America’s Casino Economy — with Kyla Scanlon

0:00:06 Support for this show comes from the Audible original, The Downloaded 2, Ghosts in the Machine.
0:00:15 Quantum computers, the next great frontier of technology, offering endless possibilities that stretch the human mind.
0:00:23 But for Roscoe Cadulian and the Phoenix Colony, quantum computing uploads the human mind with life-altering consequences.
0:00:34 Audible’s hit sci-fi thriller, The Downloaded, returns with Oscar winner Brendan Fraser, reprising his role as Roscoe Cadulian in The Downloaded 2, Ghosts in the Machine.
0:00:41 This thought-provoking sequel from Robert J. Sawyer takes listeners on a captivating sci-fi journey.
0:00:47 A mind-bending must-listen that asks, what are you willing to lose to save the ones you love?
0:00:53 The Downloaded 2, Ghosts in the Machine. Available now, only from Audible.
0:01:06 Support for this show comes from the Audible original, The Downloaded 2, Ghosts in the Machine.
0:01:09 The Earth only has a few days left.
0:01:15 Roscoe Cadulian and the rest of the Phoenix Colony have to re-upload their minds into the quantum computer.
0:01:20 But a new threat has arisen that could destroy their stored consciousness forever.
0:01:29 Listen to Oscar winner Brendan Fraser reprise his role as Roscoe Cadulian in this follow-up to the Audible original blockbuster, The Downloaded.
0:01:35 It’s a thought-provoking sci-fi journey where identity, memory, and morality collide.
0:01:40 Robert J. Sawyer does it again with this much-anticipated sequel that leaves you asking,
0:01:44 What are you willing to lose to save the ones you love?
0:01:50 The Downloaded 2, Ghosts in the Machine. Available now, only from Audible.
0:02:04 Support for this show comes from the Audible original, The Downloaded 2, Ghosts in the Machine.
0:02:07 The Earth only has a few days left.
0:02:13 Roscoe Cadulian and the rest of the Phoenix Colony have to re-upload their minds into the quantum computer.
0:02:18 But a new threat has arisen that could destroy their stored consciousness forever.
0:02:27 Listen to Oscar winner Brendan Fraser reprise his role as Roscoe Cadulian in this follow-up to the Audible original blockbuster, The Downloaded.
0:02:33 It’s a thought-provoking sci-fi journey where identity, memory, and morality collide.
0:02:38 Robert J. Sawyer does it again with this much-anticipated sequel that leaves you asking,
0:02:42 What are you willing to lose to save the ones you love?
0:02:47 The Downloaded 2, Ghosts in the Machine. Available now, only from Audible.
0:02:57 Episode 371.
0:03:00 371 is the country code for Latvia.
0:03:04 In 1971, Starbucks opened its first store in Seattle.
0:03:06 True story, I’ve gotten really into VR.
0:03:09 And like many technologies, the first great real application is porn.
0:03:14 And I tell you, you cannot get over how immersive it is.
0:03:19 I got totally lost in this porn film in VR.
0:03:21 Unfortunately, I forgot I was at a Starbucks.
0:03:27 Go! Go! Go! Go!
0:03:38 Welcome to the 371st episode of the Prop G Pod.
0:03:39 What’s happening?
0:03:43 I’m home in London now, but heading to New York soon to kick off my press tour
0:03:47 for our latest book, Notes on Being a Man.
0:03:52 And truth be told, I’m looking forward to getting into New York,
0:03:53 and I’m looking forward to seeing friends.
0:03:59 But we’re doing literally everything from The View to Morning Joe to Bill Maher.
0:04:03 And quite frankly, I’m intimidated.
0:04:05 I’m just really wanting it to be over.
0:04:06 I want to do really well.
0:04:08 And I guess that’s good.
0:04:08 That’s part of it.
0:04:13 But I have, I wouldn’t call it anxiety, but I’m not, I’m more intimidated.
0:04:17 And it’s, sometimes it’s better to be lucky than good.
0:04:19 I know this book is going to sell a lot.
0:04:22 And I know that sounds arrogant, but I usually have a feel for this stuff.
0:04:24 And again, more lucky than good.
0:04:25 The timing is right.
0:04:29 This is a conversation that’s sort of evolving and pivoting from,
0:04:34 okay, the manosphere where some really ugly voices entered into the void.
0:04:37 To the far right’s credit, or to the right’s credit,
0:04:38 they recognized the problem before other people.
0:04:40 They said something is wrong in Mudville.
0:04:44 The problem was, their answer was to regress to the 50s,
0:04:49 where non-whites and women had much less power, much less agency.
0:04:50 That’s not the answer.
0:04:55 And then to start these weird fucking videos from Tucker Carlson,
0:05:01 or nominate for president people who conflate masculinity with cruelty and coarseness.
0:05:03 So that’s not correct either.
0:05:06 So I think there’s an understandable, or has been an understandable gag reflex
0:05:11 anytime you start talking about the crisis of young men,
0:05:12 or the crisis young men are facing.
0:05:15 My producer says, what is the point of the book?
0:05:17 I’ll give you sort of a distillation.
0:05:22 And that is, I think that young people really benefit from a code.
0:05:25 And that is, you have to make hundreds, if not thousands, of decisions every day,
0:05:26 big and small.
0:05:31 And it’s difficult to make these decisions just floating in space and responding to them real time.
0:05:34 And where do you get this code?
0:05:35 You can get it from your religion.
0:05:36 You can get it from the military.
0:05:37 You can get it even from your corporation.
0:05:39 You can get it from your parents.
0:05:40 What does that mean?
0:05:45 It means you should immediately feel that that physical strength is used to help others,
0:05:45 to protect others.
0:05:49 So let me get to what I think are sort of the three legs of the stool of basically masculinity
0:05:51 and one overarching theme.
0:05:54 Provider, protector, and procreator.
0:05:54 Provider.
0:06:00 I think in a capitalist economy, every man should, at the outset, as a young man, assume that he
0:06:03 is going to need to take economic responsibility for him and his family.
0:06:07 And by the way, sometimes that means getting out of the way and being more supportive of your
0:06:09 partner who’s better at the money thing than you.
0:06:16 I think we have to, from a very young age, teach boys that the greatest demonstration of
0:06:17 strength is protection.
0:06:18 And it’s not just physical.
0:06:21 People are bad-mouthing someone else.
0:06:24 Your default is to protect them and to defend them.
0:06:26 Finally, procreation.
0:06:34 I think we need to celebrate a young man’s horniness, his desire to have sex, his desire to have
0:06:35 a partnership.
0:06:42 One of the key attributes of a man that will yield dividends is their ability to establish
0:06:49 friendships, express friendship, but also demonstrate and communicate romantic interest.
0:06:52 And here’s the key part, while making that person feel safe.
0:06:56 But real mating and real interest begins in person.
0:06:58 I went to Temple and I saw how kind he was.
0:07:02 I worked with him and saw how outstanding he was at what he does.
0:07:06 I hung out with him and just found that he was funny and nice and responsible and wasn’t
0:07:07 a fucking idiot staying out late.
0:07:10 He went home because he had a plan.
0:07:14 I always felt safe around him.
0:07:16 Providing, protecting, procreating.
0:07:17 And what does it all add up to?
0:07:20 What is the litmus test for when a boy becomes a man?
0:07:22 It has nothing to do with age.
0:07:24 I know a lot of males that have never become men.
0:07:27 It has nothing to do with a religious ceremony.
0:07:29 It certainly doesn’t have anything to do with sex.
0:07:33 What it has to do with is one term, surplus value.
0:07:36 You witness people’s lives.
0:07:43 If you are able to someday, towards the end, think, I loved so many people so much that while
0:07:47 I received a great deal of love back, I go out on the plus side of this column.
0:07:49 I have achieved surplus value.
0:07:51 Then you leave this earth a man.
0:07:54 All right, enough of that.
