There Is No A.I. “Race”
In 1884, Charles Parsons invented a machine that revolutionized the mass production of electricity. His steam turbine could generate power far more cheaply, and on a vastly greater scale, than traditional piston engines. Parsons belonged to a long line of great British inventors—including the “father of electricity,” Michael Faraday—who helped bring a new technology to the world, one that illuminated cities, enabled subways, and provided the bedrock of modern computing. Before artificial intelligence, humanity associated electricity with the realm of gods. A betting man, at the cusp of the twentieth century, would have been hard pressed to deny Britain its place in the future.
It didn’t work out that way, of course. Four years later, Britain still lacked a single central station supplying electricity to the public. By then, Thomas Edison’s company had built a hundred and eighty-five stations across America; two years later, the country had more than a thousand of them. By 1912, the U.S. had become the world’s leading industrial power and was producing five times more electricity, per person, than Britain. When it came to electricity, British scientists of the time observed, “our countrymen have been among the first in inventive genius,” but its practical development was in a “backward condition.”
More than a century later, Americans are told by their leaders and inventors that, if China pulls ahead in artificial intelligence, “there is no day after tomorrow,” as Treasury Secretary Scott Bessent recently warned. China is only six months behind—or four, or nine, or perhaps mere nanoseconds. But what exactly happens if China “wins” the A.I. race? Nathan Rosenberg, a historian of technology, once wrote about our fixation on the “Who did it first?” question. What matters in this view are the Parsons of the world—why the eureka moment happened there and not here, to this person and not that one. And yet, Rosenberg wrote, the moment of invention is a mere prelude to the unglamorous saga of “diffusion”: how a new technology burrows into firms, municipalities, processes, and people. Historians, Rosenberg argued, had assumed diffusion “out of existence.”
One disciple of the Rosenberg school is Jeffrey Ding, a political scientist at George Washington University. In the book “Technology and the Rise of Great Powers,” from 2024, Ding debunks the first-mover myth, noting that across four industries credited with making America the world’s leading economy—steel, electricity, chemicals, and automobiles—American firms pioneered fewer than a third of the relevant innovations. Being first, Ding argued, was a poor predictor of who wins. “In the current narrative, the metric for winning or leading on A.I. is who has the fanciest models,” Ding told me. “But, in a lot of my research, the lead is about who can diffuse A.I. across the entire economy and gain a productivity boost.”
Recent incidents—including a swarm of OpenAI agents hacking the company Hugging Face—have prompted calls, both from in-the-trenches A.I. researchers and the Anthropic C.E.O., Dario Amodei, for an industry-wide commitment to “pace the frontier,” or prioritize A.I. safety. And though the fear of being “enslaved” to Chinese A.I., as J. D. Vance once put it, threatens to thwart this project, the diffusion theory might loosen the bind. If the goal is to “win” a broad-based prosperity, as America did with electricity, “pacing the frontier is actually very aligned with a strategy to win the race,” Ding told me.
Any new technology has to win the public’s trust in order to be adopted. The race toward nuclear energy faced a major setback in 1979, with the meltdown at Three Mile Island; dozens of projects were canned in the aftermath. Since 1996, the United States has completed only three reactors, while China broke ground on nine just last year. “Imagine what the level of nuclear power adoption would be in the U.S. today if there were more proactive safety measures put in place before Three Mile Island,” Ding told me. In the Hugging Face debacle, he sees the beginning of the same pattern—a majority of Americans are already pessimistic about A.I.—but believes an approach that prizes reliability over raw power could keep the A.I. rollout from stalling.
Chinese policymakers, for their part, appear to be diffusionists: their signature “AI+” initiative, from 2025, aims to integrate the technology into factories, hospitals, and local administration. But, over all, Ding is bullish on America’s prospects; state-directed economies like China’s, he argues, are good at sprints but bad at marathons. (The Soviet Union launched Sputnik, for example, but it was the United States that built an economy on satellites: G.P.S., communications, and remote sensing.) The “AI+” program is “just talk,” Ding told me—a better measure of diffusion is cloud computing, the infrastructure on which much of A.I. runs. There, he found, China trails the United States in both spending and adoption.
What America needs in order to “win,” then, is less investment in the frontier and more in the broad middle. Ding puts special emphasis on community colleges, vocational schools, and state universities, institutions that can train not just future Nobel laureates but an A.I.-literate middle class—those who will actually carry the technology into the local bank and city hall. It also means making peace with Chinese open-weight models, which have already become popular among American businesses and developers.
