elections that many pollsters are just not
0:33:40 very good.
0:33:41 Let’s be honest, right?
0:33:45 It’s not a particularly scientific science, if you want to call it that.
0:33:50 But still, why would they who are setting out to do one thing in a very binary way?
0:33:55 I ask a bunch of people, this candidate or that candidate, why would they not be better
0:34:02 than a group of people who are looking to profit from feeling they know a piece of information?
0:34:06 This election was probably the best case example I could give of that.
0:34:12 So when people are polled about certain candidates, they tend not to always say who they support.
0:34:18 So traditionally, Donald Trump underperforms and polls.
0:34:19 David Dinkins.
0:34:22 I don’t know if you remember this in New York City, the first black mayor of New York City.
0:34:23 He over polled by a lot.
0:34:29 A lot of people wanted to be seen saying that, yes, I will vote for the first African-American
0:34:30 mayor.
0:34:31 Right.
0:34:35 So let me tell you about the person who was the most successful better in 2024, who was
0:34:37 a French citizen.
0:34:38 He had a very similar view.
0:34:41 He said, I don’t think these polls are working very well.
0:34:44 But I’m going to run my own poll.
0:34:50 And so he asked a slightly different question, which was not who do you support?
0:34:52 Who do you think your neighbors support?
0:34:57 There’s a little bit of work that suggests that people are a little bit more realistic
0:35:00 about thinking about that question than what they themselves think.
0:35:06 Anyway, he was so confident in what he found from this poll that he put down $80 million
0:35:08 on Donald Trump to win.
0:35:11 And yeah, he made $80 million.
0:35:17 Does this suggest that pollsters next time around will basically emulate that methodology
0:35:22 of asking a question that’s not so binary, it’s not so, what are you going to do?
0:35:26 I’m pretty skeptical of pollsters getting into the 21st century.
0:35:31 Like the writing’s been on the, like, forget about what I’ve just been saying.
0:35:36 Being a pollster is infinitely more difficult today than it was 40 years ago.
0:35:37 Absence of landlines.
0:35:38 Yeah.
0:35:43 I don’t know who’s calling, and my phone doesn’t equate to where I physically am.
0:35:45 It’s just very hard to do polls.
0:35:51 The kind of advancements that they’ve made are relatively marching, in my opinion.
0:35:57 The thing that most surprised me about your work talking to you is how the betting markets
0:36:04 on elections have been around for a long time and have been accurate for a long time and
0:36:05 have been robust for a long time.
0:36:09 Do you know anything about San Francisco history?
0:36:15 San Francisco definitely had their own markets, many of which were relatively big money, millions
0:36:17 of dollars in today’s dollars.
0:36:21 They would take place in like cigar stores and things like that.
0:36:23 We’re talking 1900, a long time ago.
0:36:27 Some people had money, but a lot of people didn’t have money, but there were fewer things
0:36:29 to bet on back then.
0:36:32 So people were really into betting on elections.
0:36:34 And so they would do these non-monetary bets.
0:36:37 If you didn’t have the cash, they call them freak bets.
0:36:38 I don’t really…
0:36:39 Freak?
0:36:40 Freak bets.
0:36:41 I don’t…
0:36:42 F-R-E-A-K?
0:36:43 As in a certain book that I’m familiar with, yes.
0:36:44 I like the sound of that, yeah.
0:36:47 At any rate, they did all sorts of crazy things.
0:36:51 It was, “I won’t shave for the next 20 years.
0:36:53 I’ll walk halfway across the country.”
0:36:54 And these are documented somewhere?
0:36:57 Yeah, these are all at least newspaper stories.
0:37:03 And my favorite San Francisco story that I saw was in 1916, which was a very tightly
0:37:05 contested election.
0:37:06 Two people…
0:37:07 1916?
0:37:08 1916.
0:37:10 So this is Woodrow Wilson getting reelected.
0:37:15 And two people were betting, and the loser had to get dressed as a woman.
0:37:16 Okay.
0:37:17 These were two men.
0:37:18 In public and private?
0:37:20 In public and within a mile of here.
0:37:21 And go out and parade around?
0:37:22 And they would parade around.
0:37:28 And so this one guy did, apparently it was not legal to dress as a woman at that point
0:37:29 in time.
0:37:33 This guy got arrested, and then his friends came and bailed him out, apparently.
0:37:36 So for losing the bet, he had to dress as a woman, and because it was illegal to dress
0:37:38 as a woman, he was arrested?
0:37:39 He was arrested.
0:37:40 Wow.
0:37:41 Wow.
0:37:42 Prime really does not pay.
0:37:43 That’s brutal.
0:37:44 No.
0:37:45 When was cross-dressing illegal until?
0:37:47 In San Francisco, I think 40 years ago.
0:37:48 Really?
0:37:49 And that’s San Francisco?
0:37:50 Yeah.
0:37:51 Yeah.
0:37:52 Major City.
0:37:53 All right.
0:37:55 Well, Coleman, thank you.
0:37:56 It’s always great to talk to you.
0:37:57 Great.
0:37:58 Thanks.
0:38:06 This is Stephen Dubner, and you were listening to a Freakonomics Radio show.
0:38:09 We recorded live in San Francisco on January 3rd.
0:38:20 We will be right back with our final guest.
0:38:22 We have one more guest tonight.
0:38:29 He is an economist at a nearby school called Stanford, I believe it’s pronounced, which
0:38:36 please welcome Eric Brynjolfsson.
0:38:47 Okay, I’m very fond of this man, very, very interesting and bright fellow.
0:38:53 So Eric, it says that you are a senior fellow at the Stanford Institute for Human-Centered
0:38:54 AI.
0:38:55 Is that correct so far?
0:38:56 So far, so good.
0:39:00 And you’re also director of the Stanford Digital Economy Lab.
0:39:01 So I just want to know what both of those are.
0:39:04 I want to know what a human-centered AI is, honestly.
0:39:06 Well, that’s a good question.
0:39:11 Fei-Fei Li started it along with Jonathan Chimendi, and they recruited me out to Stanford.
0:39:12 You were MIT?
0:39:15 Yeah, I was at a major city in Massachusetts.
0:39:19 You’re picking bones with me, because that is the other city that thinks it’s a major
0:39:20 city.
0:39:22 Well, I’m sorry, it keeps…
0:39:26 It’s too bad we keep feeding New York in all the sports, but that’s just the way it goes.
0:39:28 You know, here’s the thing about New York in sports.
0:39:32 When you’re a major city, the sports don’t really matter that much.
0:39:33 Good.
0:39:35 Yeah, you can cope.
0:39:40 So the idea is that AI is doing these amazing things, but we want to do it in service of
0:39:44 humans and make sure that we keep humans at the center of all of that.
0:39:48 A lot of technologists are very focused on the technology, but I’m an economist, as you
0:39:53 mentioned, and they’re political scientists, sociologists, artists, and we’re all working
0:39:59 to use AI to help lots of the other parts of the world and of academia.
0:40:04 When you talk about human center, I mean, one thing that comes to my mind is labor, right?
0:40:05 Yes.
0:40:08 You and I have had this conversation on the show for probably eight or 10 years now about
0:40:15 to what degree does automation and AI mean job replacement, and if so, how big a problem
0:40:16 is that?
0:40:20 But you’re talking about more than just machines doing human jobs.
0:40:26 You’re talking about having AI or having technologies that let humans be human in their most essential
0:40:27 way or what?
0:40:28 Totally.
0:40:31 Too many people think of machines as just sort of trying to imitate humans.
0:40:35 There’s this iconic test of artificial intelligence called the Turing test that many people are
0:40:39 familiar with, which is how much can you make a machine mimic a human to the point where
0:40:41 you can’t tell which is which.
0:40:46 That was, I think, a visionary idea when Alan Turing proposed it in 1950, but in a way,
0:40:50 it’s a very constraining idea because machines can help us do new things we never could have
0:40:55 done before, and that’s a much higher ceiling, and so we want to look for ways that machines
0:40:59 can complement humans, not simply imitate or replace them.
0:41:03 I wrote a paper recently called The Turing Trap trying to steer people away from this
0:41:06 idea of just imitating humans.
0:41:12 If we were having this conversation a year ago about AI generally, the first five questions
0:41:16 would be, “So, are the machines going to wipe out humanity?”
0:41:20 Now, it’s not that nobody’s thinking about that and concerned about it anymore, but
0:41:22 it’s no longer the conversation.
0:41:24 Why is that?
0:41:26 I think it’s still part of the conversation.
0:41:27 I don’t know.
0:41:30 Maybe in the press, there’s things that go up and down in cycles to some extent.
0:41:32 AI is becoming much more powerful.
0:41:36 There continues to be rapid progress, and the good news is we can have tremendously
0:41:43 higher productivity and wealth and have medical solutions addressing poverty in the environment,
0:41:50 but it also raises a number of risks, misinformation or people using it in a way that creates weird
0:41:55 interpersonal dynamics, AI boyfriends and girlfriends, maybe millions of those that people have as
0:41:59 their primary relationship, pathogens, and even catastrophic risks.
0:42:02 Say more about pathogens in AI.
0:42:08 The great thing is AI can help us discover new drugs, as well as new materials.
0:42:13 There’s just a study from a grad student at MIT describing how researchers using AI were
0:42:19 able to discover 44% more materials than a randomly assigned group that didn’t have
0:42:22 access to the technology, so a big difference.
0:42:24 Some of those new materials, lots of them can do good things.
0:42:27 You can also create dangerous ones.
0:42:31 You can flip the bit on a drug that’s meant to make you healthier, and it can make you
0:42:35 much less healthy to the point of killing you.
0:42:37 You know a lot more about this than most of us do.
0:42:39 You’ve come at it from a variety of angles.
0:42:44 We’ll talk about the economic angle in a little bit, but would you call yourself generally
0:42:45 a techno-optimist?
0:42:48 I’d say I’m a mindful optimist.
0:42:51 What I mean by that is that they’re sort of blind optimists.
0:42:54 I run into a lot of those in Silicon Valley who are just like, “Hey, don’t worry.
0:42:55 Just chill.
0:42:57 It works out in the past.
0:42:58 It’s going to be great.
0:43:00 Just sit back, and we’re going to have a great time.”
0:43:03 There’s a lot of pessimists who basically say the opposite.
0:43:07 They both make the same mistake, I think, which is they take the agency away from us.
0:43:11 This technology is going to do stuff to us, and whatever it is is what it is.
0:43:13 I think that we have a lot of choices.
0:43:18 One of the reasons I came to Stanford, the Center for Human-Centered AI, is that I think
0:43:23 we can help steer the technology in ways, and if we do it right, we could have the best
0:43:26 decade we’ve ever seen, but it’s not inevitable.
0:43:27 Okay.
0:43:29 But we’ll call you a mindful optimist is what you say.
0:43:30 Thank you.
0:43:32 Do you know much about what they call nominative determinism?
0:43:33 Have you ever heard that phrase?
0:43:34 No.
0:43:39 It’s the idea that your name, your very name has some effect.
0:43:41 That sounds like a good Freakonomics chapter.
0:43:45 We wrote a chapter about names that almost everybody remembers wrong.
0:43:47 We wrote that there is no such a thing.
0:43:48 Mr. Baker is a baker.
0:43:49 Yeah, exactly.
0:43:53 My name is Stephen Baker, and I open a bakery, or my name is Dennis, and I become a dentist.
0:43:54 And so on.
0:43:57 But there are people who believe that, but with you, I got to thinking.
