Why China Isn’t Worried A.I. Will Replace Its Workers

The difference in perspectives between superpowers is shaping the race for A.I. dominance.

Hosted by Ross Douthat

Produced by Sophia Alvarez Boyd

Mr. Douthat is a columnist and the host of the “Interesting Times” podcast.

The United States and China are really the only two countries that matter right now in shaping the A.I. future. As President Trump and President Xi Jinping meet in Beijing, there’s a kind of Cold War atmosphere, with people talking about an A.I. arms race. But who is winning? Are we even in a race at all? Kyle Chan, a foreign policy fellow at the Brookings Institution, says it’s hard to call it a race because the U.S. and China have very different A.I. goals.

China Doesn’t Worry About A.I. Like We Do

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Ross Douthat: Kyle Chan, welcome to “Interesting Times.”

Kyle Chan: Great to be here.

Douthat: So at the moment, there are really only two countries that matter for the A.I. future: the United States and China. Their leaders are meeting in Beijing this week, and the atmosphere is sort of similar to a kind of Cold War atmosphere, where people think and argue and talk about them being in a kind of arms race.

You are an expert on China and A.I., and we’re going to talk about that race: who’s winning, what winning even means, whether it even makes sense to talk about the U.S. and China in terms of a race.

But I want to start with a basic question. How is China’s current approach to A.I. different from the American approach?

Chan: It’s quite different, actually. In the U.S., there’s a particular focus on A.G.I. — artificial general intelligence — and to create something approaching an artificial superintelligence, some kind of almost machine god that can do virtually everything that any human can do ——

Chan: And more. That’s right.

Douthat: You want to get more. That’s the “super” part.

Chan: [Chuckles] Absolutely. And you can see that the amount of spending, the amount of investment, the amount of effort that the American Big Tech companies and their quote-unquote “start-ups,” like OpenAI and Anthropic — which are now close to $1 trillion each — are pouring into this is an indication that they’re making a big bet that they can get there at some point, maybe in the near future. That’s the race to A.G.I. in the U.S.

China is running a different kind of race. I would argue they’re running multiple races. On the one hand, they are trying to produce better and better A.I. models. They do want to try to keep pace with their American competitors, but that’s not all they’re focused on. They’re also focused on efficiency, making these models smaller, cheaper to run, easier to deploy. That’s one area.

Another area they’re focused on is diffusion — trying to get A.I. into the hands of as many users as possible — and part of that strategy involves open source. This involves kind of giving away your models for free. And that allows other people around the world, including in Silicon Valley, to download Chinese models and to also customize them and tweak them based on their own data, and to make them work in a way that’s more tailored to their own needs. That’s the advantage of open source.

Another major area that China’s focused on is applications. Specifically, robotics is a huge area of focus, both for the government and for Chinese A.I. companies.

But you don’t really hear so much about A.G.I. You might hear some of the Chinese tech founders talk about this, and they sometimes sound a little similar to their counterparts in the U.S. But overall, they’re much more focused on the nuts-and-bolts uses and applications of A.I. in people’s daily lives. That’s the key priority.

Douthat: So if I went to Shanghai or Beijing right now and spent a couple weeks there interacting with physical reality and digital reality, do you think I would notice a big A.I.-driven difference versus life in the United States? Just describe the everyday experience of this strategy, to the extent that it makes a difference in how people are living.

Chan: Yeah. So in the larger cities in China, you might see autonomous delivery robots dealing with package deliveries, food deliveries. In a restaurant, you might see a waiter robot bringing your food. This is not super, super widespread yet, but it’s starting to come about. Hotels, rather than having room service be delivered by a person pushing a cart coming up the elevator, it might be a delivery robot. You have of course self-driving cars. You might even have drone delivery for coffee or food.

But it would be a subtle but probably surprising difference to what most Americans experience in terms of their interaction with A.I. in the physical world.

Douthat: Let’s just pause for context, because you talked about the government versus the Chinese A.I. companies. I think most viewers and listeners are accustomed to the American situation, where you have a set of big companies, they have been extremely, lightly regulated by Washington, D.C., and just in the last year, we’ve started to get into dynamics where the Pentagon especially seems concerned about their national security implications. There’s talk about regulation, screening of models and so on, but basically it’s been a very traditionally American capitalist environment. Not a Manhattan Project or anything like that.

To what extent is China similar or different just in the relationship between the companies and what is obviously a much more powerful and often repressive state?

Chan: In China, the state is in charge. Or specifically, I should say the party state. The Chinese Communist Party and the various government agencies that they oversee, they’re the ones who set the rules. They’re the ones who ultimately are shaping the trajectory of China’s A.I. industry.

They have quite strict regulations — for example, requiring A.I. models to be registered in advance. They have certain content and censorship rules that must be followed. They have a whole host of ways to enforce their rules and have leverage over Chinese A.I. companies. And there are echoes back to a previous era where Chinese regulators cracked down on Chinese internet companies, for example.