0:07:58 In today’s episode, we speak with Kyla Scanlon, an economic commentator, educator, and bestselling
0:08:01 author of In This Economy, How Money and Markets Really Work.
0:08:06 We discuss with Kyla Trump’s casino economy, what to make of the AI bubble, and why the markets
0:08:07 no longer reflect reality.
0:08:10 So with that, here’s our conversation with Kyla Scanlon.
0:08:23 Kyla, where does this podcast find you?
0:08:26 Um, I’m actually in, uh, Florida right now.
0:08:28 Marco Island.
0:08:29 Marco Island.
0:08:33 Wait, you have grandparents or parents who vacation in Florida?
0:08:33 No?
0:08:34 What’s going on?
0:08:35 No, no.
0:08:38 I’m here for the equipment, leasing, and finance conference.
0:08:39 Yeah.
0:08:41 I heard it’s a crazy party.
0:08:43 Is it, has it gotten out of control yet?
0:08:44 The ELF party?
0:08:46 Yeah.
0:08:48 Michael Phelps is here today.
0:08:50 So, um, it’s fun.
0:08:50 Yeah.
0:08:56 I spoke yesterday, so I’m leaving later today, but that is where you find me, is, uh, Marco
0:08:56 Island.
0:08:57 Yeah.
0:08:58 Thank you for being here.
0:09:05 I, we wanted to bring you on because you had a, uh, uh, what was, I thought a really interesting
0:09:11 and provocative, uh, piece in the New York Times arguing that the American economy is really,
0:09:12 uh, Trump casino.
0:09:15 You said, can you walk us through that thesis?
0:09:16 Yeah.
0:09:22 So that piece, you know, the economy has always been somewhat of a casino, but underneath
0:09:26 the Trump administration, like there’s a lot more room for gambling.
0:09:31 Like you could see tariffs as a gamble on the American economy that our allies will want to
0:09:34 continue to work with us, that the dollar will remain stable.
0:09:39 But then also in private markets, you’re seeing a lot of gambling-esque things too, like private
0:09:41 credit is looking a little bit shaky.
0:09:46 Venture capital firms are funding, uh, like debt roulette startups.
0:09:49 And then of course you have the AI bubble that everybody is talking about right now.
0:09:55 So it just feels like everywhere you turn around from the government shutdown to the stock market,
0:09:58 like gambling has become the status quo.
0:10:03 Do you think, um, I’m trying to reverse engineer this to something very basic.
0:10:10 And that is, so I would argue that geopolitics is just, uh, an administration that’s somewhat
0:10:15 ignorant and hasn’t done the game theory and overestimates their power at the poker table.
0:10:18 They show up with cards that they don’t actually have.
0:10:21 Um, and that’s, I would call that poor judgment.
0:10:27 I’m not sure it’s, it’s gambling, but at the same time on the other end, what I see is a
0:10:32 lot of young people who are constantly reminded every day that they’re failing because they
0:10:37 don’t have, you know, ripped abs or aren’t on a Gulf stream or didn’t make 300% yesterday
0:10:39 on some meme coin.
0:10:44 And they believe that that is a normal part of the economy taking these sorts of crazy
0:10:46 outsized risks and are engaging in it.
0:10:49 And they have access to this type of risk taking in their pocket.
0:10:56 As someone who is younger, have you done any research or any thoughts about how this, it strikes
0:11:02 me, this gambling economy seems to be especially prevalent among your generation.
0:11:03 Your thoughts?
0:11:04 Yeah.
0:11:09 John Cohen wrote a great book that came out a few months ago about the rise of sports
0:11:09 gambling.
0:11:13 And so he did a lot of on the ground reporting with young people.
0:11:18 Like one of his primary interviews was a early twenties person named Kyle who was living in
0:11:21 Colorado who had had his life destroyed by gambling.
0:11:26 And so you do see a lot of people go towards that path.
0:11:31 Like one of the theories that I’ve been testing is that there’s this idea is that young people
0:11:34 have like zero risk tolerance or like all the risk tolerance.
0:11:38 So you see, you know, Gen Z becoming the tool belt generation, going back to the trades.
0:11:41 I think that’s primarily to reduce risk.
0:11:44 Like when I talk to people who are going down that path, they’re like, I don’t think a college
0:11:45 degree is going to pay off.
0:11:48 So I’m just going to take this staple job at the factory.
0:11:54 And then you see other young people who are going into meme coins, they’re going into
0:11:59 sports betting, they’re, you know, vetting it all on companies that are doing AI things.
0:12:05 And so it has become increasingly prevalent, I think, because we people are just grasping
0:12:08 for straws to try and climb the economic ladder.
0:12:14 You outlined three likely outcomes for this casino economy, the more probable one being
0:12:19 that we see smaller crises unfolding as low growth persists through a series of disparate
0:12:19 shocks.
0:12:25 Do you see any kind of initial signs of the trouble that you’re monitoring in this casino
0:12:26 economy?
0:12:30 I mean, lots of people are starting to talk about private credit.
0:12:36 I think that’s a bit concerning, like we’re seeing some of the auto lenders start to go
0:12:37 bankrupt.
0:12:45 First Brands, Tricolor, JP Morgan lost, I think, $175 million on that company going under Primalend.
0:12:52 So you’re starting to see some ruptures begin to happen in the private market where all of this
0:12:55 risk was taken on.
0:12:59 And there was like zero regulation, which is always a recipe for disaster.
0:13:03 So I think we’re starting to see that begin to show up.
0:13:09 And then I think we’re starting to see young people begin to suffer from the consequences
0:13:15 of the unfettered access to gambling, which you talk a lot about as well.
0:13:21 And so I think we are starting to see some of these pain pockets begin to pop up for sure.
0:13:23 What do you think of these predictions markets?
0:13:29 One is businesses and two is a reflection on our kind of society and economy.
0:13:32 I mean, I think it is kind of like gamble on everything.
0:13:38 It’s, I don’t know, like, I think the idea makes sense.
0:13:43 And like, if you’re trying to find consensus for information, I think that makes sense.
0:13:44 And like, sure.
0:13:51 But I think what they incentivize is people finding some sort of way to gamble on everything.
0:13:56 Like one of the comments underneath my New York Times article on Twitter was like, how can
0:13:58 I bet on how many views this article is going to get?
0:14:03 And so I think everybody is just seeing the world through the lens of gambling, which is
0:14:07 not a very stable or well-structured society.
0:14:10 And when I say everybody, obviously, like I’m, you know, being dramatic.
0:14:17 It’s not everybody, but it is a lot of people, because, again, it seems like the one way to make money is to bet on everything.
0:14:29 Do you think some of it, and again, this is, this really is a question looking for illumination and, and, and potentially pushback.
0:14:36 But I wonder if some of it is kind of our, our role models for a younger generation.
0:14:40 When I think about the president is always going to be a role model, whether we want him to be or not.
0:14:44 And the wealthiest person in the world in a capitalist society.
0:14:58 And both of these individuals, it feels like they’re sort of conflating or creating an image where you can easily conflate masculinity and leadership with being incredibly aggressive and incredibly risk aggressive.
0:15:06 And doing things that have never been done before, saying things that have never been done before, shooting a rocket into space that scissors can capture.
0:15:16 I mean, there’s a positive side to this risk aggression, but it feels as if our leaders are no longer measured in any way, that they’re taking these outsized risks.
0:15:23 And that’s sort of, is that potentially what’s going on here, that our role models are just more risk aggressive on, from, you know, any angle?
0:15:25 I think a little bit.
0:15:27 And like, not all risk is bad.
0:15:34 Like, in order to grow an economy, you know, you have to be able to catch a spaceship inside of scissors.
0:15:36 You have to take on some element of risk.
0:15:44 But I think, like, the risk that is being encouraged now, like, when you look at the president, just objectively, like, the guy bankrupted because he knows.
