Tyler Cowen on Why AI Hasn't Changed the World Yet | Odd Lots

Bloomberg Audio Studios. Podcasts, radio, news. Hello and welcome to another episode of The Odd Lots podcast. I'm Joe Weisenthal.

And I'm Tracy Alloway.

You know, not a novel observation here, but I do think that if like in early 2022 or late 2021, you had, someone had revealed to you all of the amazing things that we could do with AI these days, I think you would've expected that either the broader economy or society would be more different than it has been. Like by and large, you know, I think most people's jobs are done roughly the same way, sort of society still seems to operate, although a little, maybe a little bit worse every day. I don't know. But like, I just don't think like, It's a mind-blowing technology, and yet by and large, like, it hasn't had the economic disruption that I think many people would have guessed.

Maybe I'm cynical on this subject, but I always say never underestimate the human capacity for stasis, I guess, and making things much more difficult than they actually need to be. And putting up, you know, bureaucratic barriers, regulatory barriers, and things like that. So it's not, it's not that surprising to me, but it is true. You have a lot of economists out there who think there was going to be this massive productivity boost, right?

Well, it's certainly tech people. Like, I don't know, like economists, you know, they're like, oh, there were some, we're going to have a productivity boom. We're raising our estimates from 2% to 2.25%. And then you have, everything's relative. And then, you know, we talked to Cathie Wood one time and I think she, what did she predict? 20% real GDP growth for 20 years. Or you certainly have these people in Silicon Valley, deflationary boom, post-scarcity any minute right now. Some real gaps, I would say, between how a lot of economists think about some of these things and the numbers that an economists would be comfortable using versus maybe literally everyone else.

Like Cathie Wood, certainly.

Many others. Yeah.

You know what I think about is how different would your career and my career have been had AI existed in like 2008, 2006 when we were starting to, to blog basically.

It's a really good question and I don't know the answer because part of me thinks, well, you know, that whole path that was like defined my career, like would not have been there, would not have existed. Or no, no, maybe. But on the other hand, maybe in 2006 I would've been like, just like I was super early into blogging, super early into experimenting with AI news and it would look different, but maybe I would've wrote some different—

Different but the same.

Yeah, different but the same. You know, like I think it's, uh, it's pretty hard to tell.

One thing I know is like back then we were writing to optimize Google results, right? That was based, or, you know, like I know social media was disseminating stuff as well, but like Google was still the main platform for a lot of stuff. I'm sure if we were doing it now, we would be optimizing for ChatGPT or Perplexity or someone like that to actually pick up the content.

I mean, I think—

That's the audience now.

Yeah, it is. And I think like any, especially any like commercial publisher, right? That's trying to do it at scale. I think like a sort of niche voice expert could still have like their audience that comes to them directly.

Of course.

But like at scale, at scale for sure, every publisher is trying to figure this out. Anyway, we really do have the perfect guest, someone we should have had on the podcast years and years ago. I, I, it's almost surprising that it's just the first time we've had him on.

It is crazy.

It is crazy. But it is someone who I think is like at the intersection of everything that we're talking about because he's an economist, uh, he knows the tech really well. The tech people know him, the tech people love him. He may even be one of the, the preferred economists for, uh, this. I, I feel he is like, the economist that all the people in the AI world want to get his take. A longtime blogger, someone I, you know, like both of us sort of gave up on like blogging, although we have our newsletter, it's like close enough, but it's different than blogging. Someone who's stuck with the medium for a long time. One of the true original econ bloggers that I've been reading for over 20 years. We are gonna be speaking with Tyler Cowen. He is the host of the Conversations with Tyler podcast. He also obviously is one of the two bloggers at the famous Marginal Revolution blog. Economics professor at GMU, appreciator of ethnic foods all around the D.C., Northern Virginia, Maryland area. Someone known on the internet for a long time. Tyler, thank you so much for coming on Odd Lots. Really thrilled to have you here.

Hello. Happy to be here.

Amazing. What do you think about my initial assessment? How fair do you think it is that, like, had you known in 2021 how powerful these tools would be, maybe we'd be a bit surprised that by and large, like, business seems to more or less run the same.

I'm not surprised at all. So what I see right now is people using AI as an add-on to their preexisting work routines. Oh, you need to write a memo, you ask AI how to do it. You need to write a column, you ask AI to proofread it or fact-check it. And that works great. But those are marginal gains. What we really need to see a major impact is new organizations built around AI, and those will be startups. They will come only slowly. It will take, you know, 20 or more years before they really transform the economy. And in the meantime, it's a whole bunch of add-ons which are fun and fine. But that's why I think it's slow.

What can you tell us about the history of technology such that legacy organizations that existed prior to the invention of, and maybe potentially revolutionary new technology, have a hard time massively changing their workflows.

Well, you can take even very simple examples. So Toyota starts competing with General Motors in the 1970s. General Motors is paralyzed. It cannot really come back and adopt the new and superior Toyota methods. And those are not really that different compared to, say, AI. So there's just plenty, plenty examples. Old mainstream media could not cope very well with the internet. There are exceptions like the New York Times. Uh, Odd Lots podcast would be another.

