Transcript for Interview with Tyler Cowen on AI

Read the full interview transcript.

Johnathan Bi: DeepSeek is a Chinese AI model approaching the performance of the best US models, but trained at a fraction of the cost, and the world is in shock. My guest Tyler Cowen was the first columnist to break the news on DeepSeek, weeks before the markets themselves reacted. Tyler's surprising claim is that the very US chip sanctions designed to thwart Chinese innovation engendered this innovation. By restricting China's high-end chip supply, the US encouraged China to pioneer techniques and cost-effective training. In the beginning of this interview, we're going to discuss what this Sputnik moment has to teach us about effective policy, US-China relations, and how innovation actually works. And after that, Tyler is going to share his comprehensive forward-looking view on AI about how it will transform knowledge work, warfare, economics, and everything in between. Tyler believes that AI will radically split the population into two, with a small portion of people who are able to use the technology, leapfrogging the rest in all domains of work.

A new global super-rich class and everyone else. What I found most valuable about this interview then, are all the practical tips that Tyler sprinkles along the way about how we can stay ahead of the curve and not be made obsolete.

---

Johnathan Bi: Peter Thiel had this line where he said, crypto is libertarian and AI is communist, in the sense that AI benefits from this large-scale centralization of data.

Tyler Cowen: I don't think that's true. I'm not even sure that Peter still thinks it's true. Not meaning to speak for him, but we do see that say the FBI can now trace a lot of crypto transactions pretty readily. To be a criminal and use crypto is no real way to escape the law in many cases. I think when Peter said that the dominant form of AI was surveillance. And think that that's totalitarian, or at least autocratic is easy to see. But once you see that AI reshapes workplace relationships, knowledge, freedom of speech issues, it has a lot of further-reaching effects. And again, I'm not pretending to have exact predictions, but it's not really biased toward the status quo. I would say people are seeing that more and more. So if your country is ruled by a status quo and very intent on defending the status quo, they may be seeing more change than countries that are used to things changing more. So it's quite possible in the future, AI... I wouldn't say it's libertarian. I wouldn't say it's anti-autocratic. I would just say subversive of many status quos. Some of them good, some of them bad.

Johnathan Bi: Almost two years ago, US enacted a blanket ban on the most powerful AI chips restricting their sale to China. And in a recent column, you argued that this backfired. US policy succeeded in hampering China's ability to deploy high-quality chips in AI systems with the accompanying national security benefits. But it also accelerated the development of effective AI systems that do not rely on the highest quality chips, namely DeepSeek.

Tyler Cowen: If I had been President Biden, I probably would have done the exact same thing. But that said, sometimes you need to realize that what you tried didn't work. Now China might have accelerated its AI development even more with more powerful chips. But do I want China to be part of the same hardware network as I am or for China to fully develop its own independent hardware network and other innovations? It's not clear which one is better.

Johnathan Bi: Your column reminded me about how America unintentionally jumpstarted China's space program. So there's a Chinese man called Qian Xuesen who was born in the early 20th century. He was born and raised in China, came over to study in MIT. Caltech professor was a colonel in the US military, worked for DOD and was eventually a co-founder of JPL. But during the Red Scare, people were accusing him of communist sympathies and they put him under house arrest, Qian Xuesen. And he was eventually deported in a prisoner exchange swap with Korean pilots in China. And then when he went back, he jumpstarted China's entire space program as well as China development of ICBMs. If you look at talent migration between the world's superpowers, America is the biggest gainer of talent.

Tyler Cowen: Sure. Including from ethnic Chinese.

Johnathan Bi: Yes, including from ethnic Chinese. And so the general question for you is when an economic innovator wants to defend their innovations from an economic laggard, there seems to be two general policies, right? One is to open up so much to get all of their best talents to make them dependent on your hardware. But the other one is to cut everything off, not just on the hardware side, but also on the talent side. Which strategy do you see most effective in economic history?

Tyler Cowen: I want to make my bet on openness for the most part. We're not very good at choosing the right restrictions and enforcing them. There's always more direct forms of espionage. You're not actually controlling the technology or keeping it in your borders, so you might as well get the advantages of openness. That's my general feeling. I think in particular cases that feeling can end up being wrong. Were we too open with the secrets of the atomic bomb? Well, actually that was a remarkably closed program. Truly secret. And it was a big complex out at Los Alamos and America truly didn't know what was going on. But at the same time, those secrets still leaked out to the Soviet Union. So I'm pretty skeptical about these attempts to make it closed.