0:44:01 I looked up the etymology of your name, Eric Brynjolfsson.
0:44:07 The internet tells me the last name is an Icelandic patronymic, son of Brynjolf.
0:44:13 With Brynjolf broken into Bryn, which means armor, and jolf meaning wolf, so son of the
0:44:19 armored wolf, and then Eric usually translates to eternal ruler or ever powerful.
0:44:23 So you are the ever powerful son of the armored wolf.
0:44:28 Do you think that’s why you’re an optimist?
0:44:29 That would make sense.
0:44:34 That’s what people, when I go to Iceland, that’s how people know me.
0:44:35 It’s true.
0:44:40 I’ve heard you talk in the past about, as I understand it, essentially a new way of
0:44:43 measuring our economy.
0:44:46 You call it GDPB, so I want you to tell us about that.
0:44:48 I want you to tell us what the B stands for.
0:44:51 But I want you to start at the beginning, because many people, even people who have
0:44:57 nothing to do with economic sync, GDP is a highly imperfect measure of what we want it
0:44:58 to measure.
0:45:01 And if I recall correctly, I don’t know much about this, but I’m sure you do.
0:45:06 But the inventor of Simon Kuznetz, when he created GDP, warned that it should not be used
0:45:08 for essentially what we’re using it for.
0:45:09 That’s exactly right.
0:45:14 Simon Kuznetz, with his team in the 1930s, basically developed what we now use as our
0:45:18 national accounts, GDP, productivity is all based on the system of accounts.
0:45:22 Paul Samuels, one of the greatest inventions of the 20th century, I agree, but it’s also
0:45:25 been massively abused and misused.
0:45:29 Nowadays, if you see a headline, economy grew by 3.2%.
0:45:32 They mean GDP increased by 3.2%.
0:45:34 And why is that an imprecise or not useful measure?
0:45:39 Well, GDP measures basically everything that’s bought and sold in the economy.
0:45:44 What that means, with few exceptions, if something doesn’t have a price, it’s not counted in
0:45:45 GDP.
0:45:47 So we’re missing a lot of important stuff.
0:45:52 Clean air, a classic problem is if I cook a meal for myself, that’s not part of GDP.
0:45:57 But if I hire somebody to cook it, or if somebody pays me to cook it, then it is part of GDP.
0:45:59 So you have a lot of little weirdnesses like that.
0:46:01 A lot of household production is not there.
0:46:05 And one of the biggest ones, I’m the director of the Stanford Digital Economy Lab, is all
0:46:11 these digital goods that are often free, Wikipedia, search, Facebook, texting, email.
0:46:15 If they have zero price, other than the electricity and a few other things, they’re basically
0:46:17 not counted in GDP.
0:46:19 Yet people get a lot of value from them.
0:46:24 Right now, the average American spends a little over eight hours per day looking at a screen
0:46:28 of some sort, TV, computer, whatever.
0:46:31 That means they’re spending slightly more than half their waking hours interacting
0:46:34 with bits, not with all the other things.
0:46:40 That means a big part of our lived experience is these things that are not being well measured
0:46:42 by traditional GDP.
0:46:46 So it’s interesting, because where you’re heading here plainly is that we are richer
0:46:51 than we appear, because how we’re counting wealth is imprecise and incomplete.
0:46:56 On the other hand, if we’re even richer than the numbers say, why are so many people so
0:46:57 miserable?
0:46:59 Well, you’re absolutely right.
0:47:02 We have a lot more wealth than we had before.
0:47:04 But we also did before as well.
0:47:09 I mean, there’s television and penicillin, things were also not counted very well.
0:47:15 But wealth is not the same as happiness, as we know, and so it doesn’t automatically translate
0:47:16 one for one.
0:47:20 But it doesn’t mean we have an imperfect measure of the value that our economy is creating
0:47:21 for us.
0:47:26 There is this famous in economics idea of basically diminishing return on wealth and happiness
0:47:30 that was argued by Danny Kahneman and someone else, I can’t remember who, that original
0:47:31 paper.
0:47:35 Easterlin is called the Easterlin paradox that what you just said that as people got
0:47:37 richer, they didn’t seem to get happier.
0:47:41 More recent research found that, actually, it just sort of is diminishing returns like
0:47:42 you’re saying.
0:47:43 It’s not that it actually stops.
0:47:44 Yeah.
0:47:45 And I guess this is what gets us to GDPB.
0:47:47 So tell us what the B stands for.
0:47:48 Yeah.
0:47:50 Who are you working with or for?
0:47:54 And what is the intention of invoking this new measure?
0:47:56 So the B stands for the benefit.
0:48:01 As I said earlier, GDP is basically a measure of production, what it costs to produce things.
0:48:05 The GDPB is trying to capture the consumer surplus.
0:48:09 It’s the value between what the most you would have paid, what you actually have to pay.
0:48:14 So with Wikipedia, if you would have been willing to pay $15 a month and you pay zero,
0:48:15 you’re getting $15 of consumer surplus.
0:48:17 And you’re trying to measure that.
0:48:18 Yes, we are.
0:48:19 How do you do that?
0:48:25 So if I were to do a survey and say, okay, I’ll give you $500 to stop using the internet
0:48:29 or stop using email, more realistically, for 30 days.
0:48:31 Some of you would raise your hands and some of you wouldn’t.
0:48:36 If I said, okay, what if I gave you $50, what if I gave you $5, you get fewer and fewer
0:48:38 people being willing to give it up.
0:48:40 And that gives you a downward sloping demand curve.
0:48:45 A lot of people think it’s worth at least $500, not so many think it’s only worth $5.
0:48:50 And the area under that curve, we call that consumer surplus.
0:48:53 And if you do that for lots of different goods, you start getting a sense of how much value
0:48:54 all these different goods are creating.
0:48:56 And is this a government project?
0:49:01 No, it’s something I came up with on my own where we decided that we should measure consumer
0:49:02 surplus and not just cost.
0:49:05 And so we started doing some small scale surveys.
0:49:09 And we got some money from different groups, the National Science Foundation, the Sloan
0:49:10 Foundation.
0:49:12 So I guess part of it is a government project.
0:49:15 And we’d love to get more support to do it at a larger scale.
0:49:20 We’re doing about 250 goods right now, including digital goods, non-digital goods.
0:49:24 We ultimately want to get a representative basket of several thousand goods that we can
0:49:30 track periodically alongside traditional GDP and see how they compare.
0:49:33 The thing that’s so interesting to me, I mean, the whole thing is fascinating.
0:49:38 I’m curious to know what the ramifications would be if your measure were to become widely
0:49:39 embraced.
0:49:44 But one consequence that I could imagine is that the way that our government currently
0:49:49 looks at regulation and antitrust especially, which is going to change with the new administration
0:49:50 for sure.
0:49:55 But when you’re talking about basically the hidden or uncounted benefits of many, many,
0:50:01 many firms that are the targets of regulators now, it could be that those benefits that are
0:50:08 not being counted should be reason for antitrust legislation to be considered very differently.
0:50:09 Would you say that’s the case?
0:50:10 Yeah.
0:50:15 I mean, I think already there is a standard among many antitrust experts that came out
0:50:19 of Chicago actually that, you know, we should look at consumer welfare as the ultimate metric.
0:50:20 But that was a few decades ago.
0:50:22 I feel like we’ve moved past that now.
0:50:23 Well, that’s the concept.
0:50:28 In terms of measuring, so Lina Khan has a different measure and there’s an ongoing debate.
0:50:33 But I like the consumer welfare standard, which is, you know, is this concentration,
0:50:38 this merger, this spin off, whatever, is it making consumers better off or worse off?
0:50:39 And that’s hard to measure.
0:50:42 But our tool, GDPB, gives us a set of measures for that.
0:50:43 And you’re right.
0:50:48 In many cases, there’s a tremendous amount of value from Google search or from email.
0:50:52 One of my students was over in the European Commission and they were upset about all the
0:50:56 money that the big companies based here in San Francisco and around the United States
0:51:00 were making on European consumers and saying, oh, this is a very unbalanced thing where
0:51:03 there’s a lot of money going in this direction.
0:51:07 And he pointed out, well, actually, if you measure the value that people are getting,
0:51:11 there’s far more value that French citizens are getting from these services than what
0:51:12 they’re paying.
0:51:14 So the net gain is in the other direction.
0:51:15 That’s really interesting.
0:51:19 I mean, I’m guessing that the way that European regulators think about American tech firms,
0:51:23 that argument as true as it might be is probably not going to change the regulatory position.
0:51:25 Not as much as them having their own tech firms.
0:51:29 And so when they have companies like Mistral, I met with the finance minister in France,
0:51:33 and he was coming around to the view that, well, actually, maybe tech companies can create
0:51:37 some value now that we have one of our own.
0:51:40 So there’s quite say it that way.
0:51:47 I would argue that Silicon Valley, Northern California generally, have created an innovation
0:51:55 economy that is now global and just massively large and massively influential in many ways.
0:52:01 In a way, I feel like the global economy kind of is, at root, the Silicon Valley economy.
0:52:05 I know we still do a lot of other stuff in this country, and it’s not the majority of
0:52:09 the economy by any stretch, but it’s such a fundamental part.
0:52:15 And more so, it has such sway in our daily lives, in our political lives, and so on.
0:52:20 And when I hear you talk about GDP, I think, if anything, we are underweighting the leverage
0:52:22 of this economy here.
0:52:25 So I’m curious to know if you think I’m medium wrong, totally wrong, only a little bit wrong
0:52:26 or maybe a little bit right.
0:52:27 I agree.
0:52:31 I mean, look, I moved out here four years ago from Boston, another pretty innovative
0:52:36 place, but I really underestimated how amazing the culture is out here.
0:52:39 I am constantly meeting people doing startup things.
0:52:43 They have these grand visions and dreams, and I think they’re mostly pretty sincere about
0:52:45 wanting to change the world for the better.
0:52:47 I moved here in summer of 2020.
0:52:49 I remember it was COVID.
0:52:53 We had this garden party, and I sort of half-jokingly nervously said, “Hey, are you guys all going
0:52:55 to be moving to like Austin or Miami or something?
0:52:57 Did I kind of miss the party?”
0:52:58 And they laughed at it.
0:52:59 “Oh, don’t worry.”
0:53:01 It kind of seems like, you know, San Francisco and the Bay Area is going downhill.
0:53:02 I said, “Don’t worry.
0:53:03 There’ll be something.”
0:53:05 We didn’t know about Chatch E.P.T. at that point.
0:53:08 Maybe a few of the people in the room might have been working on it for all I know.
0:53:13 But then, of course, there’s this explosion, and if anything, I think the tech innovation
0:53:18 scene is even more concentrated in the Bay Area now than it was when I came in 2020.
0:53:21 And there’s just a whole wave of innovations.
0:53:24 People talk about it, but, and I’m an economist, I don’t really fully appreciate it until I’m
0:53:25 here.
0:53:28 There’s a cultural element to it, an attitude.
0:53:31 It partly attracts people from around the world who have this mindset of wanting to
0:53:33 change the world.
0:53:38 People help each other to do it, and like you said, it’s been a tremendous engine of creativity
0:53:39 and wealth creation.
0:53:45 And what about the, I mean, I said it derisively and half jokingly, but what about the failed
0:53:49 state feel that San Francisco has projected to the world?
0:53:55 At least how do you reconcile the, you know, the epicenter of the global tech machine and
0:53:59 economy with the fact that this is a city that has repelled people?