Thank you.

But it's the norm. So we're seeing it again with AI. And again, you need a complete turnover of who and what is doing business for it to really matter on a big scale.

If you're, if you need that complete turnover and you need some time for AI to become fully embedded in a business model or for a business model to form around AI, what industry or what part of the economy would you expect it, I guess, to show up first in that sort of revolutionary way?

Well, we have obvious data on this and it's programming. You will hear people who do programming claim that say 80% of the work is now done by AIs. I suspect that's an overstatement, but there's no doubt at all that there's simply a lot of programming already done by AIs. When you have low fixed costs, a competitive sector, immediate feedback, you know, the revenue has to flow. Programming and also New York City finance. There's been quants in finance for a long time. Those quants are now, you could say, more AI-equipped than they used to be. And those areas already are being revolutionized.

I've heard, and we got some pitches to do episodes, which we should do at some point, but I've heard about like some law firms that are being like, like new AI law firms where there are lawyers, et cetera. But from the very ground up, the idea is perhaps there is some way to just get way more productivity if they start from the very beginning with some combination of lawyers plus AI models. It seems like that could be the kind of thing where maybe the legacy law firms are seeing some productivity gains from AI. There's probably some evidence you could find, but that a very, a new one with a totally different approach could deliver that, that big productivity boost that actually ends up changing the industry.

It's already the case, say, mid-tier associates are much less needed, but there's one big problem with law in particular, and that is the way large language models work now. You have to send your queries somewhere else. You can't just own and control and hold the whole thing on your hard drive. Now, I think within a few years' time, that will be very different. But until then, major law firms are extremely skittish about just typing in their questions and sending it, you know, to San Francisco. I don't actually think there's a risk, but when you think about how fiduciary responsibility works, they just don't want to do it.

Talk more about, I guess, privacy concerns and regulation, because this seems to be an area where if you are in a heavily regulated industry or if you're just in an industry that tends to be full of paranoid people like lawyers, it does seem like there's going to be a natural tendency to be very, very cautious when it comes to sharing data with AI. You're going to be worried about actual data ownership, the queries that you're sending to San San Francisco, as you say. Are those industries just inevitably going to be slow to adapt?

They'll be slow to adapt again until the point where they just control their own model and they, you know, hold it within the firm and no one else really can get at it. So what you need is cheaper models where a law firm can afford to have its own model, and I think that's a few years away. It's not a very long time away, but it won't come in 6 months. Uh, Sam Altman— I just did a podcast with him, and he said a privacy problem is AI queries are subject to subpoena, and he thinks they should have as much protection as, say, your conversation with your lawyer or your doctor or your therapist. I think that's a good idea, but that hasn't happened yet. And until it happens, or you get the whole thing on your own hard drive, progress in law is going to be slow. But once the progress comes, That's one of the areas where I think AI has the most promise. It's just very, very good at mastering a large corpus of text and organizing it for you.

It is interesting, isn't it? Where it's like, okay, if you were my lawyer, you and I could have a conversation and it would be not— it would not be, uh, it'd be privileged. Yeah, it would be privileged. Or, you know, one can have conversations with anyone. And as long as you're doing it on the phone or if you're doing it person to person, it's much more difficult to get that, you know, in discovery. Or I always think about this with, you know, public, public records of employees that sometimes you can get their emails through FOIAs, etc., but you can't get the content of conversations. It does feel— I hadn't really thought about this dynamic, though, that when you're using an AI, it is sort of like a conversation. And yet sort of from an evidentiary basis, it would be much more like an email.

I think when it comes to medical issues, there are many more people willing to share their data. Not everyone by any means. Some medical conditions are secret or people just don't want others to know. But I see many, many people I know typing in all kinds of things about their medical history to, say, GPT-5 and getting what are on the whole very good answers. It's like medical diagnosis for free, spreading now to the whole world. A lot of countries where people just don't even have access to good doctors at all. And I think that will be important more quickly than the law innovations.

Just as a thought experiment, what does all of this mean for insurers? Because I kind of think, you know, I think about a bunch of people typing in their medical information. I think about basically the explosion in data that we have nowadays. And it seems like the insurance industry would be one place that would really benefit from all this trove of additional information if they could access it?

Well, this is one of my worries about AI in general. I'm quite positive on what's happening, but as insurers get better and better information on their customers, this is just through big data more generally. It doesn't have to be current large language models. Uh, they know exactly how to write the risk and how to price the premium. And in a sense, for the buyer, it's not insurance anymore. So if we know your house is going to burn down with high probability and you have to pay the super high premium, you don't really have the benefits of the insurance. So some insurance markets might unravel if through big data the insurers learn too much about what's likely to happen.