0:15:48 Like, he took on a ton of risk and, you know, that wasn’t always successful.
0:15:56 But he had, like, some form of a safety net to catch him, whereas a lot of people who are taking on risk now are doing it because they have no safety net.
0:16:03 And so I think people are looking at the billionaires, maybe soon to be trillionaires, and saying, like, okay, they took these big leaps.
0:16:05 Like, they figured it out.
0:16:06 Like, hopefully I can do that, too.
0:16:13 But the path is not always that clear, and it’s not that stable, and those people had a lot of help along the way.
0:16:19 But I do think it encourages behavior that might not be conducive to cohesiveness.
0:16:26 Like, when we think about Twitter and, you know, even just, like, quote-unquote, taking a risk on saying something polarizing on Twitter.
0:16:29 Like, a lot of people are monetizing their accounts that way.
0:16:35 So, yeah, that sort of gambling mindset applies to both money and to communication.
0:16:43 So, we now have 10 companies responsible or make up 40% of the S&P.
0:16:45 The S&P is 50% of global market cap.
0:16:50 So, 10 companies are now arguably 20% of the world’s value, at least in the public markets.
0:16:56 That, to me, feels like a concentration of risk that typically we didn’t like to have or tolerate.
0:17:01 What are your thoughts on the concentration of value across a small number of companies?
0:17:03 Yeah, I don’t think it’s great.
0:17:08 Because, also, you know, 40% of GDP growth is coming from the AI companies.
0:17:13 And the 20% of companies that you referenced are, like, primarily dabbling in AI, the big tech companies.
0:17:17 And, you know, there’s 75% of S&P 500 earnings growth.
0:17:23 And so, like, our whole economy is becoming this, like, really big, risky bet on AI.
0:17:31 But when you think about, you know, the jobs that we’re adding, they’re primarily in healthcare and social services, at least the last time that we got data from the government.
0:17:34 And so, like, these companies are taking on more and more value.
0:17:35 They’re growing bigger and bigger.
0:17:41 But they’re maybe not adding to the economy in a way that we would expect outside of building data centers.
0:17:42 Like, data centers don’t add that many jobs.
0:17:45 You don’t need that many people building them.
0:17:47 Like, what the U.S. needs is jobs.
0:17:48 And so, I worry about that.
0:17:55 Like, I think I do worry about the concentration risk, especially when we think about 401Ks and people who are going to try to retire soon.
0:17:58 Like, all of the onus of their retirement is on them.
0:18:01 And, therefore, it’s on the S&P 500 continuing to succeed.
0:18:11 And then I also worry about these companies really just sucking the life out of the market and then not contributing to the economy in a way of a growing labor market.
0:18:17 Yeah, I parrot a comment you made that just sort of summarized the economy right now.
0:18:20 You said America is essentially a giant bet on AI.
0:18:28 And I thought that was just such a kind of cogent distillation of what’s going on right now.
0:18:33 My sense of history is the stuff you’re expecting to go right oftentimes doesn’t.
0:18:36 And the stuff you’re expecting to go wrong oftentimes doesn’t.
0:18:40 Like, upticks in the market are from areas we weren’t expecting.
0:18:46 And crises, you know, 9-11 and COVID, very few people were predicting those things.
0:18:55 If you were, if someone said to you at your conference, Kyla, do you think it’s a good time or a bad time to invest in this AI economy?
0:18:56 What are your thoughts?
0:19:05 I mean, what I’ve been telling people, and obviously, like, it’s not investment advice, but I still think it’s important to have some exposure to the companies.
0:19:16 Not all exposure, like, that’s kind of one of the issues with younger investors is, like, 70% of their portfolio will be in tech companies, which is, like, you know, a decent rule of thumb.
0:19:19 But with the concentration risk, I think it’s pretty dangerous.
0:19:32 And so a lot of investment advisors will advise you to diversify across gold, across utility companies, across, like, things that are a little bit more stable, you know, across international companies, too.
0:19:37 So not having your whole portfolio just exposed domestic.
0:19:46 So I think that’s, like, one way to navigate the uncertainty and, you know, the potential bubble popping that we might have.
0:19:49 So that’s been a good rule of thumb.
0:19:52 What does Kyla Scanlon do with her money?
0:19:53 How do you invest?
0:19:54 What’s your approach to investing?
0:19:57 Yeah, Kyla Scanlon does what I just said.
0:19:58 So, yeah, that’s what I do.
0:19:59 So index funds, or…?
0:20:01 Yeah, yeah, yeah, primarily.
0:20:05 And then, you know, I’ve been taking advantage of high-yield savings accounts as well.
0:20:10 You know, the Fed is probably going to cut rates, so that’s going to get less and less exciting.
0:20:12 But when rates were high, that was pretty cool.
0:20:17 But, yeah, no, I’m pretty exposed across ETFs.
0:20:20 I’m a very boring, very plain vanilla investor.
0:20:25 I, you know, put aside $20 a month toward the S&P.
0:20:28 And then I’ve been investing more and more in gold.
0:20:33 But the recent run-up in gold has been a bit, like, oh, this feels a little dangerous, too,
0:20:38 which is crazy that, like, people are looking at gold as something that’s too risky to invest in.
0:20:41 I have some exposure to crypto as well.
0:20:48 So I just try to, like, have a diversification as one of the only free lunches and investing, as they say.
0:20:50 So I try to take advantage of that.
0:21:00 And do you buy the thesis that the surge in gold and the increase in crypto over the last couple of years is essentially the debasement of the dollar and trust in America?
0:21:07 I mean, that’s, you know, that’s an interesting topic that a lot of people have gone back and forth on.
0:21:11 I mean, crypto is a levered NASDAQ, so I don’t think you can really say that about crypto.
0:21:15 It’s been unfortunate to watch that industry lose itself.
0:21:19 And I used to work in crypto and I thought it could be something really cool.
0:21:23 And I just think it’s become also a part of the gambling economy.
0:21:33 But with regards to gold, like, I think the interesting thing there is that China is really trying to become the place where people park their gold reserves to kind of, you know, navigate around the U.S. dollar.
0:21:38 Saying, like, hey, everybody, like, invest in gold and then invest that gold with us.
0:21:45 And I think that might work in some regards, because I do think people might be trying to find some alternative to the dollar.
0:21:49 I think that’s going to take a long time if that does eventually happen.
0:21:56 But I think there’s some element of truth and people are trying to not have as much exposure to the U.S.
0:22:01 You said a couple of things I want you to unpack there, that crypto has levered NASDAQ.
0:22:02 What do you mean by that?
0:22:06 And then secondly, you said you were in crypto, but you think the industry has lost itself.
0:22:07 Say more about that.
0:22:11 Yeah, I mean, I’m not the first person to call crypto levered NASDAQ.
0:22:14 It’s essentially like the way that tech stocks move.
0:22:16 Crypto will move like three times bigger.
0:22:21 So if tech has a big sell-off, then crypto will have a gigantic sell-off.
0:22:23 If tech moves up, crypto will move up.
0:22:33 It’s interesting because, you know, now JP Morgan is allowing institutional clients to use Bitcoin and Ethereum as collateral.
0:22:44 So there is like that institutional backing to crypto, but that also means it tends to trade a bit like tech stocks because institutions have sort of flattened it and like flattened the moves.
0:22:50 So I just think it’s like not any different than tech, which is probably a very unpopular opinion.
0:22:58 But to the point that I used to work in crypto, yeah, I used to work with several crypto companies and thought it was really great.
0:23:12 A lot of my very early writing was about crypto and kind of about what it would look like to have the future of finance, like what decentralized finance could look like, you know, what it could look like to sort of build this online world that had its own form of money.
0:23:21 And yeah, I mean, when you even think about Bitcoin, like the original proposal was a person-to-person payment system.
0:23:24 And I don’t think it really can be that just because it’s so speculative.
0:23:26 So it’s not necessarily a bad thing.