0:54:00 Yeah.
0:54:01 It’s a tragedy.
0:54:03 Part of it, to be fair, I think it’s overrated.
0:54:06 Like London Breed was saying, I heard, you know, apparently it has the lowest murder
0:54:10 rate in 60 years, and, you know, I come up to San Francisco a fair number of times.
0:54:15 I don’t think it’s like what is described by Elon Musk or others on Twitter.
0:54:21 Well, there’s a good timing.
0:54:22 But part of it is real.
0:54:25 I just walked over from Union Square, and there were definitely some homeless people
0:54:26 on the street.
0:54:29 In the green room, I gave London Breed a little bit of a hard time, you know, about why do
0:54:30 we allow this?
0:54:35 I think in some ways, I’m not a sociologist, but maybe all the wealth and success allows
0:54:40 a lot of sort of slack and allows them to get away with a lot of mismanagement.
0:54:44 I’m not signaling out her, anybody in particular, but I do think a lot of that government is
0:54:47 not managed as well as it could be.
0:54:51 They can get away with it because there’s just so much innovation and wealth being created
0:54:52 that you can have a lot of slack.
0:54:57 I’m hoping that will get tightened up a bit because it doesn’t reflect well on California
0:55:03 or on San Francisco, and with all the money being poured in to try to support San Francisco
0:55:04 in the Bay Area.
0:55:09 We should have the cleanest streets, the best police force, the safest neighborhoods, and
0:55:13 we don’t.
0:55:17 So if you were mayor for, you know, a month, I think I’d be a terrible mayor.
0:55:20 Economists do think differently about problem solving, right?
0:55:23 Well, a lot of them are probably just common sense, but a few of them, you know, where
0:55:27 economists may be different, like I’m a huge fan of congestion pricing.
0:55:30 Almost everyone who I know who is not an economist doesn’t think that’s a good idea.
0:55:32 But well, I guess some of these guys may be economists.
0:55:35 One of the first rules of taxation is you tend to get less of what you tax.
0:55:38 So if you’re taxing work and investment, you’re going to get less of that.
0:55:39 Why not tax pollution?
0:55:41 Why not tax congestion?
0:55:46 I also sometimes advise Singapore, and they’ve put it in place all these rules that economists
0:55:47 have.
0:55:48 Will you just slip that in?
0:55:49 You sometimes advise Singapore?
0:55:50 No, no.
0:55:51 Well, on Thursdays or what?
0:55:54 I’ve been there and met with senior officials, just like I meet with senior officials in
0:55:55 lots of different places.
0:55:57 I mean, not like an official advisor or anything.
0:55:59 Do you have a badge of some kind?
0:56:00 A badge?
0:56:01 No.
0:56:02 You have a cape?
0:56:03 No, no.
0:56:04 I am just a professor.
0:56:08 But what I like about Singapore is they listen to professors, and they don’t listen to professors
0:56:09 in the US Congress.
0:56:13 And that’s one of the reasons that they’re successful over there, I think I’m biased.
0:56:17 And one of the reasons so many people are leaving California is because it’s so expensive
0:56:18 here, and it doesn’t need to be.
0:56:22 And the reason it’s so expensive is because a lot of people would love to live here, but
0:56:26 the housing prices are insanely high because it’s supply and demand.
0:56:27 It’s elementary.
0:56:28 It’s economics 101.
0:56:33 These are things that are actually really easy to fix, and we could do a lot better.
0:56:37 I see why they call you the ever-powerful son of the armored wolf.
0:56:38 That was fantastic.
0:56:52 Eric Brynjolfsen, thank you so much.
0:56:57 I would like to thank Eric Brynjolfsen, Coleman Strumpf, and Mayor London Breed for joining
0:56:59 us on stage in San Francisco.
0:57:03 And I would especially like to thank the 1,500 folks who bought a ticket and came to hang
0:57:04 out with us.
0:57:10 If you want to see Freakonomics Radio Live, we have an upcoming show on February 13th
0:57:15 in Los Angeles with Ari Emanuel and other special guests.
0:57:19 Tickets are at freakonomics.com/liveshows, one word.
0:57:24 And if you liked hearing what Eric Brynjolfsen had to say about the impact of AI, be sure
0:57:29 to catch the next episode of Freakonomics Radio, where we will hear about a new technology
0:57:31 designed to thwart AI.
0:57:36 That’s right here in your podcast feed at our new time Friday morning.
0:57:42 Until then, take care of yourself, and if you can, someone else too.
0:57:45 Freakonomics Radio is produced by Stitcher and Renbud Radio.
0:57:50 This episode was produced by Abigail Lowenthal, Ellen Frankman, Morgan Levy, and Zach Lipinski,
0:57:53 with research help from Dalvin Aboagi.
0:57:59 Special thanks to Jesse McDaniel with Fresh AV, all the folks at Another Planet Entertainment,
0:58:07 the crew at the Sidney Goldstein Theater, and our partners SiriusXM and KQED Live.
0:58:11 The Freakonomics Radio Network staff also includes Alina Kulman, Augusta Chapman, Eleanor
0:58:16 Osborn, Elsa Hernandez, Gabriel Roth, Greg Rippin, Jasmine Klinger, Jeremy Johnston,
0:58:20 John Schnars, Neil Coruth, Sarah Lilly, and Theo Jacobs.
0:58:23 Our theme song is Mr. Fortune by the Hitchhikers.
0:58:25 Our composer is Luis Guerra.
0:58:32 Once again, thanks for listening.
0:58:37 I was able to get the Chinese government to commit to allowing San Francisco to host
0:58:38 pandas.
0:58:39 You went to China to get the pandas.
0:58:42 I went to China to get some panda bears.
0:58:49 It’s called panda diplomacy.
0:58:57 The Freakonomics Radio Network, the hidden side of everything.
0:59:00 [MUSIC PLAYING]
0:00:10 Every once in a while, we get out of our recording studio and take Freakonomics Radio on the
0:00:11 road.
0:00:16 We recently put on a live show in San Francisco at the historic Sidney Goldstein Theater.
0:00:19 If you were in the audience that night, thank you.
0:00:20 We had a blast.
0:00:21 Hope you did too.
0:00:25 If you were not there, this bonus episode is for you.
0:00:29 It is a recording of that show edited down to podcast length.
0:00:34 We have got another live show coming up in Los Angeles on February 13.
0:00:40 LA has been through so much with the wildfires, so much destruction and death and fear.
0:00:44 All of us who love that place are eager for its recovery.
0:00:48 And we are hoping to do our tiny part just by showing up.
0:00:51 A portion of our ticket sales will go to Relief Efforts.
0:00:53 I hope you’ll join us if you can.
0:00:58 You can get tickets at freakonomics.com/liveshows, one word.
0:01:01 It’s Thursday, February 13th, in Los Angeles.
0:01:05 One of our guests will be the inimitable Ari Emanuel.
0:01:10 Okay, here now is what happened in San Francisco.
0:01:12 As always, thanks for listening.
0:01:38 .
0:01:43 There are so many of you.
0:01:44 This does not seem like a fair fight.
0:01:47 There’s one of me and all of you.
0:01:55 I’m sure it’ll work out okay, but the hecklers begin.
0:01:59 So in case it’s not clear, this is not what we typically do.
0:02:01 I assume most of you know Freakonomics Radio.
0:02:07 You wouldn’t be here otherwise.
0:02:10 The show that we make is the opposite of a live show.
0:02:14 The show we make is really I’m a writer and it’s a writer’s show.
0:02:20 We come up with an idea, we do a bunch of research, we figure out what kind of people
0:02:25 to interview, then we prepare for the interviews, we do a lot of interviews.
0:02:30 We start to put together a script, a draft script, we rewrite it, we start to mix the
0:02:31 tape.
0:02:35 It takes many, many, many, many hours to make one episode and you know that’s the way we
0:02:36 like it.
0:02:39 At night, we’ve got like an hour and a half or two hours.
0:02:40 That’s it.
0:02:43 We have no pause button, we have no reconsideration.
0:02:46 It’s just us here together.
0:02:49 So if you’re up for that, I think we’re going to have a very good time together.
0:02:57 That’s the intention at least.
0:02:59 When I was a kid, I was very shy.
0:03:01 I still am, truthfully.
0:03:05 I had another problem in addition to shyness, which was that I really was curious.
0:03:07 I wanted to find out stuff.
0:03:11 In the old days, it took a lot of effort to find out stuff.
0:03:18 You’d have to go to the library or you would have to ask an adult and when you’re shy,
0:03:21 asking a stranger questions was not so easy.
0:03:27 My solution to all of that was to become a journalist, where you’re, okay, I’ve never
0:03:34 heard journalism applauded before, so thank you.
0:03:39 So becoming a writer, becoming a journalist, really solved both problems because all of
0:03:44 a sudden you have permission to ask anybody any question and you’re getting to find out
0:03:45 stuff all the time.
0:03:50 Now, in the old days, writing for newspapers and magazines and I wrote books for a while,
0:03:53 it was old fashioned fun, physical, analog labor.
0:03:59 You’d go out with people, might be writing a piece about one person over many weeks or
0:04:03 months, you’d follow them around, might be a whole scene and you’d come back after those
0:04:08 weeks or months with a whole bunch of cassette tapes that you would then transcribe yourself
0:04:09 as a writer.
0:04:10 That’s how you got to really know the material.
0:04:15 You’d come back with all these notebooks full of stuff and then you would sit down to sift
0:04:18 it and sort and write and I loved that.
0:04:20 I loved every single piece of it.
0:04:22 I still have all my notebooks.
0:04:24 I still have all those cassette tapes.
0:04:29 It was very, very labor intensive, but it was wonderful labor and my favorite part of
0:04:32 it was always just hanging out with the people.
0:04:37 A lot of it honestly was really boring, but the parts that were exciting were so exciting
0:04:38 when you really learned something.
0:04:43 It makes me think of what the physicist Richard Feynman, who’s been a hero of mine for a long
0:04:47 time, what Feynman called the pleasure of finding things out.
0:04:50 It was just so pleasurable that I never stopped.
0:04:56 What we do now with the radio show may seem different because it’s audio and yada yada,
0:04:58 but it’s really the same thing.
0:05:04 Coming up with ideas, putting yourself in position to have interesting conversations with people
0:05:10 who are smart or weird or maybe all of the above.
0:05:16 I think if we were to go back 20 or 30 years to when digital everything was really starting
0:05:23 to explode, I don’t know if any of us would have thought that we’d have so much communication
0:05:27 as we do and so little conversation.
0:05:34 I feel like because everyone is able to publish and be their own bullhorn, that in a way we’ve
0:05:38 sort of forgotten how to talk to each other.
0:05:45 By now I’ve probably interviewed, I don’t know, 5,000, 10,000 people in my life and
0:05:52 I can’t think of a single one where afterward I didn’t feel like my brain grew a little
0:05:55 bit or my heart grew a little bit.
0:05:59 It’s an unbelievably valuable human trait that we overlook, this ability of ours to
0:06:04 have language and have a conversation where we can learn about each other, move each other
0:06:05 and so on.
0:06:07 Really tonight, that’s what I want to do.
0:06:09 I just want to have some good conversations.
0:06:15 We’ve lined up some people I think are going to be excellent for you and me to hear about.
0:06:16 We’ll get started.
0:06:21 Does anyone have any complaints before we begin?
0:06:27 I get your emails, I know who you are.