Economists seem to be very consistent about the effects of technology on labor demand, which is that in the end it washes out, right? Some people— okay, there's disruption, but I'm going to save money because I used AI, but that means I have more spending power and then I'm going to buy something else that I wouldn't have bought had it not been for paying wages. And then that'll create demand for labor elsewhere. And so in the end, the idea that you could really have tech-driven unemployment at scale that is not transitory or not temporary is hard. A lot of economists seem to be intuitively skeptical of this idea, whereas you have people in the AI field, oh, 50% of the people aren't gonna have jobs. We need UBI, otherwise there's gonna be a permanent underclass. Could there be something different about AI such that it doesn't have the same labor market effects that past technologies have had?

I would say you understand me well. So the energy sector, there's gonna be a lot of new jobs taking care of older people. I think as AI produces more potential medical innovations, we'll need to test them. So the biomedical sector, testing clinical trials, there'll be a lot new jobs. I'm not worried about mass unemployment and most economists are not. And I agree with their perspectives, which I think you outlined pretty clearly.

What do you say though? 'Cause I have a feeling that when you're out in San Francisco, they don't see it that way. Like, and they talk a lot and some of them are more in, you know, UBI talk and permanent underclass talk and all of this stuff. Do they see your perspective when you make this case? What do they say? Or what do they, what are a lot of them seem to be missing about the logic that you spell out?

Well, I think more and more they're coming around to The Economist's point of view. So Andrej Karpathy, who was at OpenAI, you know, in the most important years, he just did a podcast saying he thinks adjustment will be slow, things will be fine. Will grow at 2-point-something percent. There won't be mass unemployment. And you wouldn't have heard that, say, 2 years ago. But I think as people see the models rolling out and as you mentioned, well, the real-world impact, it is stretched out in time, right? It's not all immediate. Earlier on, people had more the sense that AI was a kind of God box. Yeah, you just talk to it and it can magically do anything and convert that into results in the real world.. But if you think about your actual job, even if it's a highly intellectual job, so much of what you do is the interaction between your intellect, your physical presence, your interactions with others, your travel, many other things. And until we get to some far, far-off world where the robots are perfect copies of you, which I don't think ever will come, uh, jobs will be fine, but they will change a lot. And I'm actually worried about who will be the biggest losers I think poor people will do great. The very wealthy will do well. But people who are sort of upper, upper middle class will find this automatic ticket to a law or consulting job that assured they would be upper, upper middle class for the rest of their lives. I think a lot of that is going away already.

I think also no one would have expected plastic surgery, I guess, to be a beneficiary of the AI revolution. But if you think that what's going to matter in the future is like your personal presence.

Yeah, that's right.

And your network of social contacts. Then I guess we should all be working on looksmaxing. Yeah, absolutely.

Right. Charisma.

Charisma. Okay, noted. Everyone work on their respective charisma. One thing I was wondering is the impact of AI on public finances. I am not very good at tax policy. Joe knows this because I've complained about taxes to him repeatedly, but I'm thinking—

Maybe that means you're really good at tax policy.

But If you're thinking about where the value add of AI actually shows up in the economy, so, you know, presumably you get a productivity boost. We're not entirely sure how much that's going to be, but where does that additional output actually show up in terms of revenue for governments? How is that collected and how would you expect the distribution to vary across the world?

Well, I think in the United States, medium term, there'll just be much, much more healthcare.

Hmm.

Will be new drugs, new medical devices. We'll have to test all these things. We'll have to produce them. And that will be— it was already the case that those sectors were growing, but that growth will be accelerated. So that's where I think there'll be the biggest difference longer term. And people will live longer because we'll fix, at least partially, various diseases and maladies. So if you live to be 94, across a lifetime, you spend way more on health care than if you live to be 77. And that's yet further growth for the healthcare sector. But some things like medical diagnosis, that's already very cheap. Like, you know, a good large language model probably outperforms your current doctor, at least if you type in what's wrong with you properly.

But does that additional productivity or the output generated by AI, does that actually show up in additional taxation for the government?

Well, the healthcare sector generates an enormous amount of taxation revenue. I do think we'll have some sectors that maybe just become free in the same way that Wikipedia is free. So I could imagine, say, 10 or 20% of the music sector is music you create at home using your own AI, and it's a customized song for you. And maybe you paid a subscription for the service, but rather than, you know, spending more money on Spotify or a streaming service, You just build the music, and that's a partial substitute for some human-created music. I don't think human-created music will go away at all. People want to enjoy the human touch, the feeling that you're a fan of Taylor Swift or whatever. Uh, but there's going to be a lot of AI-generated music and art and many other areas, and some of it will be free. Uh, but that's not a problem from a revenue standpoint. So instead of spending money on, say, buying a picture, you create one digitally at home with your AI, you'll spend that money on something else.

I got to ask now, are you a Swiftie?

No, it's boring for me. It's a little too predictable. So I have to say I'm not, but I'm glad other people are. Let's put it that way.

