Why Chinese Will Embrace AI—Whether They Love It or Hate It

For a country shaped by 180 years of technological catch-up, AI isn't a question of whether, only of how and for whom

This episode was originally meant to be about what shaped the relatively optimistic mindset many Chinese people have toward AI. (Thanks afra for the enlightenment; we had a great talk in Beijing) But by the time I finished, I realized I’d packed a lot more into it than I’d planned. I hope you enjoy reading it anyway. If you find it useful, please hit like or subscribe to my newsletter. Thank you!

Just like other places around the world, China is facing the impact of AI. But if you talk with ordinary people, no matter whether they love it or not, almost no one disputes that AI is unstoppable. To understand the almost uniform posture Chinese people take toward artificial intelligence, you have to start from a point that many outsiders aren’t familiar with: 1840, the year the Opium War battered open the doors of a country that had sealed itself shut.

I know some American readers will see this and think, here we go, another round of the Chinese century-of-humiliation narrative. Yes and no. If you set the emotional storytelling aside, the real through-line of a Chinese high school history textbook is not about humiliation and revenge, but the Chinese people’s repeated attempts to save the nation, just the prescription constantly being swapped out. The Self-Strengthening Movement(洋务运动) tried to borrow the West’s machinery and technology, then failed at the First Sino-Japanese War. The Hundred Days’ Reform and the 1911 Revolution borrowed Western political institutions, ended up with warlords and chaos. The New Culture Movement borrowed Western thought and culture—and this thread doesn’t reach a resting point until the founding of the People’s Republic in 1949.

These attempts differed enormously from one another, yet they converge on a single conclusion that no matter which political system or which regime is in power, technological progress is the one thing you cannot get around. For anyone who has been through this Chinese high school education, a kind of progressivism about technology becomes deeply embedded in their view of history.

It’s precisely because of this that, for someone who grew up inside this basic education system and absorbed its historical narrative, artificial intelligence is simply another name for technological progress. And in this framework, technological progress belongs to the grand trend of the world—it is the direction history moves in, a current no one can opt out of. You either ride it or you drown in it.

Of course, education is itself part of class reproduction, so this logic won’t just stay in history books, it’s also conveyed to the country’s top-level institutional design. This June, Qiushi, the Party’s flagship journal, turned its attention to China’s reform of education, science, technology, and talent.

The popularization rate and key indicators of basic education in our country have comprehensively surpassed the average level of middle- and high-income countries. At the same time, however, problems still exist to varying degrees, such as placing excessive emphasis on the rote transmission of knowledge while neglecting the assessment of students’ comprehensive qualities—especially the evaluation of their innovative abilities—as well as ‘prioritizing selection over cultivation, and emphasizing the ‘creaming off’ of top talent over fostering innovation.’ We must promote the full-domain coverage of science and innovation education, stimulating students’ interest in innovation through everyday-life experiments, interdisciplinary projects, and the like, with a focus on cultivating students’ problem-solving abilities.

What this signals, on one side, is that China has recognized that the very basic education system that once underwrote its development is turning into its own opposite. In the AI era, the people that traditional education produces no longer meet demand, so education itself has to change to hunt for innovative talent. Seen from another angle, this amounts to once again defining the education system as a tool in the service of the goal of technological progress.

The Real Question Has Been Flipped Around

For exactly this reason, for many Chinese people, the real question was never why we should embrace AI, but on what grounds we would not. AI represents an advance in productive forces, and the lesson of history is that regimes that deny or suppress advanced productive forces mostly end up failing and collapsing. To put it more plainly: what people can do is adjust the relations of production to fit the development of the productive forces, but the productive forces themselves can’t be made to stop walking.

On this point, the Chinese logic resembles tech accelerationism; both accept that technological progress is unstoppable. The accelerationists of Silicon Valley are not a monolith—they range from a broadly left-leaning camp that dreams of a post-scarcity society of abundance, to the more radical “effective accelerationism” (e/acc) crowd, embodied by figures like Elon Musk, who want to harness ever-greater energy and turn humanity into a multi-planetary species. For neither group, however, is technological progress truly an end in itself; it remains a means to a more abundant human future. The crucial difference, then, lies less in the goal than in how and by whom technology is made to serve people. The accelerationist vanguard largely trusts that unfettered progress will deliver that better future on its own, whereas the Chinese view holds that technology should of course advance, but that the government simultaneously bears the responsibility for steering it toward the public good. The official vocabulary captures this with the phrase “AI for good” (智能向善).

Finance is one of the most concrete arenas in which the government is doing exactly this kind of guiding, and it was the theme of this year’s Lujiazui Forum, where the watchword was technology finance. The reason finance matters so much here is that, in this new wave of industrial revolution, the core industries represented by AI and semiconductors follow a developmental logic entirely different from the old land-and-credit model. On one hand, they demand enormous upfront capital; on the other, their asset-light nature leaves them with few physical assets to pledge as collateral. Combined with the heavy concentration of talent and capital they require, this makes tech firms far more dependent on, and far more demanding of, the financial system to feed them. Building a stronger and better-fitted financial system to support them has therefore become an increasingly pressing necessity.