0:06:29 We’re going to have some good conversations.
0:06:33 Our first one, I think you will enjoy quite a bit.
0:06:34 Would you please welcome our first guest?
0:06:41 She is the mayor of San Francisco, London Breed.
0:06:49 How’s things?
0:06:57 Well, freedom is fast approaching right now, so it’s almost like I dropped thousands of
0:06:59 pounds.
0:07:00 So you call it freedom.
0:07:04 For those who don’t know, you’ve got just a few days left.
0:07:06 You must have some wild s*** planned.
0:07:13 Oh, yes, pull out those phones because you guys are going to see a different mayor breed.
0:07:17 Let me start with, I hate to say it, a lot of people think of San Francisco as kind of
0:07:18 a failed state.
0:07:24 Not quite Haiti or Libya, but the stuff they see, they see the worst of the word.
0:07:25 That’s what the media does.
0:07:27 The media is really good at that.
0:07:30 And then it becomes a political weapon as well.
0:07:32 I mean, COVID was really hard.
0:07:38 You personally seem to have done the shutdown, handled that really well, aggressively, early
0:07:39 and so on.
0:07:41 But tell me how the city is recovering.
0:07:47 Well, it has been a rough ride, but I’m really excited about where we are now as a city.
0:07:52 The city has been more fun than it has been in a long time because you said more fun.
0:07:57 We have closed down streets to have night markets, first Thursdays, events, entertainment
0:08:01 zones, because we need some joy.
0:08:05 The city has been a place of no, you can’t do fun things.
0:08:10 And we turned it into a city of yes, we have helped over 20,000 people exit homelessness.
0:08:17 We have had a significant decline in our crime rate and one of the lowest homicide rates
0:08:18 since the 1960s.
0:08:23 I mean, this is the work that we’re doing, but we also know there’s more to be done.
0:08:24 It’s a major city.
0:08:29 Cities have challenges, but we are finally in a place where we build the capacity.
0:08:30 We change the laws.
0:08:32 We made the hard decisions.
0:08:34 And I just believe that the best is yet to come.
0:08:38 The biggest thing that we do struggle with is the perception.
0:08:42 So we need people to come to San Francisco or people who live here to tell their own
0:08:44 story of San Francisco.
0:08:49 So driving in, I mean, it’s a cliche, like, you know, you talk to a taxi driver, Uber
0:08:52 driver, you drive in from the airport, and I realize I’m not really seeing the city.
0:08:54 You didn’t take a waymo where you didn’t have anybody to talk to?
0:08:58 I have to say, I’m a little bit scared of the waymos so far.
0:08:59 How do you feel about them?
0:09:01 Well, it’s interesting.
0:09:07 They become a tourist attraction in our city, but you just said people do a lot of communication,
0:09:08 but not conversation.
0:09:10 So I don’t know if I’m going to take a waymo.
0:09:11 Because you want someone to talk to you?
0:09:12 I want somebody to talk to you.
0:09:13 Yeah.
0:09:14 All right.
0:09:15 Well, stick with me.
0:09:16 Okay.
0:09:21 I will say driving in from the airport, what I saw mostly were billboards for AI companies,
0:09:23 which I don’t see in New York.
0:09:28 And then I get to the tenderloin and I feel like I’m in a Hieronymus Bosch painting.
0:09:31 It is wild and it’s heartbreaking.
0:09:36 I know it’s been there forever and I know it predated you, but, you know, I just wonder
0:09:37 how much the perception hurt you running.
0:09:38 Okay.
0:09:40 Let me just ask the question I really want to ask.
0:09:41 Why did you lose?
0:09:43 You stood for reelection.
0:09:45 I’m going to say this with a lot of pride.
0:09:49 There was over $20 million spent on my race to unseat me.
0:09:50 Is this all Levi’s money?
0:09:53 I don’t know where the money came from, but there was a lot of money.
0:09:58 I think that things were not happening as quickly as people wanted to see them happen.
0:10:04 And that is something I take full responsibility for because this government and how bureaucracy
0:10:07 works, it is not designed to make things move quickly.
0:10:10 When you say bureaucracy, do you mean mostly the board of supervisors?
0:10:15 I think I do mean a lot of the board of supervisors.
0:10:16 And now this new mayor is getting a good board.
0:10:20 I’m just so mad about it.
0:10:23 People say, oh my goodness, your response to the pandemic was amazing.
0:10:26 And yeah, it’s because we cut bureaucracy.
0:10:32 We had emergency authority to make decisions without the bullcrap that gets in the way
0:10:35 of trying to make things move.
0:10:39 And then we go back to a post-pandemic world after we come out of that.
0:10:45 We needed to be able to act quickly, dealing with the rise in fentanyl overdose tests and
0:10:48 the emptying of our shelter beds and the need to build more houses.
0:10:53 We had all these things we needed to do and could not move fast enough.
0:10:58 And the good news is we work very hard to build our capacity to make the necessary changes,
0:11:03 to use technology, and to really help combat these issues.
0:11:07 And think about it, our crime rates have consistently been dropping.
0:11:11 I mean, even car break-ins are lower than 10,000.
0:11:13 And this is a major city.
0:11:14 It hasn’t been that low since 2015.
0:11:19 Let’s talk about the major city thing, because I come from New York.
0:11:20 And things happen.
0:11:22 Things happen in all major cities.
0:11:26 But that’s my problem is I don’t think of you as a major city.
0:11:36 I think of you as a very, very nice…
0:11:39 Now you understand why I don’t do this live thing.
0:11:44 But don’t you think of San Francisco as a major city?
0:11:50 Okay, Stephen, you better watch out what restaurant you eat in.
0:11:52 Somebody might put something in your food.
0:11:57 Well, that’s not a nice way to make friends with the out-of-towners.
0:11:58 But no.
0:12:00 But where was I now?
0:12:03 Major city, I’m going to skip that question.
0:12:05 You lost some population during COVID.
0:12:10 I did read you say something about how you had fewer people die here per capita than
0:12:12 any other big city in America.
0:12:16 But I was wondering, okay, but wait a minute, wait, save you applause because you’ll boom
0:12:17 in a second.
0:12:23 But I wondered if that’s just because everybody left and they were dying elsewhere.
0:12:25 Listen, let me just say this.
0:12:26 We shut down early.
0:12:29 We made really hard decisions.
0:12:30 It was not easy.
0:12:34 And the people in San Francisco really came together to try and save lives.
0:12:38 I was really proud of how people went grocery shopping for folks.
0:12:43 Folks showed up to work in the hospitals and people sacrificed to make that happen.
0:12:44 And so I’m very proud of that.
0:12:49 A lot of people did leave and they were talking a lot of crap when they were leaving San Francisco.
0:12:51 But you know what?
0:12:58 Many of those people are back because this is $34 billion in venture capitalist investment
0:13:02 of the top 20 AI, artificial intelligence companies in the world, eight are right here
0:13:09 in San Francisco, 5 million square feet of office lease sign in San Francisco, 70% of
0:13:13 the new office space is by new companies in AI.
0:13:17 People are coming back to San Francisco because they know this is where they’re going to
0:13:21 be successful despite what people try to say about the city.
0:13:23 It is still where people want to be.
0:13:24 I’m really glad to hear that.
0:13:29 I do love your city by saying I didn’t think it was a major city mean to imply that I didn’t
0:13:30 love it.
0:13:31 But it has less than a million people.
0:13:32 So I totally understand that.
0:13:33 This makes me think.
0:13:39 I live in New York and we lived there during the 9/11 attack and it was scary, very different
0:13:40 event obviously in COVID.
0:13:44 And I have a sister who lives in Buffalo who called us up and she was very worried about
0:13:45 our family.
0:13:49 She said, Steve, you know, you should really pick up and my kids were very young, pick
0:13:51 up and move to Buffalo.
0:13:52 And I didn’t even think it was so terrible what I said.
0:13:59 I said, Beth, you know, I’d rather die in New York and live in Buffalo.
0:14:04 And to be fair, Buffalo is a wonderful major city.
0:14:05 So let me ask about you.
0:14:09 You grew up hard in public housing, raised by your grandmother.
0:14:10 All kinds of stuff around.
0:14:11 There was crime.
0:14:16 There was drugs, your own family suffered from all that.
0:14:20 And the thing that I really want to know about you, you know, we have this idea when there
0:14:25 are people in the public eye, we just think they’re invincible.
0:14:30 Everybody always has challenges and it’s how they overcome them that really defines us.
0:14:38 So with you, I can’t figure out how you got to where you got with the odds that you faced.
0:14:44 And I’m not asking you for advice necessarily or if you have a superpower, but can you just
0:14:50 describe what it took not just to survive, but to thrive with those barriers.
0:14:52 There are so many different things that happen.
0:14:56 Last time when we talked on the podcast, I talked about my brother who’s incarcerated
0:14:59 and how we both went to the public school system.
0:15:02 He didn’t even graduate from high school and I did.
0:15:07 It’s hard to finger point where the issue happened, but I feel really honored and grateful
0:15:14 to God for just the strength to overcome so many of those obstacles and to get my education
0:15:20 and to want to go back to the community and make a difference.
0:15:21 Obviously you worked hard.
0:15:26 Obviously you were disciplined and all that, but how much do you think is just temperament?
0:15:31 I don’t know if I would say that I have the best temperament because I have a temper, but
0:15:36 I will say that I have remained true to who I am as a person.
0:15:41 But the whole reason why I got involved in public service in the first place is because
0:15:49 a violent crime in my community where people were dying, where our homicide rates were significant
0:15:57 in the 90s and it is just amazing to see us in a better place than we’ve ever been before.
0:16:01 And I have always said it is always the will of the voters that I’m going to respect and
0:16:10 be grateful that I had the opportunity to serve.
0:16:14 Do you feel that you were treated differently than the mayors who came before you who came
0:16:16 from more traditional backgrounds?
0:16:19 I think so a little bit, yeah.
0:16:23 I didn’t talk about it much, but when the mayor calls you and not return the mayor’s
0:16:29 call, that was pretty offensive or to sit in a meeting with me and to look at my chief
0:16:32 of staff and talk to him and not talk to me directly.
0:16:34 How do you handle that in the moment?
0:16:37 In the moment, I’m like, hi, I’m right here.
0:16:42 Nice smile and I’m the one who makes the decision and then I move on from it.
0:16:46 I didn’t come from money, I come from the hood, I didn’t have built-in relationships
0:16:52 with a lot of these people, but I did do what I could to try and reach out to people and
0:16:56 develop those relationships and make sure that my door was always open.
0:17:00 So even if someone opposed me, which, you know, I had a member on the board of supervisors
0:17:03 who was just the worst person to work with.
0:17:04 That person’s name was what again?
0:17:11 Well, here’s the interesting part is somehow once that person decided they wanted to work
0:17:16 with me, we developed a tight, really good working relationship.
0:17:21 And so what I’ve always said is, look, I may not like you, I don’t have to like you, but
0:17:22 I will work with you.
0:17:24 I’ve heard you say that.
0:17:25 I really like that.
0:17:30 I want to steal that because I think most of us, it’s hard to do when you don’t like
0:17:33 someone, but you need to work productively with them.
0:17:34 So what do you do?
0:17:35 Do you picture him?
0:17:36 Nate, what do you do?
0:17:43 No, I just think when I wake up in the morning, I’m the mayor of San Francisco.
0:17:51 Like I’m the mayor of San Francisco.
0:17:52 So come right in.
