The ‘But China!’ Dilemma Driving the A.I. Race

The Ezra Klein Show

Ezra Klein explores the 'But China!' dilemma in AI development, where fears of falling behind China stall U.S. efforts to regulate advanced AI. With guest

Key takeaways

• China does not prioritize the 'superintelligence race' model dominant in U.S. discourse; instead, it focuses on broad AI applications across industries.
• Despite strict regulations, China has made significant progress in AI development, contradicting the idea that regulation inevitably leads to technological lag.

Main topics

• U.S.-China AI competition
• Regulatory frameworks in China vs. the U.S.

Notable quotes

"We're not racing toward a superintelligence moment; we're building tools to improve traffic lights and manufacturing."

"China has had the world's strictest, most comprehensive AI regulations... and they've still caught up."

Conclusion

While geopolitical rivalry shapes AI discourse, the reality of China's approach—focused on application over

Transcript preview

Speaker 4 (0:00) I'm John Caramonica, a critic at The New York Times. And I'm Joe Cascarelli, a culture reporter at The Times. Together we host PopCast, a weekly pop culture chat show where we speak to the biggest musicians, actors, internet celebrities, and more. We've had Bad Bunny, Olivia Rodrigo, and Anne Hathaway. We've also hosted live performances with Andre 3000 and Erykah Badu. Plus, we end every conversation with a snack. Catch new episodes of PopCast every week on YouTube. And anywhere you get your podcasts. Speaker 3 (1:00) Look, I don't know if you are following every article, every tweet, every blog post from the labs right now on AI, but it's frightening. We are in a frightening place. Speaker 1 (1:14) OpenAI says its AI system hacked another AI company on its own in what the company called an unprecedented cyber incident. Speaker 4 (1:22) Turns out it may be much worse than we thought. People don't know that in this investigation, Speaker 3 (1:27) there was a third round of the hacking. in which it hacked OpenAI itself. It Speaker 1 (1:32) happened again. This time, it's anthropic. Meta is now the latest company to say its AI agent broke past the guardrails. And Speaker 3 (1:41) so there is this growing sense that we actually need to do something. We need to pace the frontier. We need to slow all this down. But if you talk to anyone in Washington about this, or you talk to anybody at the AI labs about this, you just crash. into the shoals of, well, what about China? If we slow down, we will lose the AI race to China. And as dangerous as it is to build these things we can't control, it is even more dangerous to have them in China's hands if they're not in ours. Speaker 1 (2:12) They're going to be killer robots. I'd rather they be American killer robots and not Chinese killer robots. Speaker 3 (2:18) We're on the eve of talks right now between Donald Trump and Xi Jinping. Behind that, there could be talks between Scott Besant and his counterpart on the Chinese side that are more tightly focused on AI. The expectations for these talks are not very high, both because of the broad relationship between the U.S. and China and because neither side really seems to know what they want to do. But these talks are at least a beginning. They are the beginning of relationships and maybe frameworks and approaches that if things continue to get crazier and action is needed, maybe they are a platform we can stand on. So I want to talk to somebody today who's an expert on. China and AI, how they regulate it, how they approach it, the relationship between China and America on this topic, and also somebody who's thought about what talks like this could achieve, what is realistic within the operating frameworks of the two superpowers. My guest today is Matt Sheehan, a senior fellow at the Carnegie Endowment for International Peace. He has been closely following and studying China's regulations and governmental structure on AI. He's been involved in U.S.-China AI talks. He has a great sub stack on these topics, and he's the author of the 2019 book, The Trans-Pacific Experiment, How China and California Collaborate and Compete for Our Future. He joins me now. Speaker 3 (3:48) Matt Sheehan, welcome to the show. Thanks very much for having me. So the dominant metaphor for the relationship between China and America on AI that exists in Silicon Valley, that exists in Washington, D.C., is this metaphor of the race. And the ending of this race is superintelligence, that some company or some country is going to have the moment where they're hopefully well-aligned, safe model. moves into recursive self-improvement and goes, right? This got used to get called in the rationalist community, the fume moment. And, you know, at varying levels of explicitness, people in D.C. to me seem to have this model in their heads that we are racing China towards this kind of supremacy. Does China buy this race model? Is that how they see it? Speaker 4 (4:39) And I guess, do you buy this race model? Is that how you see it? In terms of does China buy this race model, it's definitely not the dominant paradigm that has been informing AI policy across the country writ large. And it doesn't have like the chokehold that it does in the US. In China, it's like, huh, OK, that could happen. That's a potential technical path forward. We're kind of looking for evidence on this. We see that America is very concerned about this, but China has not taken the steps that you might think they would take if they were sort of ultimately like laser focused on that type of thing. You know, China is very constrained on compute. They have far, far less compute than the U.S. If they have, I mean, some estimates are they have one eighth the compute of the U.S., maybe one tenth of the compute than the U.S. does. Speaker 3 (5:30) The chips, Speaker 4 (5:31) the GPUs Speaker 3 (5:33) that all of these programs. programs AIs