Johnathan Bi: I see. And in some sense, it's just a lot more fitting for the American system as a whole. Because everything around America is built off of openness. So I'm saying even if closedness is the best overall strategy, the cost it would take to turn the entire society into that would be just too great, right?

Tyler Cowen: We're not good at closedness. We're pretty good at openness. And in a sense maybe no one's truly good at openness, but we're probably better than any other country. So play to your strengths and hope that's the right thing to do is sometimes the best strategy.

Johnathan Bi: I see. I want to double down on what you just said there about the difference between protecting, for example, atomic bomb secrets or AI models. There seems to be very different challenges in how you protect these secrets. For example, people are claiming that DeepSeek was trained on distillation. Which is a method for our audience that you essentially have the lower level AI model like quiz the higher level AI model. And so that seems... If distillation can get you quite close to the leading models, that seems a lot more difficult to protect.

Tyler Cowen: That's right.

Johnathan Bi: Than the atomic bomb. And so that also makes a case for openness in AI, doesn't it?

Tyler Cowen: And just the number of employees at major AI companies, it's not like working in the Pentagon. I mean, there are security protocols, but they're nothing close to say what the CIA would have. And I'm not sure you could have very high-quality labs attracting the best people if walking in and working there felt like...

Johnathan Bi: Interrogation.

Tyler Cowen: Yeah. So that's another closed versus open decision. We've gone mostly in the open direction. I think I would have done the same thing, but we'll see, right?

Johnathan Bi: Right. I see. So two arguments for open now. One is that it's better fitting to the American cultural mores. And the second one is it's just the nature of AI itself and how it's different from... You can have 10 scientists working on the atomic bomb that just the field itself lends itself more to openness.

Tyler Cowen: And DeepSeek. It's online, it's there. It's embedded in consumer products like the American systems. So it's not like plutonium. Not at all.

Johnathan Bi: I see. Let's go back to the chips ban because one of the learnings you drew out is we need to think about the second-order consequences of different policies. What can a statesman do better in understanding the second-order policy effects?

Tyler Cowen: Well, if you're an American statesman, the best thing you can do is familiarize yourself with AI. My sense is remarkably few people in government are at the AI knowledge frontier. I don't mean as builders, but even just as users of the system. So just wake up, pay to access the best systems and spend some part of your day playing around with them. They will even help your daily workflow right now no matter what you do. So that's a very simple first step, but we're not even doing that. A critical point I make to people, and this may be time-dependent, but it is worth spending some extra money to have access to the best systems. Whatever they may be at a point in time. If you don't have that access, it's actually quite a bit harder to understand what is going on. So I know that not everyone out there can afford the best systems, but at least consider this as an investment. And the way it stands now, you can access them for only a month for a small amount of money, $200. Just try it for a month. If you're disappointed, okay, you're out $200, you'll at least have learned that you're disappointed. If it's worthwhile, you can continue. So not enough people are crossing that mental bridge of just saying, I need to try the very best. Apart from the direct services or usefulness of the AI, just as an educational experience.

Johnathan Bi: For themselves.

Tyler Cowen: For themselves, I recommend this to everyone, but the very poorest people I know, and I would just want to stress this point to our listeners.

Johnathan Bi: I see. Let me give you a quote from one of my favorite essays by René Girard on his philosophy of innovation. Not so long ago in Europe, the Americans were portrayed as primarily imitators. Then in very few years, the Americans became great innovators. Public opinion is always surprised when it sees the modest imitators of one generation turn into the daring innovators of the next. Until quite recently, the Japanese were dismissed as mere copiers of Western ways, incapable of real invention in any field. They're now the driving force behind innovation in more and more technical fields. At this very moment, imitators of the Japanese, Koreans, Taiwanese are repeating the same process. They too are fast turning into innovators. Hadn't something similar already occurred in the 19th century, when Germany first rivaled and then surpassed England in industrial might? Do you agree with the general message from this quote that imitation copying is in some sense a necessary first step to a country or a culture becoming a genuine innovator?