Do you have a theory? Actually, let's talk. Let's just talk about music. Do you have like a theory of the Swift phenomenon? Like, is there a reason? What is it? Because it's just so— it doesn't— I don't know. What's your, what's your meta take on the, the Taylor, the Swifties and culture and society?

Well, it's super polished. And because of the internet, the very biggest of celebrities can be much bigger than before. And someone will fill a few of those slots. But I think also how she presents herself. She has the guise of being attractive without feeling threatening to other women, uh, and there's something all-American about her and quite generic. She doesn't rule out the fandom of that many people, and she's the one who's filled that slot. She's been brilliant at managing her career and seems to just stick at it and has an incredible work ethic. People say the shows are incredible. As more and more life goes online Who can give a good show? It's the charisma and looks point. Well, she seems A+ at that. I've never been to one, but I hear plenty of reports. And you put all that together and she's, you know, the megastar of the music world.

Do you think like culture, like there's this popular idea that culture is sort of dead, and I do think that is probably overstated, but you know, you look at movies and people have, people have observed this for a long time. It's just rehashes of franchises that have been around for 30 years. And I think if you look at Spotify streaming There's still this overwhelming tyranny of the boomer rock, et cetera. And this feeling that culture in many respects is this rehash that is very hard for new things to break out. I mean, Taylor Swift at this point is a decades-old phenomenon. Is that real in your view, or is that just people in the pundit class who have been lazy and not discovering new things and not actually putting in the effort because they're not young anymore and they're not going out and they say, nobody listens to new music.

Joe, are you just talking about yourself?

Yeah, I'm half talking about— I'm trying, I'm doing a little introspection here. Is this just me because I don't go to shows like I did when I was 20, or something changed?

But a lot of it is the pundit class. So you look at movies, I think it's perfectly correct to say the most popular movies today are pretty dreadful. And it used to be the case that the most popular movies were Godfather and Star Wars. Yeah, that's a big change. But if you look at moviemaking around the world, and in a given year list, say, the 25 best movies from all places, which may not even come to your multiplex. Every year you have an incredible list. I don't think they're worse than the movies of earlier times. I do think mainstream Hollywood is much worse. So in many areas, you just have quality moving more into niches.

By the way, I just want to say, the first time I ever encountered your work, um, prior to even having stumbled across Marginal Revolution, was at the bookstore in Austin finding a copy of In Praise of Commercial Culture. And I just feel like that book has held up so well. I mean, in the specific sense that there is so much mass culture these days, whether it's high-end Netflix TV shows, etc., whether it's A24 films, whether it's Beyoncé or Taylor Swift or some of these other big names who are simultaneously incredibly popular And I get that you're not a Swiftie. Neither am I anymore. But people take this— yeah, I, I like their country.

Once she left.

Yeah, once she left country. But like where people take these popular culture things extremely seriously as art and don't dismiss these outputs as sort of being trash.

Right now we're in a golden age for country and Western music and also horror movies.

Hmm.

Neither is really like my taste in particular. But it's easy to see what has gotten worse, and especially for critics, harder to see what has been getting better.

That's my sweet spot. Country and horror is perfect for me. But just on the culture point, I mean, I think the lack of culture argument, the one I hear the most is it's a lack of shared culture, right? So you do have like some giant monoliths like a Swift or a Beyoncé that everyone knows about. And, you know, they do have these large audiences, but broadly, we're not all experiencing the same media that we used to, right? Like, no one is gathering around the TV to watch the finale of, you know, some show that airs like once a week and has been going on for 5 years.

The exception is NFL football, which I don't really get it. But yeah, but it's not cultural.

Sports is outside of my expertise.

And the Super Bowl is cultural, right? It's a cultural event. You care about the advertisements. But the biggest of YouTube stars, which again, I would say is not personally my thing, But they can have bigger audiences than those older TV shows did.

Right.

Right.

Well, so what I'm getting at is it does feel like nowadays there's an ability because of tech to serve up very specific content and like niche content in streams. And the, the analogy that I like to use is, you know, everyone knows if you download Netflix for the first time, the first movie you watch is incredibly important because whatever you watch, you know, if it's a rom-com, you're going to be served up Kate Hudson films for the rest of your life, right? Like the algorithm looks at what you're watching and then it serves up that additional content. What does that mean for society? The idea that you have people, you know, basically funneled into smaller and smaller streams in some respect?

Well, a lot of the Netflix algorithm, it just directs you to slop.

True.

A lot of people have always wanted slop. Like people listen to Muzak way back when, and it was quite common. Or they would just listen to Top 40, which in some years was very good but often was pretty terrible, even in the 1960s. So what you can do today is basically watch not any movie out there, but you have MUBI, you can still buy DVDs and Blu-rays, uh, you have access to more cinema today, uh, than you ever have. So people will sort themselves, and I think it's from the point of view of cultural consumption, I don't think there's ever been a better time to be alive than right now.

I like that.

Well, a lot of people abuse that and go for slop. Of course, that's sad, but it's hardly new.