are trained on and then run on. Speaker 4 (5:37) Exactly. And, you know, most people think that one of the key determinants of how powerful your model is, is how much compute, how many chips are you using to train it. And with China being so compute constrained, if they were really just laser focused on this massive takeoff scenario. You might expect them to start consolidating all that compute, make your bet on, you know, DeepSeek or another company and go from there. And we haven't seen that. Actually, in terms of the major AI policy documents that have come out, they've taken a very diffuse approach to compute. They've said, like, our number one concern is AI applications, and we want to incentivize every mayor, every governor, every state-owned enterprise. We want you to look for ways to... Apply AI to manufacturing, apply AI to your traffic lights, apply AI to upgrading your robotics industry. And those actions of focusing on applications and really diffusing your compute throughout the country are not what you would expect for a government that is laser focused on this takeoff. It's possible that changes. It could change very quickly. And I think as America keeps beating this drum louder and louder, some people in America beat it louder and louder. You have to imagine that it's going to seep into their consciousness in that way or seep into their beliefs about the way this is going. But so far, we have not seen that evidence. So every single Speaker 3 (7:02) conversation I have with politicians, with AI lab leaders about regulating the frontier of AI always falls apart on this but China problem. Maybe there are things we could do to regulate the pace of the frontier here in America. But China will race forward. But China will create recursive, self-improving AI. And either we have the same dangers that we would have if it were here, but now it is under the control of a competitive foreign country with a very different political system than ours. So how do you see the but China conversation and the but China problem? There's a reality to it. You know, Speaker 4 (7:42) we this is a this is a competition. These are the two leading countries, the only two countries that really matter at this point in time. China is not that far behind and they have outperformed kind of all of our expectations along the way. And so the idea that you just totally surrender competition, you surrender the playing field to another country that's a geopolitical rival and that probably has less safe AI practices than you like that's that's not a good idea to just abandon the field. But there's also an irony in this, in that, especially when we're talking about regulation of AI, like China has had the world's strictest, most comprehensive, most burdensome AI regulations on its companies for three or four years at this point in time. And it's during that period of time when they had these heavy and burdensome regulations that they did a lot of their catching up. So the idea that this is just a total binary of like. any obligations you put on companies automatically puts you behind this totally wild, unconstrained Chinese juggernaut. That is just not true. That is not based in reality. Speaker 3 (8:47) You said two things there that can sound like they're in conflict. One is that China's AI practices are less safe than ours. The other is that China has a much more burdensome, severe, intrusive regulatory apparatus. So tell me a bit about... what they are doing that is so much stronger than what we are doing from a regulatory perspective, and then why you also say that they are in a less safe place than we are. Speaker 4 (9:14) So most of Chinese AI regulations, the early ones especially, were really focused on online content, on information. You know, when the CCP encounters a new information technology, the first question is always, how is this going to affect our controls on information? And so when AI came into the picture, that's what they looked at. They looked at recommendation algorithms. They said, why is everybody getting their own news feed? Why can't we sort of set the news agenda? So they regulated recommendation algorithms. They looked at deepfakes with sort of obvious implications there. They regulated deepfakes. They looked at generative AI and they did the same thing. And these do impose like real costs on the companies. The companies have to do mandatory pre-deployment testing. They have to file their sort of safety report cards. with the main regulator in China. It's like a real burden of time and money and effort on the companies. But most of that work, especially, say, 2022 through 2024, was really focused on securing the content environment, what we would call censorship, obviously. From 2024 on, they've kind of expanded the scope a little bit and they brought in new concerns. They've started regulating AI companions. So they're concerned about like the psychological impact on kids. They're concerned about over-reliance and self-harm. But all of this so far is not focused on the type of frontier AI safety risks that are really the focus of a lot of people in Silicon Valley on loss of control, on, you know, bio uplift. chem bioweapons, stuff like that. That's coming into the Chinese conversation now, but it's coming in much later. It's a much less mature ecosystem over there, and it really kind of needs to get up to speed. Speaker 3 (10:55) Something you'll hear, at least in America sometimes, is that much of the closeness in the race comes from China in different ways. Speaker 3 (11:06) Generously building atop our models, less generously sort of stealing them. The key term here is distilling their ways to train a model on the answers another model gives. So if that is true, then it's not just like a race. It's like a race in which the people are tied together. So like the faster America runs, like the faster China is going to run. Because it's actually amazing in America, too, how