0:23:29 It’s just I don’t know if crypto knows what it is.
0:23:31 It’s definitely not a currency.
0:23:32 It’s just an asset.
0:23:37 And you feel as if it sort of lost itself or it sounds like your tone was you soured a little bit on the industry.
0:23:45 This is just one of the things that happens when people get really, really, really rich is they forget what they’re doing something for.
0:23:49 And I think a lot of people in crypto, you know, saw tremendous wealth.
0:23:58 And I think you can kind of lose the plot when all of that money comes pouring in and you might forget the mission of what you’re originally doing.
0:24:00 I think Ethereum has kept to the plot pretty closely.
0:24:05 Like Vitalik, one of the founders, seems pretty focused on like what he wants that thing to be.
0:24:09 But that’s not, you know, that’s not the whole industry.
0:24:14 We’ll be right back after a quick break.
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0:28:16 What are you seeing when you look at economic data?
0:28:22 What do you think are the biggest stories unfolding to get the least amount of coverage relative to the impact they might have?
0:28:24 What are we not talking about that we should be talking about?
0:28:28 Everyone’s, I feel like we’re on to kind of the AI bubble.
0:28:31 There’s a lot of, there’s a lot of media around that.
0:28:32 This reminds me of 1997.
0:28:39 And that is, everyone had consensus we were in an internet bubble and the NASDAQ went up another 100%.
0:28:43 It’s when everyone decides we’re in a new model and it’s different this time.
0:28:47 And maybe all rules, you know, all bets or the rules have been broken.
0:28:48 That’s when you need to watch out.
0:28:52 So I feel like the AI quote-unquote bubble has been covered.
0:28:57 What are you seeing in your data and your research that you don’t think is getting enough coverage?
0:29:01 So you think we’re in 1997 right now relative to the AI bubble?
0:29:05 The good news is when you’re my age, you have some historical perspective.
0:29:07 The bad news is you have historical perspective.
0:29:10 And that is you want to make your life easier with pattern recognition.
0:29:15 And the reality is most of these patterns are, you know, the history does repeat itself.
0:29:16 Well, what is it?
0:29:18 It doesn’t, it, you know, it rhymes.
0:29:19 It doesn’t repeat.
0:29:21 I see a lot of similarities.
0:29:23 These circular deals really worry me.
0:29:28 You know, NVIDIA investing $100 billion in a company with the agreement they’re going to buy their chips.
0:29:36 And that is accretive in the short run, but setting up kind of a house of cards in terms of, you know, capital structure, capital formation.
0:29:38 I see euphoria.
0:29:46 But at the same time, it’s different this time in the sense that these companies, their earnings growth hasn’t matched their PE expansion, but it’s pretty strong.
0:29:48 These are real companies with real cash flows.
0:29:54 But what I was referring to is that the economists called the dot bomb implosion perfectly.
0:29:58 They said how it would start, why it would happen, the damage it would do.
0:30:00 Problem is they called it a 1997.
0:30:05 And from that point, if you’d stayed in internet stocks, you would have made a ton of money.
0:30:07 Now, granted, you would have given it all back.
0:30:17 But I don’t, you know, what I have come to believe is that when everyone, when all economists agree on something, you should go the other way.
0:30:28 And it feels like all economists, at least right now, are saying AI is, you know, somewhat overvalued, which lends me to believe that, okay, it’s probably going to run further.
0:30:32 I mean, every instinct in my body is saying sell all stocks right now.
0:30:37 But typically, when I have that emotion, a lot of people are having that emotion, and it’s not the thing to do.
0:30:40 But so, yeah, I see echoes of it.
0:30:46 But the reality is I don’t trust my gut on this stuff a lot because I try to be emotionless and do what you’re doing.
0:30:52 And that is just be diversified and not try to time the market and not try and convince yourself you’re smarter than the market.
0:30:59 But are there things out there that, you know, it’s, it’s, it’s the iceberg you don’t see that takes the ship down.
0:31:02 Are there things you see, you see that people that we’re not talking about?
0:31:12 I mean, yeah, I agree with you that everybody’s talking about the AI bubble and how bad it could be if it all explodes because it is such a big part of the economy.
0:31:15 You know, 40% of GDP growth is, is no joke.
0:31:22 But I think, like, a lot of people are talking about it, but the government shutdown, I feel like, has not.
0:31:24 Like, we’re kind of like, oh, no, it’s still shut down.
0:31:29 And we’re, it’s, like, about to be the second, I think it is the second longest shutdown ever.
0:31:35 And, you know, a bunch of people, 40 million people are about to lose access to food stamps.
0:31:44 And I just think, like, there’s such a clear distinction, and I’m curious if it was the same way in the 1990s.
0:31:50 There’s such a clear distinction and divergence between the stock market and the economy.
0:31:55 So, like, with the government shutdown, like, that’s severely affecting the economy, but you have this huge run-up in stocks.
0:32:03 And I think a lot of people are kind of covering that idea, but when we talk about the AI bubble, I don’t think we necessarily talk about that idea.
0:32:07 It’s more like, oh, no, NVIDIA gave OpenAI a hundred billion, billion, billion dollars.
0:32:10 So, was it like that in the 1990s, too, like that?
0:32:13 Did you feel that divergence between the two?
0:32:15 It’s a really thoughtful question.
0:32:29 You know, in the 90s, I was building internet companies and not that thoughtful, or I didn’t have much situational awareness beyond the e-commerce company I was running, trying to raise money for, and trying to hire people.
0:32:32 I didn’t think a lot about big-picture societal issues.
0:32:36 Also, we just didn’t have the concentration of wealth.
0:32:40 We didn’t have—it felt like a more gentle time.
0:32:46 It was George Bush, who looked soft and cuddly back then, although progressives thought he was evil and carnate.
0:32:50 Now we look back and think, God, he was so adorable and so nice.
0:32:53 And there wasn’t nearly the polarization.
0:33:11 And also, we didn’t have—we were blessed with a lack of social media showing—I mean, social media has figured out that I’m a progressive and that every video they show me of a mass person from ICE separating a woman from her husband knows I’m going to be so fucking enraged that I’m not going to be able to look away from the phone.
0:33:21 And so I don’t know how much—you know, there’s an interesting statement, another statement I love, is that we’re not that divided, but we have the most powerful companies in the world trying to divide us.
0:33:23 So it is different.
0:33:37 I don’t envy people of your generation whose media consumption is so anxiety-ridden, is so trying to tune you up to enrage you such that you’ll be engaged.
0:33:41 One, where does someone like you get the majority of your information?
0:33:43 What is your media diet?
0:34:05 And have you found—and this is more of a question around, you know, the psychological impact—but if you found that it takes a toll on you and people your age, I’m—and I don’t—I can’t figure out if it’s I’m just getting older and angry or more depressed, but I literally have to have self-imposed blackouts from the media now because I find that algorithms are purposely trying to take me down really, really ugly rabbit holes.
0:34:09 Anyways, your media diet and thoughts on the impact on your generation?
0:34:17 Yeah, I mean, my media diet is I—I read a lot of the, you know, major news publications, so New York Times, Wall Street Journal, Bloomberg.
0:34:22 I also love, like, the other magazines, like N Plus One, Phenomenal World.
0:34:28 So I read a lot, but I also use Twitter a lot, and it’s been—or X.
0:34:40 So, and that’s been, like, the biggest bummer in the world is that used to be such a place for economists and finance people to really get together and, like, talk about ideas.
0:34:48 Like, it used to be, you know, this place to really connect, and even back in 2021, and now it’s not.
0:34:53 It’s, like, so polarized, and the algorithm is being tweaked to totally fry everybody.
0:34:57 And so I definitely see that with a lot of young people.
0:35:03 And I have an account that I’ve tuned to be quite conservative.
0:35:13 So this is, like, a burner account that I don’t post or anything, but I just view that account to make sure I’m not missing anything,
0:35:20 because my feed is also, you know, pretty attuned to what Democrats are up to or the center-left or center-right.