So changing gears a little bit, Tracy and I write almost every day because we have a daily newsletter that forces us to. And I really like having that because I don't know if I would write every day if I did not have that obligation., to deliver something in people's inbox that they pay for as part of their Bloomberg.com subscription. I love writing, but I don't know if I would do it every day if I didn't have this sort of requirement. I might just tweet. How do you— you've been blogging for over 20 years. How do you avoid the temptation to just fire off all your ideas via tweet and actually commit to the blog?

I'm never tempted to do that. I like to think things out.

I do too. I just don't.

When I write properly. Yeah, I've actually blogged every single day for over 22 years.

It's amazing. It's amazing. Most people gave up. And so what's the difference?

I don't feel it requires any discipline from me. The discipline is not writing more, like I have to restrain myself. So I guess I'm just weird. I don't think I have any, like, neat little trick or formula. It's one of these niches that you can do now that you couldn't do before. And I found my niche, as have the two of you.

Here's a slightly different question playing on that theme, but going back to the intro, how different do you think your blogging career would have been had chatbots existed, you know, 10 or 20 years ago when you were starting out?

I don't think we know yet. My intuition is that people still want to read human writers simply because they're human. And if the bot is as good as you, most of the world doesn't care, but that has not truly been tested yet. I think we'll see in the next 2 years, but that's what I'm expecting. Just like, I think, I think in music there'll be plenty of AI music. It might be, say, 10 or 20% of the music sector, but listeners will still want that human-to-human connection.

Do you think, you know, when Twitter came out, they called it a microblogging site as if it were just blogging but on a shorter basis. But I think it's fundamentally different, you know, in the early, the glory days of blogs, which we'll be talking about forever when we're all very old people, how good it was. You know, I think there was this sort of spirit of liberal linking with each other and idea exploration, whereas Twitter strikes me as much more conflictual and one-upmanship and so forth. Do you think there are fundamental, I don't know if political is the right word, but new communication paradigms have their own terroir, so to speak, in terms of the impulse towards collaboration or conflict, et cetera? And does that change society?

Yeah, I still like blogging and I'm sad people have moved away from it. Twitter, to me, it seems too meme-heavy, and meme-heavy media have more potential for racism, which of course is a big negative. And I see so many people who are driven crazy by being on Twitter, whether it's because they're writing on it or reading it, I'm not sure, maybe both. I don't want to name names, but it's a lot of people, and I bet you see the same ones that I do.

Also very sexist nowadays. I would just add, in unappreciated ways.

Many ways.

Speaking of sexism, the impact of AI on economics. Talk about that. Economic institutions, you know, famous for modeling and spend a lot of time with numbers and things like that. Is that all just going to be replaced by AI?

Not all. So I think what human economists will do is put more and more time into gathering data and feeding it to the AIs. The returns to doing that will be very high, but the actual econometrics statistics— humans will maybe set up part of the problem, but the hard, boring routine work will be done by the machines, as to some extent it was already the case. And this will be a way to make a lot of progress rather quickly.

Do the actual economic statistics or data points that economists collect— do some of those need to be changed or thought of differently in light of the AI era?

Well, I don't know. Eventually they will need to be. But I would say any period of radical change in history, your statistics are less useful. It's not that the people creating the statistics are making some mistake. You just cannot capture every way the world is changing. And index number comparisons require the basket of goods be relatively close to constant. And at some point that doesn't hold anymore. And we'll be faced with that. We'll deal with it. I would say the current statistics we have, they're more underrated than overrated. So they're actually pretty good. I'll be glad when we get them back again.

This is another thing. The tech people you talk to, they must think like GDP is terrible. It doesn't capture all this stuff, all this value that we can't price. I'm sure you've had conversations explaining to many AI workers that GDP is not the worst statistic in the world. I want to go back though to, so, you know, you mentioned like on Twitter, right? You say something, someone posts a meme, they dunk on you, they make fun of you, they whatever. Your chatbot won't do that. Like if I'm having a conversation with ChatGPT, it's never going to respond to me with a meme sort of indicating one day it might, one day it might, but that I'm a moron.

It'll learn your language, Joe.

Yeah, but if anything, it's too obsequious, right? I mean, the issue is Like the online world has become this very like sort of competitive, conflictual world. And then I go to the chatbot and my complaint is literally the opposite. It doesn't challenge me enough. It's too obsequious. Every question I ask, it's a great question. Sometimes I wish it would call me a moron a little bit more. But what does it change about the world? And we know that like many people's brains have been broken by social media and that probably has downstream effects on how our politics operates these days. What does it do to the world if we start inhabiting these chat environments where they're just very sort of polite? And every time you say something, it says, yes, great thought, Tyler. Great thought, Joe. Would you like to expand it? You asked the perfect question. What do you see that having sort of second-order effects on how society operates?

Well, that's the 4.0 model that does that. The newer models like Claude 4.5 and GPT-5 They're more objective and that's better, but they never make fun of you.