0:17:57 Look, sometimes it shows on my face, but I’m a grown up here.
0:18:03 And I have to be better than somebody who’s petty because you don’t particularly care
0:18:04 for someone.
0:18:09 I mean, you know what’s in your head, but the business of the people is the most important.
0:18:13 I can’t just support or work with the people who voted for me.
0:18:17 I can’t just talk to the people that I want to talk to.
0:18:22 And it’s what anybody in elected office should be if you are here for the right reasons to
0:18:24 get the business done for the people.
0:18:29 And I’ve been able to accomplish a lot because I’ve always kept the door open.
0:18:34 As we speak, you have a few days left in office, and I want to know what you’re planning next
0:18:35 if you have plans.
0:18:40 And I also want to know the Democrats got crushed this year coast to coast.
0:18:44 And there’s an election in about a month from now for DNC chair.
0:18:47 Was that something that you’ve poked around at by any chance?
0:18:55 So under the law, I can’t look at other opportunities until I actually leave office.
0:19:02 And so I will be having a lot of meetings once I leave office because I need a job.
0:19:07 Let’s just pretend that you’re elected DNC chair in a month, whatever it is.
0:19:12 What would you say, considering the shellacking that the party had, what’s the thing or two
0:19:17 that you think the Dems need to do to put themselves in position to win some more elections?
0:19:22 I think that the biggest thing we need to do is cultivate young, new talent.
0:19:25 I mean, my race is a perfect example.
0:19:31 I am a perfectly capable, qualified Democrat who runs a major city.
0:19:38 And when you have young Democrats, you guys like that, huh?
0:19:43 When you have people in these various positions, whether it’s mayor or board of supervisors
0:19:51 or other places, we have to invest the resources into helping to grow our talent pool to ensure
0:19:53 that we have a pipeline.
0:19:55 Do you think the Republicans have done that well?
0:20:00 Or do you think that they’re, because look, Trump is no one’s idea of an ideal candidate.
0:20:03 And yet one by a lot, you could read that a few ways.
0:20:06 A lot of people like Trump a lot, which is plainly the case.
0:20:10 And or the Democrats were really unpopular.
0:20:13 I’m just curious, and I know you faced it yourself.
0:20:15 Your far left hit you very, very hard.
0:20:19 You had to deal with a lot of things as ultimately a centrist Dem.
0:20:24 So I’m just wondering if the big tent needs to be reconfigured for the Dems.
0:20:26 I think that the tent needs to be open.
0:20:28 Again, I come from nothing.
0:20:33 So I’ve only mostly volunteered and helped people in their campaign.
0:20:35 So it’s significant that I’m mayor.
0:20:41 So how do we capitalize on that in order to ensure that people like me don’t get lost
0:20:48 by the party, but really does start with, how do you get more people choosing to register
0:20:51 as a Democrat rather than decline to state?
0:20:53 How do you feel about open primaries?
0:20:58 I would be open to it, but I’m not 100% sure that that’s the right route to go.
0:20:59 Because why?
0:21:00 What’s the advantage?
0:21:03 I mean, there are a lot of good arguments for why a two-party system is not as bad as
0:21:04 we always say it is.
0:21:08 Because when you look at the alternatives, there are many countries with five, 10 parties
0:21:11 and they’re in worse chaos, honestly.
0:21:15 I mean, it’s politics and you got to remember politics is never going to be nice and wrapped
0:21:16 into a neat little bowl.
0:21:18 It’s going to be something you have to fight for.
0:21:23 The reason why I struggle with the open primary has a lot to do with, I want to see the Democrats
0:21:30 united and I want us to do the work to get behind the candidate, whether we agree with
0:21:35 that person or not to really fight for that candidate and also to listen to people as
0:21:38 to why they might want something different.
0:21:42 We may see something or hear something and we say, “Oh, they don’t know what they’re
0:21:43 talking about.”
0:21:45 But you know what?
0:21:50 If you listen closely and you hear what they’re saying, you have to think about, “Well, how
0:21:55 do we appeal to the people who we believe may not know what they’re talking about?”
0:22:00 I just think you have to be a little bit more open-minded and not just toss someone to the
0:22:06 side just because their beliefs aren’t 100 percent of what you think our value system
0:22:12 should be because clearly we got a lot of work to do and we have to understand all those
0:22:15 different states differently than we have in the past.
0:22:17 That’s really, really nicely said.
0:22:20 Congratulations on your career, everything.
0:22:24 Thank you for coming out tonight.
0:22:29 We will be back with more from our live show in San Francisco right after this.
0:22:41 Okay, back now to our recent live show in San Francisco.
0:22:46 All right, I’m having a good time.
0:22:47 Are you?
0:22:53 Are we okay?
0:22:58 You may be wondering why we are here at this big theater in San Francisco on this rather
0:23:00 awkward date.
0:23:02 It’s January 3rd, I guess.
0:23:08 Nobody does events this week, the week of New Years, but we’re here because this week
0:23:14 in San Francisco is the annual meeting of the American Economics Association.
0:23:20 The AEA is, as you can imagine, it’s a huge gathering of economists from all over the
0:23:25 world and it really is as exciting as that sounds.
0:23:29 And then you ask, “Well, why would they hold it now in the week of New Years when everything
0:23:32 is dead, everybody’s traveling and so on?”
0:23:39 And the reason is because economists are really cheap and when they’re booking these conferences
0:23:45 every year in a different city, they want the cheapest week for the hotels and the conference
0:23:50 center and therefore they hold it immediately after New Years.
0:23:58 And so when we heard it was coming to San Francisco this year, major city, we decided we go to
0:24:03 these AEA conferences to scout stories and to see our economists friends and to look
0:24:07 for new economists friends for the sake of Freakonomics Radio and so on.
0:24:10 But then we also decided this year, because we would be in a major city, that we would
0:24:13 put on this live show at the same time.
0:24:19 So we had the mayor, which is fantastic, but we have another couple of guests that we were
0:24:24 able to wrangle because the AEA was here.
0:24:26 We’ve got two more economists to come.
0:24:27 Let’s welcome the first one.
0:24:31 Please give a warm hand to Mr. Coleman Strumpf.
0:24:38 Coleman, come on out.
0:24:40 [applause]
0:24:46 Coleman, here are a few things I know about you.
0:24:51 As a kid, you got into trouble bringing candy bought at retail to school and selling it
0:24:53 at a very high markup, correct?
0:24:54 Yep.
0:24:55 My introduction to crime.
0:24:58 Introduction to crime or introduction to thinking like an economist?
0:24:59 Maybe they’re not so different.
0:25:00 Maybe they’re not so different.
0:25:02 I’ve been saying that a long time.
0:25:03 Nobody believed me.
0:25:09 I also know that as a child, you appeared in a TV commercial for Tang, the astronaut beverage,
0:25:10 is that true?
0:25:16 I, in fact, did with the rest of my family and I only say if you spend a whole day drinking
0:25:20 Tang, if you even know what that is, you will not feel so good the next week.
0:25:21 All right.
0:25:25 You’re now an economist at Wake Forest and most of your research that I’m familiar with
0:25:31 at least has been about what I would characterize as illicit and taboo activities.
0:25:34 Would you name a few that you’ve looked into over the years?
0:25:35 Yeah.
0:25:40 Sports betting, not the stuff you do on your phone, but the guy in the corner.
0:25:45 I’ve done some work on cannabis, which we might talk a little bit more about.
0:25:46 File sharing.
0:25:49 File sharing like stealing digital products.
0:25:51 You’re an empirical economist.
0:25:52 You work with data.
0:25:55 How do you get the data when you’re dealing with illicit goods?
0:25:56 It’s not as hard as you’d think.
0:25:58 I’ll tell you about sports betting.
0:26:04 I was very interested in sports betting and I one time went to Las Vegas, which was about
0:26:08 the only place you could do sports betting and I tried to wrangle up with one of the
0:26:09 bookmakers.
0:26:13 I was like, “Can you give me some information about what you guys do?”
0:26:15 And he laughed at me.
0:26:21 So maybe as a way of getting revenge on the guy, I ended up making a friend in Brooklyn’s
0:26:26 district attorney’s office and now I have a bunch of records on illegal bookmakers.
0:26:31 So I still don’t know a lot about what the guys in Las Vegas do, but I can tell you about
0:26:32 a lot of guys in New York.
0:26:34 So you blackmail people essentially, huh?
0:26:36 I get a little revenge.
0:26:40 The reason I wanted to have you on the show tonight is you appeared in an episode we made
0:26:46 back in I guess the fall, not long before the election talking about betting markets, prediction
0:26:52 markets which are sometimes the same as betting markets, some legal but mostly kind of illegal.
0:26:54 Also you helped us out with a later episode.
0:26:58 We did a series on the economics of cannabis and you had a lot of data that nobody else
0:27:02 had about legal and illegal weed shops.
0:27:09 How can you tell an illegal from a legal weed shop, let’s say in California, other than
0:27:13 maybe you go sample door-to-door, I don’t know how that works?
0:27:18 Those of you who in the audience who are interested in cannabis might know a website.
0:27:22 Should we turn the house lights on and have a show of hands or something?
0:27:28 You might know an app called, you might know an app called Weed Maps.
0:27:32 Those of you who have never used it, it’s maybe like Yelp for pot.
0:27:35 Fired up on your phone, put on the GPS, tells you all the stores near you.
0:27:41 So I saw this app and I said, hmm, it’d be kind of cool if you could just get everything
0:27:44 that’s on that site and stockpile it.
0:27:49 And if you spend a little time kicking around in the background, you can figure out a way
0:27:50 of doing that.
0:27:55 So I always have a lot of computers running and a bunch of computers for several years
0:27:57 just pulling stuff off this site.
0:28:00 So I have a list of all the stores.
0:28:04 Now how do I know who’s legal and how do I know who’s illegal?
0:28:08 So the state of California publishes a list of the legal stores.
0:28:12 So I could start using that, but the information’s a little bit incomplete.
0:28:19 So I had to look at different online sources, including Google Maps to see stores magically
0:28:25 turning from a kid’s store into a weed store in Los Angeles and you can kind of figure
0:28:29 out through a lot of sweat, which ones are legal and which ones are not.
0:28:33 Now when they’re listed on the site, whether it’s the weed map site or the California data,
0:28:35 there’s a license number, I assume, right?
0:28:37 That’s what makes a legal shop legal.
0:28:39 Do the illegal shops just make up a number?
0:28:44 Yeah, they either make up a number, go down the street, look at the legal store, take
0:28:46 a picture of that and use that number.
0:28:50 Or sometimes they just put up stuff that isn’t even a valid number.
0:28:55 Now the thing that blows me away is when in a place like California, let’s take LA versus
0:28:56 San Francisco.
0:29:01 In LA, you told us something like 70% of the weed shops are illegal.
0:29:03 So can you explain how the economics of that works?
0:29:05 Why do they proliferate?
0:29:09 Obviously, it’s cheaper because you’re unlicensed, but why are they allowed to proliferate?
0:29:11 Yeah, that’s a great question.
0:29:16 There’s not a lot of, I guess, will among policymakers to do it.
0:29:21 The people who would be doing the enforcement, the police, think about how hard this job
0:29:22 is.
0:29:27 If I say, arrest people who are doing some activity, well, I just see somebody doing
0:29:28 this activity.
0:29:35 Now you need to say, not just as somebody selling cannabis, but as somebody who’s licensed
0:29:36 or unlicensed.
0:29:37 They’re literally doing the exact same thing.