0:35:24 And, yeah, this account is very MAGA-oriented, and it’s wild.
0:35:31 Like, the amount of rage bait that that account gets served, and it’s pretty concerning.
0:35:43 And so I also have to make sure that I don’t fall down a rabbit hole, because one thing that’s really tough about these big companies is that they weaponize empathy, right?
0:35:48 And so a lot of people are pretty good-hearted, and they just want to help, and they just want to make sure everybody’s doing okay.
0:35:57 And that’s when you can get in trouble, is because you watch these videos or you read these things, like, trying to understand, trying to figure out how you can help.
0:36:05 And that’s really when it becomes dangerous, because you, you know, oh, I think a lot of people care so much that they go a little bit crazy.
0:36:10 And so I have to really watch myself with that kind of stuff, yeah, as I think it sounds like you do, too.
0:36:18 You mentioned the fissure of the growing disparity between kind of the Wall Street economy and the real economy.
0:36:25 We’ve said on the show that the Dow Jones and the NASDAQ have been just incredibly damaging metrics,
0:36:29 because they give people the illusion that things are okay oftentimes when they’re not.
0:36:35 And as long as the NASDAQ goes up, or my thesis is, as long as the NASDAQ keeps going up,
0:36:38 the president can send troops into American cities and get away with it.
0:36:44 Curious to get your thoughts on these metrics and also what metrics you look at
0:36:47 that you think are better indicators of the health of, quote-unquote, the real economy.
0:36:53 Yeah, I wrote this piece on my newsletter a few weeks ago called AI as a Stock Market,
0:36:55 and the stock market is the government.
0:37:00 It’s sort of that idea where the government, or yeah, the government has a lot of latitude.
0:37:06 If the stock market continues to go up, like, if the market was selling off right now,
0:37:09 he would not be allowed to send troops onto the street.
0:37:12 I think Congress would have a lot more pressure to reopen the government.
0:37:18 And because the stock market is so disconnected from any sense of reality,
0:37:22 we’re actually in, I think, deeper trouble than we should be.
0:37:28 And it’s, yeah, it’s, like, wild to watch this stuff, where it’s like, oh, AI earnings are going
0:37:29 to continue to go up.
0:37:31 Like, stock market’s going to go up forever.
0:37:34 It’s just so bizarre to me.
0:37:38 And even, you know, we got this inflation data the other day.
0:37:42 Even though the government shut down, they brought back a small team of the BLS because we needed
0:37:45 to readjust Social Security payments according to inflation.
0:37:51 And the stock market rallied on the idea that inflation was somewhat going down,
0:37:55 even though it’s still 3% year over year, that the Federal Reserve is going to cut rates.
0:37:57 It was like, woohoo, everything’s going well.
0:38:01 Even though, like, people can’t find jobs, inflation is still very high, and the Fed is
0:38:02 cutting into that.
0:38:09 And so, yeah, I think, like the metrics that I try to pay attention to, it’s a lot of anecdotes
0:38:11 right now because we don’t have data.
0:38:16 And I know that’s always, that’s a bit dangerous, but I, you know, I post videos about the economy
0:38:21 almost every day on social media, and a lot of people message me and tell me what they’re
0:38:23 feeling and what they’re paying attention to and what they’re worried about.
0:38:27 And so I kind of absorb all of that and try to get a better sense.
0:38:32 But then in terms of, like, real data, the Chicago Fed has some real-time labor market
0:38:34 indicators that are pretty useful.
0:38:37 It pulls from public and private data.
0:38:39 And so I found that to be helpful.
0:38:46 There isn’t an inflation metric that I’ve found to be super good outside of the numbers
0:38:48 that we get from VLS.
0:38:51 So I’m still trying to piece that together.
0:38:56 And yeah, and then I think another interesting thing is when we think about the stock market,
0:39:01 it’s important to look at the number of companies that are booming that have no revenue.
0:39:06 So a lot of the boom in the stock market right now is being led by these companies that don’t
0:39:07 have a lot of profits.
0:39:09 You know, they have essentially no revenue.
0:39:13 And I think that’s a good indicator for the actual underlying health of the stock market
0:39:16 and the fact that it’s not being led by fundamentals.
0:39:19 And it tells a different story than, like, the Dow Jones going up.
0:39:22 It’s like, why is the Dow Jones going up?
0:39:26 It’s because these companies that aren’t making money are going up because people are gambling
0:39:26 on them.
0:39:32 The administration trying to interfere with the Fed, what feels like socialism or government
0:39:37 intervention or attempted influence on private markets, picking companies they invest in
0:39:40 or wanting a golden share in U.S.
0:39:40 deal.
0:39:45 Tariffs, which is when I was in graduate school and I was a graduate student instructor in macro
0:39:46 and microeconomics.
0:39:48 It was just a case study.
0:39:51 And look at how stupid we were at one point in history with tariffs.
0:39:54 I’m surprised.
0:39:55 I’m curious if you’re surprised.
0:39:59 Are you surprised the economy is as strong or not as bad?
0:40:03 I would have thought the economy would not be holding up the way it is right now.
0:40:04 What are your thoughts?
0:40:09 You thought it would have imploded because of the tariffs or just because of everything else
0:40:09 going on?
0:40:09 All of it.
0:40:18 Fear around lack of independence of the Fed, tariffs, a move towards a cross between socialism
0:40:19 and cronyism.
0:40:25 I just think all of these things, to me, the market would have had a stronger gag reflex.
0:40:31 And the numbers, to be fair, a lot of the underlying numbers are concerning, but a lot of them are
0:40:36 stronger than I think people were expecting, right?
0:40:38 I don’t, the inflation number is not good, but it’s not terrible.
0:40:41 You know, there’s the AI boom.
0:40:45 I keep reading about this quote unquote re-industrialization of America.
0:40:48 I’m not entirely sure what that means, but I keep reading about it.
0:40:54 I don’t know how much of it is just propaganda, but are you, what are your current thoughts on
0:40:56 the state of the economy versus your expectations?
0:41:01 And if you’re comfortable talking about what you think might unfold in, say, 26.
0:41:10 Yeah, I mean, to the point of the re-industrialization of the economy, Iowa, a state that is very reliant
0:41:12 on manufacturing, is like essentially in a recession.
0:41:18 So there’s a really interesting map, and I cannot remember who made the map, but it showed the
0:41:23 number of U.S. states that were in some type of economic contraction, and it was over half
0:41:24 of them, I believe.
0:41:30 And so I think when we like zoom in on these individual cases, like states that were really
0:41:37 reliant on manufacturing actually working out, you see a lot of that not happening.
0:41:42 One of the things that Trump did promise was that he would bring manufacturing back to the
0:41:48 U.S., and the way that he’s doing that is through tariffs, which is not that intuitive,
0:41:49 right?
0:41:54 Ideally, you would use a carrot instead of a stick method in order to bring people back,
0:41:57 and it takes a long time to rebuild manufacturing.
0:42:06 And so you do see these pockets of pain for these places that overwhelmingly did vote for
0:42:06 Trump.
0:42:11 And the longer the government stays shut down, like a lot of these red states that voted
0:42:16 for Trump, they’re heavily reliant on the social safety net, like they’re reliant on food
0:42:20 stamps, they’re reliant on Medicaid, the thing that is being the reason the government shut
0:42:21 down, right?
0:42:21 Health care.
0:42:27 And yeah, I think it’s going to get more and more painful because people need those
0:42:28 things.
0:42:34 People need an economy that works outside of AI, like they need jobs that are more than just
0:42:35 data center.
0:42:41 And the argument there is that like the economy has always gone through some turmoil with technology.
0:42:49 Like nails used to be 0.5% of GDP like hammer and nails back in the 1800s.