They never will like say you are a moron. How could you possibly, how could you possibly ask such a dumb question? You are obviously so out of touch for having to ask this. This is like a very, in some respects, this is a very positive change from many of the conversations that I've had from typing into a computer.

Oh, it's great. I think people should be nicer to each other and I think they're the most objective media source the human race ever has had. If you ask it about, say, vaccines or conspiracy theories, it basically gives you the right answers.

Well, one thing that they don't do, and I mean, I do think they can be trained to be mean to you and to insult you to a certain degree, and you can decide—

it could be, but I never encountered them.

Try, try harder to get that more readily on tap, right? So we spoke to, um, the business chief business officer of Perplexity, Dmitry Shevilenko. We spoke to him recently, and he was saying that one thing chat models can't do is express a natural curiosity, which I thought was kind of weird coming from him because Perplexity is the only model I know that actually throws out those additional questions if you query it, and then it comes up with, would you like to have more information on this point, or are you thinking about this now? But there does seem to be an element of creativity perhaps that is lost in some of these LLMs. How much does that change things in media? The idea that, you know, the models are going to spit out something that's sort of predestined in many ways.

Well, that's what most humans do, to be clear. But it's now the case that on a regular basis, the models, say, can prove new theorems in math or discover new potential drugs. And keep in mind, you know, a year ago these things thought the word strawberry had two Rs, and now they're winning gold medals in Math Olympiads. So a year or two from now, maybe we don't know how much better they'll be, but I don't think they're going to have any problems being creative. Certainly more creative than humans on average.

So now I have to ask, since we're talking about being mean or nice to the models and them being mean or nice to you, do you say please and thank you in your LLM queries?

You know, I used to, and then Sam Altman said, well, it costs us just a little bit of money because of the extra tokens. And then I thought, I'll hold off on this, but I have this preexisting record of saying please, and it knows that. And then it knows I stopped when Sam said to stop. And I think I'll get points for both of those decisions.

See, I actually find if you're slightly meaner to the models in your queries, they perform slightly better, much like interacting with Joe.

No comment on that. You know what I do? I have said, which is all like, I'll have a query and it'll respond and I'll say, that was a little on the nose. Yeah. Wasn't it? Like, It would like it over—

I'll say do better perplexity. And then it does.

Yeah, I've said like do better. I've said things like that. It's like, this is really on the nose. This, this response was a little bit trite, don't you think, etc. Like, I do feel like I've gotten more comfortable at— let's be, let's be real here. You're not doing— you're not doing your best job here. What do you think is like—

it's interesting.

They like— I get that they, they win the gold medals in the math and etc. Like I've had so many conversations with the chatbots that are on some level like mind-blowing, the capabilities. I've never seen a chatbot query that is like interesting. Like that is like, oh, that is like a really interesting, maybe one I can think of, but there was like a really interesting thought. I feel like my children still say on a daily basis more like interesting things that get me thinking than I've ever gotten from a chatbot. Does that resonate to you at all?

I don't know.

I feel like you've said so many more things in this hour than any interesting thing, like actually like interesting ideas than I've ever got from the hours I've spent playing with ChatGPT or Claude.

But you know, I use mine a lot for music. So if I'm going to listen to Sibelius's Fifth Symphony, I'll just ask it, what should I listen for? And I'll say, this is Tyler Cowen asking, which I hope raises quality of the answer. It knows a lot about me.

Yeah.

And what it gives me to listen for, I find, is better than any human source I can access readily.

Better. I— that I agree with. But like, does it make a connection? Does it like tell you something about Sibelius's music that is like, oh, that's a very interesting— that's a novel way of thinking about what makes it profound? These are the things that I rarely ever encounter. Something that's like, oh, that is an interesting thought. Whereas I feel like if I were talking to a musicologist for an hour, I would get infinitely more like actual insight into something that makes the music special, something I hadn't heard before.

I don't know if it's novel because I don't really know the Sibelius literature. Uh, but most musicologists I find pretty boring and I find, say, GPT-5 on a classical symphony quite to the point. And whether or not it's original, it's not that important to me. It helps me listen to the music better.

Yeah.

And it's certainly original relative to the other sources at my disposal, say Wikipedia or what I could Google to. So I think for almost all purposes, that's enough. Does it have a truly original idea in the sense that Einstein's theory of relativity, when he came up with it, was original to him? I don't think so. That may come in some number of years. But again, for almost all purposes, that's not what we need. We need something better. Than our preexisting state of knowledge. And on that, I think it just cleans up.

So I just asked Perplexity what music I should recommend to Tyler Cowen. And it said that in order to recommend effectively to Tyler Cowen, I need to look for underappreciated recordings and obscure things that no one except him might have ever heard about. Um, and good answer. And it recommended, I mean, Boy Genius seems pretty on the new— on the nose.

Yeah, right.

Um, reggae acts like Toots and the Maytals.

Oh yeah, this is so—

this is—

I've seen them in concert.

Tyler's probably listened to all 20 of their records.