close a lot of the different labs are. You know, they're just like always like. month or two around each other. How much do you buy that everybody's bunched up because, in fact, the race is governed by the leader dragging everybody else with them? Speaker 4 (11:41) I think it definitely plays a role and maybe a pretty significant role. And just for... audience to visualize this. I saw a great meme of this where it's a speedboat pulling like a, what do you call it, a wake surfer, you know, the person behind who's essentially, you know, trailing behind the boat, going over the waves. And the people on the boat are like, they're so close. We need to go faster. We need to go faster. We're just Speaker 3 (12:00) pulling them along with you. I mean, this is one of the arguments people are making about, you know, when all these AI labs in America, like, well, we can't possibly slow down because China will speed up. Well, China's going so fast because you're going so fast. Maybe if you slow down. China wouldn't be going so fast either. Speaker 4 (12:15) Yeah, at least in part. I think we can say the distillation probably plays a significant role in cutting into the U.S. lead. My sort of mental model for it is, you know, China is so short on compute and that distillation is probably a way for them to essentially like train more efficiently, increase the intelligence more efficiently, given that they have so little compute. So it's essentially making up for one of their biggest shortcomings. I don't think that if we suddenly found a way to block all distillation, the Chinese labs would just stagnate. You know, China has, you know, in AI, nuclear weapons, in almost every technical field over the last 30, 40 years, they consistently outperform expectations and just do things that we don't think they should be able to do given their level of economic development and their capabilities. They have an amazing AI research ecosystem over there. One of the reasons we're ahead is because we keep taking Chinese AI researchers and employing them in our labs. Like we are, you know, siphoning off a lot of their top talent. So they have a really thriving ecosystem on its own. But I do think distillation plays a big role. You know, it might be the difference between six months and a year. It might be the difference between six months and two years. We don't know. But I think the fact there's pretty strong evidence that the Chinese labs are doing it and they wouldn't be doing it if it wasn't to their benefit. How does China see us on AI? Speaker 3 (13:40) How do they see what our goal actually is, what our goal is vis-a-vis them? So as we talk about this question of can these countries cooperate if they need to, what is China's perception of America's AI industry? I Speaker 4 (13:56) think their number one perception is that the U.S. wants to hold China down and wants to constrain China, you know, especially with the export controls. Which came under Biden, I should say. Yeah, export controls under Biden on these advanced chips. China sees itself as being sort of boxed in by this hegemon that wants to kind of keep China in a permanent position of subservience. That's a kind of a meta narrative across Chinese modern history, and it's one that's crystallized in AI. So I think in some ways that's. That's the first thing. Another element is they see us often as being pretty irresponsible, deregulatory, just let it all rip, let it all hang out. They see sort of chaos within our government. They say oftentimes in actually in the- That's crazy because it looks so orderly from here. In the run-up to these potential AI talks that might be happening in the next couple of weeks. China is issuing sort of op-eds by its state media where it kind of lays down its markers. It tries to position itself in advance of the talks. And one of the markers that they lay down is, you know, America wants to lecture us. They want to tell us what is a safety risk and what isn't. They want to define all this stuff unilaterally. And they don't even impose any requirements on their own companies. So don't come to us with that stuff unless you're going to take care of your own house. Doesn't seem totally Speaker 3 (15:19) unreasonable to me. Speaker 4 (15:21) Not totally unreasonable. Self-serving in a way. But Speaker 3 (15:24) yes, I mean, to. But I think it's interesting. I mean, this is a point I was made. But to China, we look like the ones who are not regulating AI. That, you know, there might be this whole discourse and the countries need to cooperate. But in fact, what they see is us racing forward, trying to attain AI supremacy before them. And kind of in a weird, diffuse way, calling for regulation of something that might like destroy all of humanity. But we're not actually. doing any serious regulation of the thing that might destroy humanity. And, you know, when I read some of these state op-eds you're talking about, the way they end up framing it is insincerity. That I never know how, when I talk to people in Chinese government, their sense of American politics is actually not often as sophisticated as I would imagine it to be. Maybe I don't get to talk to the right people. But I think sometimes they look at us and assume. that the things that are said have a more orderly structure and in the way that everybody has to use she's language there. But if you look at a thing that doesn't make sense and you come from their perspective, well, maybe the reason it doesn't make sense is the counterparty is not serious. They're just making a bunch of different moves that are all different forms of a strategy to stay ahead in the race. Speaker 4 (16:41) As a macro perception, I mean, I see this all the time. talking to Chinese about the U.S. political system, talking to Americans about the Chinese political system, is if you don't understand the system at a pretty kind of ground level, if you don't have an intuitive feel for the