0:29:40 Some people are doing it legally, some people are not doing it.
0:29:41 It’s not so easy.
0:29:46 But I would imagine that, let’s say you and I teamed up and we said, you know what, alcohol
0:29:50 is pretty cheap to make, if you think about it, just to ferment some stuff and you put
0:29:56 it in a bottle, then you brand it, and then you can sell it for like 20, 30, 50, 80, $100.
0:29:58 And we know there’s a lot of tax associated with that.
0:30:02 So let’s say that you and I could either fake it or get the real stuff a little bit cheaper
0:30:06 and just open a liquor store without having to pay any of the taxes and regulation stuff.
0:30:08 Why do we never see that?
0:30:13 In the wake of prohibition, actually, you did see things like that for 15 years.
0:30:19 Through the 1950s, you would have lots of arrests of people having illicit stills and
0:30:20 things of that sort.
0:30:25 Today, in cannabis, the illegal people are pretty sophisticated.
0:30:30 So one of the things in this weed maps data I have is I have a list of all the products.
0:30:31 What are some of your favorites?
0:30:33 Well, I like to observe.
0:30:36 Honestly, I’m a little out of date on them.
0:30:37 Is that true?
0:30:38 Yes.
0:30:39 You’re not a big…
0:30:40 I took you for a big…
0:30:41 Yeah, I definitely have that.
0:30:42 Yeah.
0:30:44 But at any rate, so I am familiar with some of the big brands.
0:30:47 The good news is, apparently Tang is not a gateway drug then.
0:30:48 Yeah, right.
0:30:53 Well, maybe it’s a gateway drug to being an economist, but I don’t really know.
0:30:59 But at any rate, if you’re wanting to sort of pretend you’re running a legitimate place,
0:31:02 you’ll take a name brand and you’ll just switch a letter.
0:31:06 And they literally get old containers or wrappers from legal stuff, and they’ll put
0:31:08 it around the legal stuff.
0:31:13 Also, one thing you told us was that in San Francisco, there are many fewer illegal shops,
0:31:15 which has to do with the way that they run their programs.
0:31:18 So I don’t know if Mayor Breed had anything to do with setting up that program.
0:31:22 We actually interviewed the guy who did that, but something like 20% of the shops here are
0:31:25 illegal versus LA about 70, right?
0:31:26 That’s what your data says.
0:31:30 Yeah, and these are from a few years back, but I would say the number is probably still
0:31:31 about holding.
0:31:37 But I would think that the illegal shops benefit further by having legality because that drives
0:31:40 the price up with the licensing and it makes their stuff, which might be identical, much
0:31:41 cheaper, yeah?
0:31:44 And on top of that, there’s the social norm.
0:31:49 I live in North Carolina where it’s not so different from what I remember growing up.
0:31:55 In New York, in San Francisco, all California, the norm about how acceptable is cannabis
0:31:59 as a thing to be using, much more accepted today than it used to be.
0:32:01 And it’s going to spill over to the illicit side as well.
0:32:05 So I would argue demand is probably much higher.
0:32:06 We could talk a long time about cannabis.
0:32:08 It’s a very interesting economy.
0:32:10 Also, the elections this year were interesting.
0:32:14 It got voted down in Florida, I think North and South Dakota.
0:32:18 But it’s interesting that we’re talking about what people used to call vices, right?
0:32:23 It’s betting, but it’s now mostly legal in the US, cannabis, mostly legal in the US.
0:32:26 What about betting on elections?
0:32:27 You know a lot about that.
0:32:33 Do you think that will become fully legal in the US in the next, you know, five, 10 years?
0:32:37 I usually, when I try to make a forecast, I look at these markets to answer the question
0:32:40 rather than try to answer it on my own.
0:32:46 Things look pretty promising, but everything is going to be governed by what a judge will
0:32:48 maybe say about these things.
0:32:51 There was a lot of enthusiasm about these markets this time.
0:32:54 They did a pretty good job at forecasting the election.
0:32:57 You argue they do, on average, better than polling.
0:32:58 Yes.
0:32:59 Yeah, definitely.
0:33:03 There’s a fundamental difference between polls and these markets.
0:33:07 The way a poll works, which is probably what most people in the audience are familiar with,
0:33:14 is you talk to a bunch of people, the representative of all voters, and you see what they’re thinking.
0:33:16 These markets are supposed to work in a totally different way.
0:33:21 You could step outside your own experience and say, look, my goal presumably is to make
0:33:23 some money at forecasting the election.
0:33:26 Well, that has nothing to do with what I think in terms of who I like.
0:33:29 I’m trying to guess what other people like.
0:33:31 Where’s the information coming from?
0:33:32 Everywhere and anywhere.
0:33:33 Right.
0:33:35 So why would it, on average, be more accurate than polling?
0:33:39 Look, we’ve learned this election and past elections that many pollsters are just not
0:33:40 very good.
0:33:41 Let’s be honest, right?
0:33:45 It’s not a particularly scientific science, if you want to call it that.
0:33:50 But still, why would they who are setting out to do one thing in a very binary way?
0:33:55 I ask a bunch of people, this candidate or that candidate, why would they not be better
0:34:02 than a group of people who are looking to profit from feeling they know a piece of information?
0:34:06 This election was probably the best case example I could give of that.
0:34:12 So when people are polled about certain candidates, they tend not to always say who they support.
0:34:18 So traditionally, Donald Trump underperforms and polls.
0:34:19 David Dinkins.
0:34:22 I don’t know if you remember this in New York City, the first black mayor of New York City.
0:34:23 He over polled by a lot.
0:34:29 A lot of people wanted to be seen saying that, yes, I will vote for the first African-American
0:34:30 mayor.
0:34:31 Right.
0:34:35 So let me tell you about the person who was the most successful better in 2024, who was
0:34:37 a French citizen.
0:34:38 He had a very similar view.
0:34:41 He said, I don’t think these polls are working very well.
0:34:44 But I’m going to run my own poll.
0:34:50 And so he asked a slightly different question, which was not who do you support?
0:34:52 Who do you think your neighbors support?
0:34:57 There’s a little bit of work that suggests that people are a little bit more realistic
0:35:00 about thinking about that question than what they themselves think.
0:35:06 Anyway, he was so confident in what he found from this poll that he put down $80 million
0:35:08 on Donald Trump to win.
0:35:11 And yeah, he made $80 million.
0:35:17 Does this suggest that pollsters next time around will basically emulate that methodology
0:35:22 of asking a question that’s not so binary, it’s not so, what are you going to do?
0:35:26 I’m pretty skeptical of pollsters getting into the 21st century.
0:35:31 Like the writing’s been on the, like, forget about what I’ve just been saying.
0:35:36 Being a pollster is infinitely more difficult today than it was 40 years ago.
0:35:37 Absence of landlines.
0:35:38 Yeah.
0:35:43 I don’t know who’s calling, and my phone doesn’t equate to where I physically am.
0:35:45 It’s just very hard to do polls.
0:35:51 The kind of advancements that they’ve made are relatively marching, in my opinion.
0:35:57 The thing that most surprised me about your work talking to you is how the betting markets
0:36:04 on elections have been around for a long time and have been accurate for a long time and
0:36:05 have been robust for a long time.
0:36:09 Do you know anything about San Francisco history?
0:36:15 San Francisco definitely had their own markets, many of which were relatively big money, millions
0:36:17 of dollars in today’s dollars.
0:36:21 They would take place in like cigar stores and things like that.
0:36:23 We’re talking 1900, a long time ago.
0:36:27 Some people had money, but a lot of people didn’t have money, but there were fewer things
0:36:29 to bet on back then.
0:36:32 So people were really into betting on elections.
0:36:34 And so they would do these non-monetary bets.
0:36:37 If you didn’t have the cash, they call them freak bets.
0:36:38 I don’t really…
0:36:39 Freak?
0:36:40 Freak bets.
0:36:41 I don’t…
0:36:42 F-R-E-A-K?
0:36:43 As in a certain book that I’m familiar with, yes.
0:36:44 I like the sound of that, yeah.
0:36:47 At any rate, they did all sorts of crazy things.
0:36:51 It was, “I won’t shave for the next 20 years.
0:36:53 I’ll walk halfway across the country.”
0:36:54 And these are documented somewhere?
0:36:57 Yeah, these are all at least newspaper stories.
0:37:03 And my favorite San Francisco story that I saw was in 1916, which was a very tightly
0:37:05 contested election.
0:37:06 Two people…
0:37:07 1916?
0:37:08 1916.
0:37:10 So this is Woodrow Wilson getting reelected.
0:37:15 And two people were betting, and the loser had to get dressed as a woman.
0:37:16 Okay.
0:37:17 These were two men.
0:37:18 In public and private?
0:37:20 In public and within a mile of here.
0:37:21 And go out and parade around?
0:37:22 And they would parade around.
0:37:28 And so this one guy did, apparently it was not legal to dress as a woman at that point
0:37:29 in time.
0:37:33 This guy got arrested, and then his friends came and bailed him out, apparently.
0:37:36 So for losing the bet, he had to dress as a woman, and because it was illegal to dress
0:37:38 as a woman, he was arrested?
0:37:39 He was arrested.
0:37:40 Wow.
0:37:41 Wow.
0:37:42 Prime really does not pay.
0:37:43 That’s brutal.
0:37:44 No.
0:37:45 When was cross-dressing illegal until?
0:37:47 In San Francisco, I think 40 years ago.
0:37:48 Really?
0:37:49 And that’s San Francisco?
0:37:50 Yeah.
0:37:51 Yeah.
0:37:52 Major City.
0:37:53 All right.
0:37:55 Well, Coleman, thank you.
0:37:56 It’s always great to talk to you.
0:37:57 Great.
0:37:58 Thanks.
0:38:06 This is Stephen Dubner, and you were listening to a Freakonomics Radio show.
0:38:09 We recorded live in San Francisco on January 3rd.
0:38:20 We will be right back with our final guest.
0:38:22 We have one more guest tonight.
0:38:29 He is an economist at a nearby school called Stanford, I believe it’s pronounced, which
0:38:36 please welcome Eric Brynjolfsson.
0:38:47 Okay, I’m very fond of this man, very, very interesting and bright fellow.
0:38:53 So Eric, it says that you are a senior fellow at the Stanford Institute for Human-Centered
0:38:54 AI.
0:38:55 Is that correct so far?
0:38:56 So far, so good.
0:39:00 And you’re also director of the Stanford Digital Economy Lab.
0:39:01 So I just want to know what both of those are.
0:39:04 I want to know what a human-centered AI is, honestly.
0:39:06 Well, that’s a good question.
0:39:11 Fei-Fei Li started it along with Jonathan Chimendi, and they recruited me out to Stanford.
0:39:12 You were MIT?
0:39:15 Yeah, I was at a major city in Massachusetts.
0:39:19 You’re picking bones with me, because that is the other city that thinks it’s a major
0:39:20 city.
0:39:22 Well, I’m sorry, it keeps…
0:39:26 It’s too bad we keep feeding New York in all the sports, but that’s just the way it goes.
0:39:28 You know, here’s the thing about New York in sports.
0:39:32 When you’re a major city, the sports don’t really matter that much.
0:39:33 Good.
0:39:35 Yeah, you can cope.
0:39:40 So the idea is that AI is doing these amazing things, but we want to do it in service of
0:39:44 humans and make sure that we keep humans at the center of all of that.
