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

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Ezra Klein (1:05)

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. Like we are in a frightening place.

SPEAKER_3 (1:18)

OpenAI says its AI system hacked another AI company on its own and what the company called an unprecedented cyber incident.

SPEAKER_1 (1:27)

Turns out it may be much worse than we thought.

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People don't know that in this investigation, there was a third round of the hacking in which it hacked OpenAI itself.

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It happened again.

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This time, it's anthropic. Meta is now the latest company to say its AI agent broke past the guardrails.

Ezra Klein (1:46)

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. They're going to be killer robots.

SPEAKER_1 (2:18)

I'd rather they be American killer robots than Chinese killer robots.

Ezra Klein (2:22)

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 US 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 is 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 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 US-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.

Matt Sheehan, welcome to the show.

Matt Sheehan (3:54)

Thanks very much for having me.

Ezra Klein (3:56)

So the dominant metaphor for the relationship between China and America on AI that exists in Silicon Valley, that exists in Washington, DC, is this metaphor of the race. And the ending of this race is super intelligence, that some company or some country is going to have the moment where their hopefully well-aligned safe model moves in to recursive self-improvement and goes, right, this got used to get called in the rationalist community the FOOM moment.

And at varying levels of explicitness people in DC 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? And I guess, do you buy this race model? Is that how you see it?

Matt Sheehan (4:47)

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, okay, 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 US. If they have, I mean, some estimates are they have one-eighth the compute of the US, maybe one-tenth of the compute than the US does.