How the very top is pushing this came through clearly in the speech that Wu Qing, chair of the China Securities Regulatory Commission, delivered at the forum. His core message was that capital markets must better serve new quality productive forces.(新质生产力) The concrete moves he laid out included extending the STAR Market’s fifth set of listing standards to the AI field, supporting the listing of high-quality AI large-model companies, and backing hard-tech firms in areas such as quantum technology, biomanufacturing and embodied intelligence, while also issuing, at an appropriate time, guidance to regulate the use of AI in the capital markets themselves. What gives the speech its weight is what it reveals that even the institutional plumbing of the capital markets is now making way for AI. Money, people, and institutions are all converging on technological progress.

Are AI and Social Security Mutually Exclusive?

Of course, plenty of people argue that China going all in on AI means sacrificing people’s livelihoods in pursuit of technology. I think that claim is debatable. The way the Chinese government handles AI’s employment shock differs from the West’s, it leans more toward safeguarding job opportunities. Matt Sheehan captured the seeming dilemma and the growing policy push to secure jobs in his insightful piece, China is getting worried about AI & jobs. What I see in recent days is a growing number of policy advisers have been tapping the brakes on AI deployment.

One of the weightiest voices belongs to Jiang Xiaojuan, a former deputy secretary-general of the State Council. (Translation in my newsletter with her kind permission: Jiang Xiaojuan: AI’s Logic Must Not Prevail) Her judgment is that employment is a matter of people’s livelihood, and that at this stage we cannot yet let AI loose to allocate resources for the market. She singles out one trend in particular: in the past, technological progress created far more new industries and new jobs than it displaced, but since the 1980s that trend has been slowing. She therefore argues for cautious development of purely labor-saving AI, holding that AI deployment cannot for now be handed entirely to the market, and that government provision of a safety net is all the more necessary.

The stance of Cai Fang, a member of the People’s Bank of China’s Monetary Policy Committee, likewise reflects this Chinese view of technology. He doesn’t oppose AI; rather, he holds that technological progress can’t be reversed and that all people can do is adapt through reform. He sums up the principal contradiction in the current job market as a structural one—work with no one to do it, and people with no work to do—with AI playing the role of amplifier and accelerator, though not the only shock, and not the largest one. The prescription he writes out is “three big essays”: industrial guidance, individual adaptation, and social security. A few of his lines capture this adaptationism well. In an interview, he said that the AI dividend won’t automatically be distributed evenly to everyone, calling on the government to speed up and build a strong, multi-level social security system to create a solid safety net that protects people’s basic livelihoods. This will give working people enough time to learn new skills and change or reshape their careers.

Why China Doesn’t Want European-Style Welfarism

China’s social-security system is indeed on the weaker side; the pensions that urban and especially rural residents receive are quite limited. But to understand why China rejects European-style welfarism, I want to offer a discourse-level perspective.

Its origins trace back to the early stage of the reform and opening period. Before market-oriented reform can be advanced, a form of discursive preparation is usually required. The discourse of Reform and Opening condensed the ills of the planned economy into a set of highly negative keywords: egalitarianism(平均主义), the “big rice pot,”（大锅饭） low efficiency. This discourse helped China rapidly advance marketization, but at the level of popular culture it had a side effect that any institution tinged with universal provision and decoupled from performance got filed into this same category, so welfare became linked with laziness and waste. Set against this was the other side, jumping into the sea of business (下海经商), a striving culture of daring to dream, daring to act, daring to hustle, which was molded into a virtue. The negative imagination about welfare and the praise for striving are really two sides of one coin.

I also want to add another conceptual layer. In the Marxist understanding, labor and practice are the foundation of human society, and labor here is not equivalent to work in the narrow sense. You can love or hate your job, but labor is the process of creating and participating in social production, and it’s the way a person becomes connected to society. Once a person is severed from labor, severed from socialized mass production, they become disconnected from society itself. This is the deeper motive behind the government’s fixation on helping people find work: what it truly fears is not just that some people rely on welfare, but that a large mass of people will be cut off from any connection to society.

For exactly this reason, the State Council’s recently issued employment-first strategy in the 15th Five-Year Plan can be read as a head-on response to AI’s employment shock. It sets up an “action to adapt to AI development and promote employment,” which further breaks down into an AI job-creation plan, a plan to tap the employment potential of AI in traditional fields, and a plan to support workers in transitioning and switching jobs—the consistent logic being to reduce AI’s crowding-out of jobs and to amplify its job-creating pull. It also emphasizes using the service sector as a reservoir for absorbing employment, ensuring people have work while also improving the quality of that work by raising incomes, strengthening social insurance, and enhancing occupational safety.

A Short-Term Buffer, but a Welfare Still Has to Be Built

That said, the current toolkit is, at its core, still about balancing AI deployment against cushioning the short-term employment shock—what it’s buying is time. From a longer-term perspective, I’d still recommend the article Cai Fang published in Study Times, which Qiushi later reprinted. In it, he writes plainly that, taking universal basic income (UBI) as a reference point, China should raise the coverage and level of its minimum-livelihood guarantee, push the transition from a minimum-wage system to a living wage, and upgrade the urban-and-rural residents’ pension into a non-contributory basic pension that covers all elderly people unconditionally and equally. He also judges that AI-empowered robotics, displacing blue-collar work on a large scale, is the way the tide is turning. And once AI hits not just white-collar jobs but blue-collar ones too, the very premise that everyone has work to do can no longer hold.

My own read is that fiscal constraints will keep these goals off the near-term agenda. But the direction of travel seems clear. AI is quietly dismantling the old suspicion of the welfare system, and the welfare state, long treated in China as something to be kept at arm’s length, is turning into a problem there is no getting around.