0:42:55 And so like there’s always some shift, but I think like this, this, and I’m curious what
0:43:00 you think about this, like the combination that we have right now of political turmoil and
0:43:04 technological turmoil is like quite pronounced.
0:43:12 And it seems the way that politics are unfolding just objectively, as you said, is like pretty
0:43:14 destructive, just net on net.
0:43:18 Like it’s harmful and I think the market is ignoring that because of the AI stuff.
0:43:25 It’s like, okay, who cares if like the economy implodes outside of AI as long as AI succeeds
0:43:26 because it’ll take over everything.
0:43:28 And so I think that’s a divergence.
0:43:33 But like this transitional time, if it does end up working, is really painful.
0:43:38 But like how do you sort of see that combination of politics and technology?
0:43:44 Like, do you think they’re feeding off of each other in a harmful way or protecting the economy?
0:43:45 Well, I would bifurcate them.
0:43:47 I don’t think you can get in the way of innovation.
0:43:50 And that is AI is going to replace a lot of jobs.
0:43:57 I actually think automation and GLP-1 are perhaps even more impactful technologies than, you know,
0:44:03 I just wrote a post saying, I think GLP-1 is more impactful on the real economy than GPT-5.
0:44:10 I just think people reducing their, the fat economy or the diabetes industrial complex is
0:44:12 just enormous right now.
0:44:19 And if people, you know, if GLP-1 were to permeate the households like I think it’s possible, I
0:44:23 think that’s going to have a bigger impact on people’s lives and quote, what we were talking
0:44:25 about before the real economy.
0:44:30 I think my, I don’t know where you are, but I’m with Trump, I just don’t get these policies.
0:44:36 I’m trying to figure out, it’s as if, if I wanted to elegantly really screw the economy
0:44:41 for the mid and the longterm and reduce our prosperity inch by inch every day, I think this
0:44:42 is a genius playbook.
0:44:47 Tariffs, cronyism, lack of respect for rule of law.
0:44:55 We’re going to place tariffs on people, young people feel bad because they can’t buy a home.
0:44:56 So what are we going to do?
0:45:00 We’re going to tariff drywall gypsum from Mexico and lumber from Canada and make building houses
0:45:01 more expensive.
0:45:06 I just don’t, it’s as if they look at every pain point and say, how can we rub salt in the
0:45:08 wound of this pain?
0:45:14 So I don’t, I have a difficult time understanding any of the rational or logic behind this or that
0:45:20 there isn’t quite frankly, more sort of small revolutions in our society.
0:45:23 What I would, you said something there that I thought was really powerful and I want to pose
0:45:25 on and that is America needs an economy outside of AI.
0:45:27 I think that’s really powerful.
0:45:32 And what you were saying before about data centers, not having that, not needing that many people
0:45:32 to build them.
0:45:34 They need even less people to operate them.
0:45:36 They don’t even need to turn the lights on during the day.
0:45:38 There’s just no one, no one’s needed there.
0:45:44 The story I’d love to get your feedback on that I think is the really big story right
0:45:46 now is Amazon.
0:45:47 I don’t know if you saw this.
0:45:50 Amazon just announced they’re laying off 30,000 corporate jobs.
0:45:56 And I got to think when they announce it, they’re going to, there was this seminal earnings
0:46:00 quarter that I can’t get over or call about three quarters ago.
0:46:08 It was Meta saying they’d increase their revenues 23% while decreasing headcount by 20%.
0:46:12 I don’t think any company’s ever done that because generally the way it works is if you’re
0:46:15 growing, you tell your head of HR to hire more people.
0:46:20 And I’ve said that AI is corporate Olympic and that it’s turned the switch off among CEOs
0:46:22 that they need to eat more or hire more to grow.
0:46:29 And I think Amazon is about to have one of those quarters where it announces great earnings
0:46:36 or great revenue growth with a huge destruction or decrease in costs, i.e.
0:46:40 people being laid off and their stock is going to surge.
0:46:41 Their stock and their earnings are going to surge.
0:46:49 We’re about to see this arbitrage of human capital arbed into greater earnings and a surge in some
0:46:51 of these information intensive companies.
0:46:53 I think it’s coming at Goldman, JP Morgan, all of those companies.
0:47:01 Anyways, your thoughts on Amazon in this kind of labor destruction or the announcement they’re
0:47:02 laying off 30,000 people at corporate.
0:47:05 UPS is doing the same thing.
0:47:08 Like, I think they announced that they were going to cut 20,000 jobs.
0:47:13 And I don’t know if it’s at the corporate level, but they actually ended up cutting 34,000 instead.
0:47:14 So even more.
0:47:16 Yeah.
0:47:19 And then Target, I think, is cutting 1,000 jobs.
0:47:21 GM is cutting a couple hundred jobs.
0:47:24 So I think we are going to see more and more of that.
0:47:30 And to the point of the investment banks, like all of the AI companies are launching their
0:47:35 AI Excel, like Claude Anthropics Model just announced that.
0:47:37 I think Perplexity has something like that, too.
0:47:44 I believe that one of the AI labs has employed former investment bankers to actually train an
0:47:47 investment banking version of AI.
0:47:56 And so I do think we are going to see the expedited attempt to replace humans, yeah, and at the
0:47:57 corporate level, too.
0:48:03 Like, that is one of the interesting things about AI as a technology is that normally technology
0:48:09 replaces what we might call blue-collar work, but this is going after white-collar work.
0:48:11 It’ll be interesting to see if it works.
0:48:17 I mean, Klarna and Duolingo, they were some of the first companies to let people go and
0:48:19 be like, we’re going to replace everybody with AI.
0:48:23 But then they had to hire people back because it doesn’t always work that well.
0:48:28 That’s the other funny thing about AI is it needs quite a bit of nudging still.
0:48:29 It’s still new technology.
0:48:34 But so, yeah, I think that’s going to be very strange.
0:48:41 And with that portion of the workforce being displaced, it’ll be interesting to see how
0:48:42 they respond politically.
0:48:45 You know, what they start asking for, what they want.
0:48:48 Right now, we have like zero regulation on AI.
0:48:54 And so I think if all the big companies start cutting their corporate workforce, we can start
0:48:59 to see a lot more groups begin to coalesce around the idea that there has to be some sort
0:49:07 of human AI partnership rather than companies just gutting people and giving jobs to technology.
0:49:10 We’ll be right back.
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0:52:47 We’re back with more from Kyla Scanlon.
0:52:50 We have our own problems.
0:52:54 I mean, the stock market, the NASDAQ, and the Dow Jones are doing really well, touching new
0:52:55 highs.
0:52:58 But it definitely feels like there’s a lot of political division.
0:53:00 People are more anxious.
0:53:04 You know, it doesn’t feel like the U.S. is a role model for the rest of the world.
0:53:08 But I struggle to point to another economy that’s doing better.
0:53:12 Do you spend any time thinking about China or the European economy?
0:53:13 Who is doing well?
0:53:16 Or also just a follow-up.
0:53:21 I’d just love to know any thoughts you have about the state of the Chinese economy right
0:53:21 now.
0:53:23 China is really interesting.
0:53:29 Like China, have you heard of Breakneck, Dan Wang’s new book?
0:53:31 Yes, I have.
0:53:31 Yeah.
0:53:34 I mean, he kind of captures it pretty well.
0:53:37 Like China has like an engineer economy.
0:53:39 The U.S. has a lawyer economy.
0:53:42 A lot of people have said that about other economies in the past.
0:53:47 Like the U.S. has always been this sort of lawyerly economy relative to everybody else being
0:53:48 an engineer economy.
0:53:55 And I think that’s pretty true, is that it feels like the U.S. is having all of this infighting.
0:54:01 And then China is over there like developing bullet trains, or I believe they just found
0:54:04 like a cure for baldness or something like that.
0:54:09 And so it seems like they’re able to like really capture technology and use it in a way that
0:54:10 the U.S. isn’t.
0:54:12 But like they have their own problems.