So it's just scraping stuff that you've already talked about.

It's not, it's not even trying.

Yeah. All right, well, but you need to make the prompt more exacting.

Rule out anything Tyler has talked or written about. Give me something he doesn't know and try GPT-5 in the pro mode Yeah, and I think it will succeed.

Well, so on this note, this is something I've been asking everyone, but like, what is an example in your mind of a really good prompt or one that sticks out to you that has generated something that, you know, maybe you didn't expect?

You know, Dwarkesh Patel once wrote a very good prompt and he shared it with me. When I interview some podcast guests, it's really a long prompt. It's, you know, hundreds of words. And it asks, what questions should I ask them? Then it goes into great detail. It should be a unique question. It should be a question they were not asked anywhere else. Then it's give me what you think their answer might be and what would be my follow-up question. And yeah, give, you know, give me some cases where you think their answer might be wrong. And it goes on and on. And you run that through the very best models, I think you get good results.

Yeah, no, I've, uh, I, you know, I've run, uh, transcripts of the podcast before and I say like Well, where should I have pushed the guest harder on? What were the weak answers that they— what were the inconsistencies that the guest had over the time? And I've found it to be a very useful exercise for things like that. So I do think like that's the thing, which is first, it is, it is objectively impressive on many of these fronts. And I would say objectively useful if you do sort of a detailed prompting. I'm just curious, what do you— what's your like As a prof— from the professor perspective, what do you think is the right way to think about how students will be using ChatGPT? I mean, I know that there's a million opinions in academia about, well, what's the right way to test now? What's the right way to deal with essays, etc.? How are you thinking about some of these challenges?

We should devote one-third of all higher education to teaching students how to use AI. And right now that's close to zero. So we don't have the faculty who can teach it as part of the problem. Often the students know more than the professors.

Yeah, I'm sure. But what about like things like—

we need to restructure radically what we do because future work will be done with AIs. So that's the thing to teach.

But like, so just to play devil's advocate, like intuitively, I still feel like there is value in long periods of time cutoff reading. Where you're not looking at devices, where you're training your body to sort of be disciplined and pay attention and focus. I still think memorization of facts and numbers and dates and places and names is very useful in actually having them in your head, et cetera. Does that seem right to you or is that sort of retro thinking on my part?

No, strong agree. And most of all writing. But that's the other two-thirds of higher ed, right? I said one-third should be AI.

Oh yeah, so tell us about the other two-thirds.

We should, with or without AI, just teach students much more and much better how to write. Most people can't write. Writing is thinking. We should do much more to teach writing and test writing. And now with AI, that has to be face-to-face in a controlled environment, or people are just going to cheat. So that we should have doubled down on to begin with.

Yeah.

So that and just numeracy and basic issues like how to manage a portfolio, what kind of mortgage to take out. There are classes that cover those things, but I think they ought to be front and center of any curriculum. Basic finance, basic life decisions like how to choose a doctor, how to prompt the AI, you know, for diagnosis, whatever, are relatively neglected in a lot of education. That to me just seems crazy.

I want to ask one market question before we go, which is obviously there's a lot of talk about an AI bubble at the moment. And I think the concern from a lot of people is when you start talking about a new technology as revolutionary, when you start talking about how, you know, the effects are basically going to be infinite and the market size is hypothetically the entire world, there's a risk that, uh, expectations overshoot reality, right? And we have seen some people voicing their worries about that right now and a little bit of nervousness creeping into the market in terms of valuations. Where do you stand on the AI bubble? Do you see signs of froth or do you think most of the CapEx spending is, uh, justified at this point?

I don't like the word bubble. I would point out that tech sector earnings are exceeding tech sector capital expenditure. This is not mostly debt financed, so we're in less trouble than many people think. It wouldn't shock me if a lot of these efforts lost money. That was the case with the railroads, the case with the internet, case with most things humans have done. But I think it will endure. It's not like Pets.com where the thing just gets swept away. These are incredibly well-capitalized, highly skilled companies where the CEOs and/or founders are quite committed to doing this, and they're going to see it through, and they're going to succeed. But does that mean every share value will go up, or NVIDIA ends up being worth $10 trillion? I don't know. I wouldn't necessarily predict that. There's always ups and downs, uh, but this is clearly a very useful thing, and we're gonna— we as Americans, we're gonna make it work, and we're way ahead of the rest of the world. Like, three-quarters of all AI compute is in this country. That's incredible. We're what percent of the world's population? 6% or I don't know, but way smaller than 3/4.

GPT-5 on thinking mode says you should listen to Michael Gulizian, who does dreamlike acoustic guitar using an open tuning. And it said that given your affinity for guitarists like John Fahey and Leo Kotke, you'll appreciate him.

Send me that answer. It sounds excellent. I haven't heard of that person. I do very much like Guitar with open tuning.

Kishore Amonkar, a Hindustani vocal singer. Things you'll like. Sun O, M.D. Badru'l-Haq. I'll send you this list. And Caterina Barbieri, modern modular minimalist electronic composition.