0:39:48 A lot of technologists are very focused on the technology, but I’m an economist, as you
0:39:53 mentioned, and they’re political scientists, sociologists, artists, and we’re all working
0:39:59 to use AI to help lots of the other parts of the world and of academia.
0:40:04 When you talk about human center, I mean, one thing that comes to my mind is labor, right?
0:40:05 Yes.
0:40:08 You and I have had this conversation on the show for probably eight or 10 years now about
0:40:15 to what degree does automation and AI mean job replacement, and if so, how big a problem
0:40:16 is that?
0:40:20 But you’re talking about more than just machines doing human jobs.
0:40:26 You’re talking about having AI or having technologies that let humans be human in their most essential
0:40:27 way or what?
0:40:28 Totally.
0:40:31 Too many people think of machines as just sort of trying to imitate humans.
0:40:35 There’s this iconic test of artificial intelligence called the Turing test that many people are
0:40:39 familiar with, which is how much can you make a machine mimic a human to the point where
0:40:41 you can’t tell which is which.
0:40:46 That was, I think, a visionary idea when Alan Turing proposed it in 1950, but in a way,
0:40:50 it’s a very constraining idea because machines can help us do new things we never could have
0:40:55 done before, and that’s a much higher ceiling, and so we want to look for ways that machines
0:40:59 can complement humans, not simply imitate or replace them.
0:41:03 I wrote a paper recently called The Turing Trap trying to steer people away from this
0:41:06 idea of just imitating humans.
0:41:12 If we were having this conversation a year ago about AI generally, the first five questions
0:41:16 would be, “So, are the machines going to wipe out humanity?”
0:41:20 Now, it’s not that nobody’s thinking about that and concerned about it anymore, but
0:41:22 it’s no longer the conversation.
0:41:24 Why is that?
0:41:26 I think it’s still part of the conversation.
0:41:27 I don’t know.
0:41:30 Maybe in the press, there’s things that go up and down in cycles to some extent.
0:41:32 AI is becoming much more powerful.
0:41:36 There continues to be rapid progress, and the good news is we can have tremendously
0:41:43 higher productivity and wealth and have medical solutions addressing poverty in the environment,
0:41:50 but it also raises a number of risks, misinformation or people using it in a way that creates weird
0:41:55 interpersonal dynamics, AI boyfriends and girlfriends, maybe millions of those that people have as
0:41:59 their primary relationship, pathogens, and even catastrophic risks.
0:42:02 Say more about pathogens in AI.
0:42:08 The great thing is AI can help us discover new drugs, as well as new materials.
0:42:13 There’s just a study from a grad student at MIT describing how researchers using AI were
0:42:19 able to discover 44% more materials than a randomly assigned group that didn’t have
0:42:22 access to the technology, so a big difference.
0:42:24 Some of those new materials, lots of them can do good things.
0:42:27 You can also create dangerous ones.
0:42:31 You can flip the bit on a drug that’s meant to make you healthier, and it can make you
0:42:35 much less healthy to the point of killing you.
0:42:37 You know a lot more about this than most of us do.
0:42:39 You’ve come at it from a variety of angles.
0:42:44 We’ll talk about the economic angle in a little bit, but would you call yourself generally
0:42:45 a techno-optimist?
0:42:48 I’d say I’m a mindful optimist.
0:42:51 What I mean by that is that they’re sort of blind optimists.
0:42:54 I run into a lot of those in Silicon Valley who are just like, “Hey, don’t worry.
0:42:55 Just chill.
0:42:57 It works out in the past.
0:42:58 It’s going to be great.
0:43:00 Just sit back, and we’re going to have a great time.”
0:43:03 There’s a lot of pessimists who basically say the opposite.
0:43:07 They both make the same mistake, I think, which is they take the agency away from us.
0:43:11 This technology is going to do stuff to us, and whatever it is is what it is.
0:43:13 I think that we have a lot of choices.
0:43:18 One of the reasons I came to Stanford, the Center for Human-Centered AI, is that I think
0:43:23 we can help steer the technology in ways, and if we do it right, we could have the best
0:43:26 decade we’ve ever seen, but it’s not inevitable.
0:43:27 Okay.
0:43:29 But we’ll call you a mindful optimist is what you say.
0:43:30 Thank you.
0:43:32 Do you know much about what they call nominative determinism?
0:43:33 Have you ever heard that phrase?
0:43:34 No.
0:43:39 It’s the idea that your name, your very name has some effect.
0:43:41 That sounds like a good Freakonomics chapter.
0:43:45 We wrote a chapter about names that almost everybody remembers wrong.
0:43:47 We wrote that there is no such a thing.
0:43:48 Mr. Baker is a baker.
0:43:49 Yeah, exactly.
0:43:53 My name is Stephen Baker, and I open a bakery, or my name is Dennis, and I become a dentist.
0:43:54 And so on.
0:43:57 But there are people who believe that, but with you, I got to thinking.
0:44:01 I looked up the etymology of your name, Eric Brynjolfsson.
0:44:07 The internet tells me the last name is an Icelandic patronymic, son of Brynjolf.
0:44:13 With Brynjolf broken into Bryn, which means armor, and jolf meaning wolf, so son of the
0:44:19 armored wolf, and then Eric usually translates to eternal ruler or ever powerful.
0:44:23 So you are the ever powerful son of the armored wolf.
0:44:28 Do you think that’s why you’re an optimist?
0:44:29 That would make sense.
0:44:34 That’s what people, when I go to Iceland, that’s how people know me.
0:44:35 It’s true.
0:44:40 I’ve heard you talk in the past about, as I understand it, essentially a new way of
0:44:43 measuring our economy.
0:44:46 You call it GDPB, so I want you to tell us about that.
0:44:48 I want you to tell us what the B stands for.
0:44:51 But I want you to start at the beginning, because many people, even people who have
0:44:57 nothing to do with economic sync, GDP is a highly imperfect measure of what we want it
0:44:58 to measure.
0:45:01 And if I recall correctly, I don’t know much about this, but I’m sure you do.
0:45:06 But the inventor of Simon Kuznetz, when he created GDP, warned that it should not be used
0:45:08 for essentially what we’re using it for.
0:45:09 That’s exactly right.
0:45:14 Simon Kuznetz, with his team in the 1930s, basically developed what we now use as our
0:45:18 national accounts, GDP, productivity is all based on the system of accounts.
0:45:22 Paul Samuels, one of the greatest inventions of the 20th century, I agree, but it’s also
0:45:25 been massively abused and misused.
0:45:29 Nowadays, if you see a headline, economy grew by 3.2%.
0:45:32 They mean GDP increased by 3.2%.
0:45:34 And why is that an imprecise or not useful measure?
0:45:39 Well, GDP measures basically everything that’s bought and sold in the economy.
0:45:44 What that means, with few exceptions, if something doesn’t have a price, it’s not counted in
0:45:45 GDP.
0:45:47 So we’re missing a lot of important stuff.
0:45:52 Clean air, a classic problem is if I cook a meal for myself, that’s not part of GDP.
0:45:57 But if I hire somebody to cook it, or if somebody pays me to cook it, then it is part of GDP.
0:45:59 So you have a lot of little weirdnesses like that.
0:46:01 A lot of household production is not there.
0:46:05 And one of the biggest ones, I’m the director of the Stanford Digital Economy Lab, is all
0:46:11 these digital goods that are often free, Wikipedia, search, Facebook, texting, email.
0:46:15 If they have zero price, other than the electricity and a few other things, they’re basically
0:46:17 not counted in GDP.
0:46:19 Yet people get a lot of value from them.
0:46:24 Right now, the average American spends a little over eight hours per day looking at a screen
0:46:28 of some sort, TV, computer, whatever.
0:46:31 That means they’re spending slightly more than half their waking hours interacting
0:46:34 with bits, not with all the other things.
0:46:40 That means a big part of our lived experience is these things that are not being well measured
0:46:42 by traditional GDP.
0:46:46 So it’s interesting, because where you’re heading here plainly is that we are richer
0:46:51 than we appear, because how we’re counting wealth is imprecise and incomplete.
0:46:56 On the other hand, if we’re even richer than the numbers say, why are so many people so
0:46:57 miserable?
0:46:59 Well, you’re absolutely right.
0:47:02 We have a lot more wealth than we had before.
0:47:04 But we also did before as well.
0:47:09 I mean, there’s television and penicillin, things were also not counted very well.
0:47:15 But wealth is not the same as happiness, as we know, and so it doesn’t automatically translate
0:47:16 one for one.
0:47:20 But it doesn’t mean we have an imperfect measure of the value that our economy is creating
0:47:21 for us.
0:47:26 There is this famous in economics idea of basically diminishing return on wealth and happiness
0:47:30 that was argued by Danny Kahneman and someone else, I can’t remember who, that original
0:47:31 paper.
0:47:35 Easterlin is called the Easterlin paradox that what you just said that as people got
0:47:37 richer, they didn’t seem to get happier.
0:47:41 More recent research found that, actually, it just sort of is diminishing returns like
0:47:42 you’re saying.
0:47:43 It’s not that it actually stops.
0:47:44 Yeah.
0:47:45 And I guess this is what gets us to GDPB.
0:47:47 So tell us what the B stands for.
0:47:48 Yeah.
0:47:50 Who are you working with or for?
0:47:54 And what is the intention of invoking this new measure?
0:47:56 So the B stands for the benefit.
0:48:01 As I said earlier, GDP is basically a measure of production, what it costs to produce things.
0:48:05 The GDPB is trying to capture the consumer surplus.
0:48:09 It’s the value between what the most you would have paid, what you actually have to pay.
0:48:14 So with Wikipedia, if you would have been willing to pay $15 a month and you pay zero,
0:48:15 you’re getting $15 of consumer surplus.
0:48:17 And you’re trying to measure that.
0:48:18 Yes, we are.
0:48:19 How do you do that?
0:48:25 So if I were to do a survey and say, okay, I’ll give you $500 to stop using the internet
0:48:29 or stop using email, more realistically, for 30 days.
0:48:31 Some of you would raise your hands and some of you wouldn’t.
0:48:36 If I said, okay, what if I gave you $50, what if I gave you $5, you get fewer and fewer
0:48:38 people being willing to give it up.
0:48:40 And that gives you a downward sloping demand curve.
0:48:45 A lot of people think it’s worth at least $500, not so many think it’s only worth $5.
0:48:50 And the area under that curve, we call that consumer surplus.
0:48:53 And if you do that for lots of different goods, you start getting a sense of how much value
0:48:54 all these different goods are creating.
0:48:56 And is this a government project?
0:49:01 No, it’s something I came up with on my own where we decided that we should measure consumer
0:49:02 surplus and not just cost.
0:49:05 And so we started doing some small scale surveys.
0:49:09 And we got some money from different groups, the National Science Foundation, the Sloan
0:49:10 Foundation.
0:49:12 So I guess part of it is a government project.
0:49:15 And we’d love to get more support to do it at a larger scale.
0:49:20 We’re doing about 250 goods right now, including digital goods, non-digital goods.
0:49:24 We ultimately want to get a representative basket of several thousand goods that we can
0:49:30 track periodically alongside traditional GDP and see how they compare.
0:49:33 The thing that’s so interesting to me, I mean, the whole thing is fascinating.
0:49:38 I’m curious to know what the ramifications would be if your measure were to become widely
0:49:39 embraced.
0:49:44 But one consequence that I could imagine is that the way that our government currently
0:49:49 looks at regulation and antitrust especially, which is going to change with the new administration
0:49:50 for sure.