0:54:16 Like they are also staring down a demographic crisis, right?
0:54:21 And they also have the life problem where a lot of their young people don’t necessarily
0:54:22 want to work.
0:54:27 And so I think that’s an economy that’s really complicated and it works really well because
0:54:28 it’s a command economy.
0:54:30 The U.S. is not.
0:54:34 And therefore, it tends to flounder.
0:54:38 I think what’s disappointing with the U.S. right now is that we just have a bunch of money
0:54:41 going into like the dumbest things possible.
0:54:44 And that’s pretty frustrating relative to China.
0:54:51 Like China also just announced that the people who post information about certain sectors on
0:54:55 tech on social media have to have like degrees in the subjects that they’re talking about
0:54:58 on social media or else they get fined.
0:55:03 And I think that could be really useful in terms of the polarization on the division that we see
0:55:07 in the States is people actually being educated on the topics that they talk about.
0:55:11 And so, yeah, I mean, I think Europe is like a different case.
0:55:16 They’ve just been struggling for a really long time to find their footing, to grow.
0:55:19 They also are suffering underneath the demographic crisis.
0:55:23 Like, I think that’s the thing that everybody’s going to have to grapple with over the next
0:55:26 couple of years is we have a rapidly aging population.
0:55:29 The economy is going to have to change to accommodate that.
0:55:36 All of these economies and economies rely on an influx of young people to continue to grow,
0:55:38 as you’ve talked about.
0:55:41 And I just I don’t know how we’re going to fix that.
0:55:43 Like, that’s the number one thing.
0:55:46 That’s the number one thing I worry about is demographics.
0:55:49 And both China and the U.S. are suffering from that.
0:55:54 Specifically, the ratio of young to old is headed in the wrong direction.
0:55:55 Do you think we can solve that with immigration?
0:55:57 That’s one way to solve it.
0:56:00 It’s, you know, immigration or having more babies.
0:56:02 Having more babies is hard to incentivize.
0:56:06 You know, South Korea tried to pay people a thousand dollars and that didn’t really work
0:56:07 either.
0:56:10 So immigration, high skilled immigration is one way.
0:56:15 The Economic Innovation Group has a good paper on high skilled immigration and like how much
0:56:16 it does add to the economy.
0:56:21 Like it is a boom, you know, paying taxes, adding to the local community.
0:56:24 But yeah, the politics gets in the way with that.
0:56:30 So I want to pivot and talk a little bit about kind of Scanlan Inc.
0:56:33 And that is, I think a lot of young, we have a lot of young people listen to the pod.
0:56:39 And I think they probably have seen the ascent of your career and your relevance in the last 24
0:56:39 months.
0:56:41 And I think that is really cool.
0:56:42 Like, how did she do that?
0:56:51 So any, any tips for what platforms have been, you know, breakthrough for you?
0:56:53 What’s worked?
0:56:54 What hasn’t?
0:57:02 If someone thinks I would like to be the Kyla Scanlan of art or of fashion or of, you know,
0:57:08 of engineering in Europe, whatever it is, I want to be a domain expert.
0:57:09 I want to have relevance.
0:57:11 I want to be invited to conferences in Florida.
0:57:17 Like what, what has worked and what hasn’t worked is you’ve developed this.
0:57:18 You’re essentially an entrepreneur.
0:57:23 I mean, it’s, my understanding is it’s just, just you, or maybe, maybe not.
0:57:24 That’s just you.
0:57:25 No, it’s just me.
0:57:26 It’s just me.
0:57:28 And you put out, that’s extraordinary.
0:57:32 The amount of content and the relevance you have as a sole proprietor is really extraordinary.
0:57:39 Anyways, what advice would you have given yourself, your younger self, three or five years ago in
0:57:42 terms of where you would have invested more and where you would have invested less?
0:57:48 So I guess like very quickly, the way I got started was, it was during the pandemic.
0:57:53 So I had moved from Kentucky, where I’m from, to Los Angeles to work at Capital Group.
0:57:58 So a buy-side firm, you know, had majored in econ finance and data analytics and just really
0:58:00 loved teaching and like wanted to get a PhD.
0:58:02 But my professor told me to go corporate first.
0:58:04 And I was like, that sounds great.
0:58:10 Six months into that job, the pandemic hit and I was all alone in this 350 square foot
0:58:12 apartment in Los Angeles, had no friends.
0:58:16 And so I started making videos and the videos were weird.
0:58:22 You know, they were skits where I was pretending to be Jerome Powell, which I don’t know if anybody
0:58:25 has ever done besides me.
0:58:29 And I just, I just really wanted people to understand the economy.
0:58:36 And so I think like that is always my biggest piece of advice is like, do it in the way that
0:58:38 feels very authentic to you.
0:58:45 And so for me, it was like these really bizarre, strange skits where people were like, oh, I didn’t
0:58:49 know, like you could have fun and talk about economics at the same time, which is what I was
0:58:50 trying to do.
0:58:57 And I just had a big, I still have a big passion for educating about the economy.
0:59:01 I think it’s a total disservice that we do to the public, sending them out into the world
0:59:03 and not teaching them things.
0:59:07 And so I started my company officially four years ago now.
0:59:12 So I’ve been doing this for what feels like a long time, but really isn’t even that long.
0:59:14 And I just think it was consistency.
0:59:21 Like I’ve posted almost every day since, and I’ve written, you know, hundreds and hundreds
0:59:22 of articles.
0:59:23 I wrote a whole book.
0:59:29 So consistency, staying authentic to what you truly care about and messaging it in a way that
0:59:31 feels relevant to you.
0:59:37 And yeah, not letting the fear of being perceived get to you.
0:59:39 Like I’m an introvert.
0:59:44 It’s funny, like my friends from when I was growing up or think it’s so weird that I have
0:59:48 it’s like public lifestyle because I do prefer to research.
0:59:53 And so I think that’s the biggest thing is like there is a whole big world out there and
0:59:56 there’s people who want to see what you want to message.
1:00:00 You just have to do it in a way that feels good for you.
1:00:06 But if you last question, if you look at all of the distribution channels and platforms, whether
1:00:14 it’s YouTube or TikTok or Substack or your newsletter or books, I stack rank the things that have
1:00:16 worked the best for you.
1:00:20 If you were to say to someone, all right, you have a limited amount of human capital.
1:00:22 This is what.
1:00:28 So we started doing 15 years ago, me and my business partner, my old firm, L2, started
1:00:30 doing these videos called Winners and Losers on YouTube.
1:00:32 And it was just a breakthrough for us.
1:00:33 No one knew who I was.
1:00:35 No one knew who L2 was.
1:00:36 People thought they were funny.
1:00:39 Sounds a little bit like what you did with mimicking Jerome Powell.
1:00:42 So YouTube was seminal for us 10 or 15 years ago.
1:00:48 What has been, what platform or medium has really worked for you?
1:00:52 Well, what’s disappointing is it was Twitter because that’s where all the finance and econ
1:00:54 people went to go hang out.
1:00:55 It’s not that anymore.
1:00:56 Don’t post.
1:00:58 I mean, still post on Twitter, but be careful.
1:01:00 It’s really become bad.
1:01:04 Instagram reels, like the discoverability on there.
1:01:09 I know, you know, we kind of talk down on Mark Zuckerberg sometimes, but the platform is
1:01:10 still pretty good for discoverability.
1:01:13 YouTube is still, yeah.
1:01:17 And still, I mean, you have to, like, you gotta, that’s the thing is you gotta eat from
1:01:20 the, it’s the worst, it’s the worst, but it’s a tool.
1:01:21 It’s a tool at the end of the day.
1:01:22 Social media is a tool.
1:01:28 If you can interrupt somebody’s scroll with like really good information as you do about
1:01:33 like markets, economy, culture, like that is worth it to go and use these platforms for
1:01:34 what they provide.