So I will buy some of these, but Sun O, I already know.

Wait, how about a human recommendation?

Give us a recommendation.

A human recommendation, since you said that country is pretty good right now, but I guess you personally aren't that into it. But have you tried Orville Peck? I think there's a new album out, out, uh, this week, I think.

What kind of music is it?

Country, but like a very modern type of country. I've tried to get Joe into it, but, uh, I'm still working on it.

I like some country, and I love old country, so Hank Williams, Johnny Cash, Jed Adkins, period.

It has a vintage tone to it, but with a modern twist. Try Orville and then get back to us about which was better in terms of the recommendations.

Tyler Cowen, Tyler Cowen, thank you so much for coming on Odd Lots. Long overdue conversation. Uh, really appreciate you taking your time.

Great to chat with you both.

Tracy, a lot to pull out from that conversation. I think it's very interesting that early observation he made about sort of legacy institutions and whether perhaps some of the, eh, sort of lack of revolutionary impact yet is just about that metabolization process into the types of companies that could theoretically absorb them.

Yeah. I mean, I, I think that's exactly it, right? So companies are using this mostly as an add-on to existing workflow. You're not going to get the huge productivity boom until companies are sort of centered on—

build from the ground up.

Yeah, which, you know, is probably going to take people who grew up with the technology rather than old people like you and I, like you and I, who just adopted it. The other thing I was thinking about, first of all, insurers are sort of a pet interest of mine at the moment, but I do think like they are emerging as some of the really big winners from a lot of, like, I guess the data saturation of the world right now and the increased sophistication of analytical models and things like that. And that'll be very interesting to see how it shakes out. And you could, if you, if you took it very, very far as a sort of thought experiment, you could start to say that like, well, the insurers are going to be a more important actor in terms of setting social standards and regulations in the future because they're the ones with the data doing all the modeling. Yeah. And saying, like, you have exactly an X chance of being in a car accident and therefore you must do the following things, right?

I thought also, like, I hadn't really thought about, you know, subpoena ability. I think it is a very big issue. But it is interesting, right? Like, it is a little weird that you and I could have a phone conversation. Now, if you're under oath and they say, what did you talk about with Joe? I expect you'd probably tell the truth. Unless it was very bad for me. And I would hope that you would lie.

That's right.

I would hope that you would. I would hope that you would.

That's your hope.

I would hope that you would.

Perjure myself to save Joe.

Yeah, I would hope that you would perjure yourself. But like, you know, you theoretically could get away with it. So, yeah, well, I mean, we have an email. There's no chance. And it's sort of interesting. It's sort of— it's always seemed a little bit arbitrary to me, but it is interesting to think about like, okay, can we have a conversation with these entities? And like, why do we have to leave it? Digital record and where are these going to be stored? And I do think in areas like health and law, which are obviously— not obviously, but sort of intuitively low-hanging fruit for productivity gains— how much have we not seen, just in part because we're still sort of negotiating the transition process as a society? What are going to be the new rules and norms about this stuff? Where it's going to be housed, et cetera. I think that's actually a sort of very interesting question or space. This is the space to watch, so to speak.

Now that I think about it, we probably should have discussed some of the regulatory framework around all of this a little bit more. But next time.

Next time.

But the other thing I've been thinking about lately is economic statistics.

Yeah.

In a world that's increasingly driven by AI. And I know that we had the big productivity discussion.

Yeah.

And technology in relation to technology in like the sort of early to mid-2000s. I'm not sure that ever actually got settled. But I very much expect that the AI economic statistics conversation is going to be even like wackier because I'm not sure how you do things like quality adjustments for something that like suddenly comes with its own brain.

Yeah.

And stuff like that.

So no, it's going to be super weird. I did the— I don't know, in my mind I have like a very— these images of like Tyler getting a tour through the, you know, ChatGPT offices and The people asking, it was like, and him having to explain that, you know, we're not going to have 20% GDP growth, that maybe 2.5% or sorry, productivity growth. And actually GDP isn't really that bad of a measure. It more or less captures the size of the economy, even if a lot of internet things are free. Like some of these classic conversations. I would like to be a fly on the wall for some of those.

Tyler Cowen in defense of GDP.

Independent. Yeah.

All right. Shall we leave it there?

Let's leave it there.

This has been another episode of the Odd Lots podcast. I'm Tracy Alloway. You can follow me @tracyalloway.

And I'm Joe Weisenthal. You can follow me @thestalwart. Follow our guest Tyler Cowen. He's @tylercowen. And of course, check out his podcast, Conversations with Tyler. In addition, of course, Marginal Revolution. Follow our producers Carmen Rodriguez @carmenarmendasho, Bennett @dashbot, and Cale Brooks @calebrooks. For more Odd Lots content, go to bloomberg.com/oddlots. With the daily newsletter and all of our episodes. And you can chat about all of these topics 24/7 in our Discord, discord.gg/oddlots.

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