0:49:55 But when you’re talking about basically the hidden or uncounted benefits of many, many,
0:50:01 many firms that are the targets of regulators now, it could be that those benefits that are
0:50:08 not being counted should be reason for antitrust legislation to be considered very differently.
0:50:09 Would you say that’s the case?
0:50:10 Yeah.
0:50:15 I mean, I think already there is a standard among many antitrust experts that came out
0:50:19 of Chicago actually that, you know, we should look at consumer welfare as the ultimate metric.
0:50:20 But that was a few decades ago.
0:50:22 I feel like we’ve moved past that now.
0:50:23 Well, that’s the concept.
0:50:28 In terms of measuring, so Lina Khan has a different measure and there’s an ongoing debate.
0:50:33 But I like the consumer welfare standard, which is, you know, is this concentration,
0:50:38 this merger, this spin off, whatever, is it making consumers better off or worse off?
0:50:39 And that’s hard to measure.
0:50:42 But our tool, GDPB, gives us a set of measures for that.
0:50:43 And you’re right.
0:50:48 In many cases, there’s a tremendous amount of value from Google search or from email.
0:50:52 One of my students was over in the European Commission and they were upset about all the
0:50:56 money that the big companies based here in San Francisco and around the United States
0:51:00 were making on European consumers and saying, oh, this is a very unbalanced thing where
0:51:03 there’s a lot of money going in this direction.
0:51:07 And he pointed out, well, actually, if you measure the value that people are getting,
0:51:11 there’s far more value that French citizens are getting from these services than what
0:51:12 they’re paying.
0:51:14 So the net gain is in the other direction.
0:51:15 That’s really interesting.
0:51:19 I mean, I’m guessing that the way that European regulators think about American tech firms,
0:51:23 that argument as true as it might be is probably not going to change the regulatory position.
0:51:25 Not as much as them having their own tech firms.
0:51:29 And so when they have companies like Mistral, I met with the finance minister in France,
0:51:33 and he was coming around to the view that, well, actually, maybe tech companies can create
0:51:37 some value now that we have one of our own.
0:51:40 So there’s quite say it that way.
0:51:47 I would argue that Silicon Valley, Northern California generally, have created an innovation
0:51:55 economy that is now global and just massively large and massively influential in many ways.
0:52:01 In a way, I feel like the global economy kind of is, at root, the Silicon Valley economy.
0:52:05 I know we still do a lot of other stuff in this country, and it’s not the majority of
0:52:09 the economy by any stretch, but it’s such a fundamental part.
0:52:15 And more so, it has such sway in our daily lives, in our political lives, and so on.
0:52:20 And when I hear you talk about GDP, I think, if anything, we are underweighting the leverage
0:52:22 of this economy here.
0:52:25 So I’m curious to know if you think I’m medium wrong, totally wrong, only a little bit wrong
0:52:26 or maybe a little bit right.
0:52:27 I agree.
0:52:31 I mean, look, I moved out here four years ago from Boston, another pretty innovative
0:52:36 place, but I really underestimated how amazing the culture is out here.
0:52:39 I am constantly meeting people doing startup things.
0:52:43 They have these grand visions and dreams, and I think they’re mostly pretty sincere about
0:52:45 wanting to change the world for the better.
0:52:47 I moved here in summer of 2020.
0:52:49 I remember it was COVID.
0:52:53 We had this garden party, and I sort of half-jokingly nervously said, “Hey, are you guys all going
0:52:55 to be moving to like Austin or Miami or something?
0:52:57 Did I kind of miss the party?”
0:52:58 And they laughed at it.
0:52:59 “Oh, don’t worry.”
0:53:01 It kind of seems like, you know, San Francisco and the Bay Area is going downhill.
0:53:02 I said, “Don’t worry.
0:53:03 There’ll be something.”
0:53:05 We didn’t know about Chatch E.P.T. at that point.
0:53:08 Maybe a few of the people in the room might have been working on it for all I know.
0:53:13 But then, of course, there’s this explosion, and if anything, I think the tech innovation
0:53:18 scene is even more concentrated in the Bay Area now than it was when I came in 2020.
0:53:21 And there’s just a whole wave of innovations.
0:53:24 People talk about it, but, and I’m an economist, I don’t really fully appreciate it until I’m
0:53:25 here.
0:53:28 There’s a cultural element to it, an attitude.
0:53:31 It partly attracts people from around the world who have this mindset of wanting to
0:53:33 change the world.
0:53:38 People help each other to do it, and like you said, it’s been a tremendous engine of creativity
0:53:39 and wealth creation.
0:53:45 And what about the, I mean, I said it derisively and half jokingly, but what about the failed
0:53:49 state feel that San Francisco has projected to the world?
0:53:55 At least how do you reconcile the, you know, the epicenter of the global tech machine and
0:53:59 economy with the fact that this is a city that has repelled people?
0:54:00 Yeah.
0:54:01 It’s a tragedy.
0:54:03 Part of it, to be fair, I think it’s overrated.
0:54:06 Like London Breed was saying, I heard, you know, apparently it has the lowest murder
0:54:10 rate in 60 years, and, you know, I come up to San Francisco a fair number of times.
0:54:15 I don’t think it’s like what is described by Elon Musk or others on Twitter.
0:54:21 Well, there’s a good timing.
0:54:22 But part of it is real.
0:54:25 I just walked over from Union Square, and there were definitely some homeless people
0:54:26 on the street.
0:54:29 In the green room, I gave London Breed a little bit of a hard time, you know, about why do
0:54:30 we allow this?
0:54:35 I think in some ways, I’m not a sociologist, but maybe all the wealth and success allows
0:54:40 a lot of sort of slack and allows them to get away with a lot of mismanagement.
0:54:44 I’m not signaling out her, anybody in particular, but I do think a lot of that government is
0:54:47 not managed as well as it could be.
0:54:51 They can get away with it because there’s just so much innovation and wealth being created
0:54:52 that you can have a lot of slack.
0:54:57 I’m hoping that will get tightened up a bit because it doesn’t reflect well on California
0:55:03 or on San Francisco, and with all the money being poured in to try to support San Francisco
0:55:04 in the Bay Area.
0:55:09 We should have the cleanest streets, the best police force, the safest neighborhoods, and
0:55:13 we don’t.
0:55:17 So if you were mayor for, you know, a month, I think I’d be a terrible mayor.
0:55:20 Economists do think differently about problem solving, right?
0:55:23 Well, a lot of them are probably just common sense, but a few of them, you know, where
0:55:27 economists may be different, like I’m a huge fan of congestion pricing.
0:55:30 Almost everyone who I know who is not an economist doesn’t think that’s a good idea.
0:55:32 But well, I guess some of these guys may be economists.
0:55:35 One of the first rules of taxation is you tend to get less of what you tax.
0:55:38 So if you’re taxing work and investment, you’re going to get less of that.
0:55:39 Why not tax pollution?
0:55:41 Why not tax congestion?
0:55:46 I also sometimes advise Singapore, and they’ve put it in place all these rules that economists
0:55:47 have.
0:55:48 Will you just slip that in?
0:55:49 You sometimes advise Singapore?
0:55:50 No, no.
0:55:51 Well, on Thursdays or what?
0:55:54 I’ve been there and met with senior officials, just like I meet with senior officials in
0:55:55 lots of different places.
0:55:57 I mean, not like an official advisor or anything.
0:55:59 Do you have a badge of some kind?
0:56:00 A badge?
0:56:01 No.
0:56:02 You have a cape?
0:56:03 No, no.
0:56:04 I am just a professor.
0:56:08 But what I like about Singapore is they listen to professors, and they don’t listen to professors
0:56:09 in the US Congress.
0:56:13 And that’s one of the reasons that they’re successful over there, I think I’m biased.
0:56:17 And one of the reasons so many people are leaving California is because it’s so expensive
0:56:18 here, and it doesn’t need to be.
0:56:22 And the reason it’s so expensive is because a lot of people would love to live here, but
0:56:26 the housing prices are insanely high because it’s supply and demand.
0:56:27 It’s elementary.
0:56:28 It’s economics 101.
0:56:33 These are things that are actually really easy to fix, and we could do a lot better.
0:56:37 I see why they call you the ever-powerful son of the armored wolf.
0:56:38 That was fantastic.
0:56:52 Eric Brynjolfsen, thank you so much.
0:56:57 I would like to thank Eric Brynjolfsen, Coleman Strumpf, and Mayor London Breed for joining
0:56:59 us on stage in San Francisco.
0:57:03 And I would especially like to thank the 1,500 folks who bought a ticket and came to hang
0:57:04 out with us.
0:57:10 If you want to see Freakonomics Radio Live, we have an upcoming show on February 13th
0:57:15 in Los Angeles with Ari Emanuel and other special guests.
0:57:19 Tickets are at freakonomics.com/liveshows, one word.
0:57:24 And if you liked hearing what Eric Brynjolfsen had to say about the impact of AI, be sure
0:57:29 to catch the next episode of Freakonomics Radio, where we will hear about a new technology
0:57:31 designed to thwart AI.
0:57:36 That’s right here in your podcast feed at our new time Friday morning.
0:57:42 Until then, take care of yourself, and if you can, someone else too.
0:57:45 Freakonomics Radio is produced by Stitcher and Renbud Radio.
0:57:50 This episode was produced by Abigail Lowenthal, Ellen Frankman, Morgan Levy, and Zach Lipinski,
0:57:53 with research help from Dalvin Aboagi.
0:57:59 Special thanks to Jesse McDaniel with Fresh AV, all the folks at Another Planet Entertainment,
0:58:07 the crew at the Sidney Goldstein Theater, and our partners SiriusXM and KQED Live.
0:58:11 The Freakonomics Radio Network staff also includes Alina Kulman, Augusta Chapman, Eleanor
0:58:16 Osborn, Elsa Hernandez, Gabriel Roth, Greg Rippin, Jasmine Klinger, Jeremy Johnston,
0:58:20 John Schnars, Neil Coruth, Sarah Lilly, and Theo Jacobs.
0:58:23 Our theme song is Mr. Fortune by the Hitchhikers.
0:58:25 Our composer is Luis Guerra.
0:58:32 Once again, thanks for listening.
0:58:37 I was able to get the Chinese government to commit to allowing San Francisco to host
0:58:38 pandas.
0:58:39 You went to China to get the pandas.
0:58:42 I went to China to get some panda bears.
0:58:49 It’s called panda diplomacy.
0:58:57 The Freakonomics Radio Network, the hidden side of everything.
0:59:00 [MUSIC PLAYING]
Stephen Dubner, live on stage, mixes it up with outbound mayor London Breed, and asks economists whether A.I. can be “human-centered” and if Tang is a gateway drug.
- SOURCES:
- London Breed, former mayor of San Francisco.
- Erik Brynjolfsson, professor of economics at Stanford University
- Koleman Strumpf, professor of economics at Wake Forest University
- RESOURCES:
- “SF crime rate at lowest point in more than 20 years, mayor says,” by George Kelly (The San Francisco Standard, 2025)
- “How the Trump Whale and Prediction Markets Beat the Pollsters in 2024,” by Niall Ferguson and Manny Rincon-Cruz (Wall Street Journal, 2024)
- “Artificial Intelligence, Scientific Discovery, and Product Innovation,” by Aidan Toner-Rodgers (MIT Department of Economics, 2024)
- EXTRAS:
- “Why Are Cities (Still) So Expensive?” by Freakonomics Radio (2020)