1:01:37 But Instagram reels, a lot of people have sub stacks now.
1:01:39 I had like one of the first sub stacks, I think.
1:01:41 And that was really cool.
1:01:42 Like a decentralized newsletter.
1:01:44 YouTube is still really powerful.
1:01:46 Podcasts are really powerful.
1:01:49 Like that’s, I think, a really good tool.
1:01:52 But yeah, TikTok, maybe not so much right now.
1:01:57 But it’s still all the main platforms and kind of being in many places at once.
1:02:02 So I think they’re all equal in that regard, is you want to have as many touchstones as you
1:02:04 can with people because they’re all on different platforms.
1:02:06 But it’s sort of taking…
1:02:07 It’s an accumulative effect, isn’t it?
1:02:08 Yeah.
1:02:09 Sort of a flywheel.
1:02:11 Yeah, it is.
1:02:14 Social media captures us all that way, right?
1:02:15 That’s scary.
1:02:21 Kyla Scanlon is an economic commentator, educator, and founder of Bread, a financial education platform
1:02:23 reaching millions through storytelling and analysis.
1:02:29 She’s also the bestselling author of In This Economy, How Money and Markets Really Work.
1:02:33 So, Kyle, I think you are an inspiration.
1:02:37 And one of the things I tell people is we were one of the…
1:02:39 I found you on TikTok, I think.
1:02:40 And I remember forwarding…
1:02:42 I think this was like two years ago.
1:02:45 I remember forwarding the TikTok to our producer saying,
1:02:47 we have to have this woman on.
1:02:50 She’s just such a unique voice.
1:02:52 And I love…
1:02:56 One of the things I do like about these mediums is that raw talent does break through.
1:03:02 You didn’t have to go to CNBC or be a junior reporter at the Wall Street Journal for 15 years
1:03:06 and finally get your shot and then get guest appearances on CNBC.
1:03:11 And then at some point, like 45 or 50, finally get your own platform.
1:03:16 I really do think you’re a case study and one of the more positive things around social media.
1:03:20 And I’m so enjoying watching you have your career ascend.
1:03:22 I think it’s just fantastic.
1:03:27 And it’s got to give a lot of young people a lot of confidence to kind of bust out on their own.
1:03:31 Anyways, keep doing what you’re doing and very much appreciate your time today.
1:03:32 Thank you so much.
1:03:55 Algebra of Happiness.
1:03:59 Who controls the algorithms or do they control you?
1:04:04 When I first got on social media probably 15 years ago, you post something and you see how
1:04:05 many likes it gets.
1:04:10 And it’s really rewarding when you post something or a piece of content or a viewpoint that resonates.
1:04:16 I still get very excited when I see, you know, I put out a stupid meme or a statement
1:04:19 and it gets 10 or 15,000 likes.
1:04:20 It still feels really good.
1:04:25 And also it feels bad when I get negative comments.
1:04:30 And slowly but surely you start adapting and shaping your narrative and even your own thinking
1:04:34 to an algorithm designed by other people.
1:04:38 Now, you think, well, it’s OK to want to please the crowd.
1:04:41 Shaming is a very powerful concept.
1:04:47 And that is for the majority of our time on this planet as a species, if we were expunged
1:04:51 or expelled from the tribe, you would die.
1:04:55 We’re, you know, nomads and we need each other.
1:04:56 There’s a tribe of 100 people.
1:05:02 20 people do the hunting, 20 do the gathering, 20 take care of the kids, 30 build housing and
1:05:05 10 of the village elders that help make better decisions.
1:05:10 And everybody or almost everybody gets to live a lot longer than they would if they were on
1:05:10 their own.
1:05:15 So being expunged, expunged is the wrong word, being expelled or cast out from into the wilderness
1:05:16 meant almost certain death.
1:05:20 So that type of shame is really powerful and it hurts.
1:05:27 The problem is that the people deciding these algorithms and shaping the likes and shaping
1:05:32 your views and your narrative do not have your best interests at heart.
1:05:34 They’re not trying to promote a discourse.
1:05:36 They’re not trying to help you get more educated.
1:05:39 They’re not trying to help improve your self-esteem.
1:05:41 They’re trying to make more money.
1:05:49 And unfortunately, what the algorithms have discovered is that enragement and conflict create
1:05:51 engagement, more Nissan ads and more money.
1:05:54 So what happens is you put out something that’s cute with puppies.
1:05:55 The algorithms love that.
1:05:56 It makes people feel good.
1:05:58 It keeps them glued to their phones.
1:05:59 A lot of likes.
1:06:05 You put out something controversial, maybe even something aggressive, and it makes the
1:06:08 other side look bad or makes somebody look bad.
1:06:10 The algorithms really like that.
1:06:15 And they will elevate your content so more people get it, more people see it, and there’s
1:06:20 more likes, which creates a feedback loop where you think, well, the more aggressive, the
1:06:27 the more pointed, the more terse, the more puncturing I get, the more dopa I feel, the more reward
1:06:28 I get.
1:06:34 And slowly but surely, the narrative that you start to develop is one of being more terse,
1:06:38 more angry, more polarized, more puncturing, less grace.
1:06:43 And then the narrative, if you will, becomes a function of the algorithm, and the algorithm
1:06:44 owns you.
1:06:49 And you no longer dictate, you no longer own the technology, the technology owns you.
1:06:50 And I’m a victim of this.
1:06:57 I, there are certain issues I feel really strongly about, and I hesitate to say things because I
1:06:59 know I’m going to get a lot of negative comments.
1:07:04 And sometimes these comments are from bots that have been weaponized by people who don’t
1:07:05 share my beliefs.
1:07:06 Okay, fine.
1:07:13 Or I’m inclined to jump on a bandwagon and start saying what I know my followers will like as
1:07:13 a progressive.
1:07:17 And the problem is when we all start barking up the same tree, we all get stupid.
1:07:20 So where I’ve landed is the following.
1:07:22 I go to my role models.
1:07:26 I’m a huge, I have a small list of people that I really admire, and I try to model them.
1:07:32 Um, a couple examples, uh, Margaret Thatcher and Muhammad Ali.
1:07:39 And the thing I take from them is that the reason why they’re my role models, the reason
1:07:44 why I think they’ll be remembered in a hundred years was they were not afraid to put forward
1:07:49 a viewpoint and behave and acquit themselves at the moment in ways and with words and with
1:07:59 viewpoints that were wildly unpopular, wildly unpopular, but they did their homework and
1:08:02 they believe them and they were, they were their truth selves.
1:08:07 So the question I would ask is in the recommendation I would make in the script I’m trying to follow
1:08:10 is I don’t want the algorithms to own me.
1:08:16 If you just have positive feedback in your comments, if you’re just getting, if you’re
1:08:21 just stating, if you’re just putting shit out there that everyone agrees with and okay, you’re
1:08:22 not taking any chances.
1:08:23 You’re not being a leader.
1:08:28 I, I always say to myself, if I don’t have people pushing back on me means I’m not saying
1:08:28 anything.
1:08:33 If everybody agrees with me, it means I’m doing something that’s funny about dogs or I’m stating
1:08:39 the obvious and that doesn’t mean the comments don’t affect me, but I realized that if I say
1:08:44 something and it gets a lot of negative feedback, okay, learn from it, reflect on it, but it doesn’t
1:08:46 necessarily mean you’re wrong.
1:08:53 I hope that when I look back on the content that I have put out there, the people say, sure,
1:08:58 a lot of it was wrong, but he was in the, his heart was in the right place and he was intellectually
1:09:00 honest and he was unafraid.
1:09:03 And that’s the question I would put to you.
1:09:07 Does the algorithm own you or are you unafraid?
1:09:14 This episode was produced by Jennifer Sanchez.
1:09:16 Our assistant producer is Laura Janair.
1:09:18 Drew Burrows is our technical director.
1:09:20 Thank you for listening to the Prop G Pod and Prop G Media.