That’s the overarching relationship, but that doesn’t mean that the Chinese A.I. labs themselves are just in lock step following whatever Beijing says. Ironically, China tried a more top-down model to technology in a previous era, and that failed miserably. It did not produce the kind of innovation and flexibility and agility in the marketplace that you would need to have cutting-edge technology.

Douthat: What era are we talking about with the more top-down approach?

Chan: That was, I would argue, going back to the Mao era. This is the classic ——

Douthat: Pre-Deng, roughly pre-1980s?

Chan: Exactly, yeah. That almost Soviet command-economy-style approach.

So what you have is sort of a hybrid model in China, if I could characterize it in a single word — a broader direction and guidance and certainly support from the central government in China as well as local governments on the one hand, but then also trying to create space for competition and innovation from the Chinese A.I. labs themselves, whether you’re talking about China’s equivalent of the Big Tech companies, like Alibaba or Tencent, the maker of WeChat, the popular super app, or you’re talking about China’s own A.I. start-ups, like Z.ai or Moonshot AI, which have actually become quite popular around the world.

Douthat: What are the Chinese equivalents of an Anthropic or an OpenAI right now?

Chan: That’s a good question. So maybe DeepSeek would be the closest. And then you have the smaller start-ups. And by smaller I mean like on the order of $40-to-$50-billion market cap. And those are some of the more successful ones.

But it’s hard to find that kind of middle ground. DeepSeek now is preparing to take in outside investment. Remember, they were actually not originally an A.I. company. They were part of a hedge fund, actually, that was trying to use A.I. to develop more sophisticated financial models. So they’re sort of a category unto themselves.

Douthat: And all of these companies, though, are operating under some basic constraints that don’t apply to U.S. companies right now, mostly around chips. Can you describe the landscape of constraint in China and what it means?

Chan: Yeah. I had mentioned earlier that Chinese A.I. companies are trying to run different races, and one of those was efficiency. Part of that is in response to the constraints that they’re under, in particular around compute and chips.

So remember, right now the U.S. has export controls on our most advanced semiconductors, basically made by Nvidia, and we stopped those from officially being sold in China. We allow the sale of watered-down versions, but the idea is that we keep the best and the most advanced chips for American A.I. companies in the United States and for allies and partners.

For China, that means that they don’t have access to the most cutting-edge A.I. chips. They have some Chinese domestic alternatives — and this is a big part of the story. One of the leading players in the space is Huawei, the heavily sanctioned Chinese tech giant that rose first in the telecom space, branched into smartphones and is now in pretty much every other industry — electric vehicles, clean technology and certainly now A.I. and chips. So China’s trying to build up their own capacity for developing A.I. chips on their own, not just designing them, but actually producing them.

The problem is, they’re just not quite as good as the Nvidia chips. And without that, it does put a lot of constraints on what they can do. So they’re trying to squeeze more out of very limited compute resources.

Douthat: Why aren’t their chips as good? I know this is a simple-minded question. Is it just that Nvidia is so awesome at engineering and China’s engineers, even if they have a Nvidia chip, can’t quite get there themselves? Talk to me like a non-chip specialist.

Chan: This is the $5 trillion question, which is currently, I think, roughly the market cap of Nvidia today.

There are a couple different aspects to this. One is actually the chip fabrication that is producing the chips. Remember, Nvidia doesn’t make their own chips. TSMC in Taiwan, they’re the ones that make the chips.

Douthat: Conveniently located not that far from China.

Chan: [Chuckles] That’s right. To the consternation of probably a lot of folks in Washington and maybe other folks dependent on those supply chains.

But TSMC has been pushing the boundaries for increasingly advanced semiconductors in a whole range of areas, and that includes A.I. And Nvidia, by partnering with TSMC, can combine some of the best design work out there with some of the best production capabilities.

For example, ASML, a Dutch company that maybe some people have heard of, it’s actually one of the biggest tech companies in Europe now. They make these extremely precise, extremely expensive lithography machines for printing chips, basically. And they’re the only ones in the world that can make this kind of machine.

They sell those to TSMC. TSMC can use that cutting-edge technology, combined with their own cutting-edge manufacturing processes, and work with Nvidia to produce these incredible state-of-the-art chips that keep getting better and better.

Douthat: So essentially, when we talk about the U.S. not allowing Nvidia to sell to China, we’re effectively talking about the U.S. cutting China out of a larger supply chain that runs through Taiwan, through the Netherlands, all around the world?

Douthat: OK. That’s interesting and very helpful. What does China have going for it then, in terms of A.I. build-out, that the U.S. doesn’t have?

Chan: Energy is absolutely huge in China. If you’re thinking about the broader A.I. stack — that........

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