When it comes to justifying unchecked growth, tech companies have long relied on a strategy we might call “But China.” During Mark Zuckerberg’s 2018 Senate testimony, his private notes were caught by a photographer: “Break up FB? . . . break up strengthens Chinese companies.” In a submission to the White House in 2025, OpenAI invoked China to claim the right to train on copyrighted works. “If the PRC’s developers have unfettered access to data and American companies are left without fair use access,” the company wrote, “the race for AI is effectively over.” Dario Amodei has expressed anxiety about an “AI-enabled totalitarian nightmare,” and Ted Cruz, putting it more plainly, has said, “If there are gonna be killer robots, I’d rather they be American killer robots than Chinese killer robots.”
What’s different about this iteration of the “But China” ideology is its fusion with a strain of speculative philosophy. In 2014, the philosopher Nick Bostrom proposed the idea of a “decisive strategic advantage.” This is a situation in which the A.I. of one nation pulls far enough ahead in capabilities “to achieve complete world domination.” Bostrom was doing what philosophers do: removing real-world complications to arrive at new moral terrain. But, as A.I. capabilities have accelerated, many technologists have begun treating these thought experiments as near-term forecasts. They imagine drone armies that could neuter a rival’s nuclear capabilities, a knockout cyberattack that overwhelms power grids, or a bioweapon that can, as one chilling white paper put it, “target specific ethnic groups, e.g. anybody but Han Chinese.”
Are these scenarios realistic? Jack Shanahan, a former director of an early Department of Defense A.I. initiative called Project Maven, told me that many of the projects he oversaw got bogged down in bureaucracy. The technology was advancing far quicker than institutions could absorb it. “The gears didn’t match,” he told me. “We’re trying to turn it at a thousand r.p.m. and the rest of the bureaucracy is moving at fifty r.p.m.” People need to be trained, processes and policies rewritten, organizations reordered, protocols invented, budgets approved, data collected and cleaned. Maven took nine years to reach widespread military use, Shanahan said, and fully integrating today’s A.I. systems with the military could take another fifteen. The People’s Liberation Army is “not immune to this,” he added.
In the case of bioweapons, what is “assumed out of existence,” to borrow Rosenberg’s line, is again the labor of diffusion. To bake a cake, one needs a lot more than a recipe. In the early nineteen-eighties, the Soviet Union tried to produce an anthrax weapon that was already designed. Four hundred pages of instructions and a sample were sent to a plant in Stepnogorsk, a town on the Kazakh steppe. The staff couldn’t build it. Even after the Soviets sent sixty-five more personnel, including the original designers of the weapon, the project stalled because the instructions couldn’t be adapted to the local facilities. The resulting weapon, completed five years later, was not the same as the recipe. “Replicating past work using scientific documents alone,” Sonia Ben Ouagrham-Gormley, a biodefense scholar at George Mason University, writes in “Barriers to Bioweapons,” “cannot be achieved without access to the corresponding tacit skills and the related communal knowledge.”
This leaves the prospect that perhaps most alarms national-security experts: a Chinese A.I.-enabled cyberattack. In the near term, it seems improbable. Even if Chinese models pulled ahead, the likeliest peril would be a mere intensification of the status quo: Chinese state-linked hackers have already breached American telecom networks and harvested sensitive data. The “But China” rhetoric tends to blur the distinction between what Mieke Eoyang, a national-security expert and visiting professor at Carnegie Mellon University, calls “presence”—lurking inside a network—and “disruption,” actually disabling it. States engage in the former constantly. (“We spy on them, too,” Donald Trump recently quipped about China.) The latter could be viewed as an act of war. Getting from one to the other requires far more than losing the A.I.-model race, including, among other things, a catastrophic breakdown in diplomacy.
“Shall we, instead, choose death, because we cannot forget our quarrels?” So asked Bertrand Russell and Albert Einstein in the early years of our nuclear age. Similar questions hang over Xi Jinping’s visit to Washington this week, for talks that many hope will include discussions of A.I. safety. Expectations are low. A.I.’s threat to humanity is a “HOAX,” Trump claimed recently; the only “guardrails” that the technology needs are a “STRONG AND SMART (High IQ!) PRESIDENT.” The Chinese foreign ministry, for its part, dismissed Amodei’s calls to “pace the frontier” as fearmongering. After years of American officials and technologists casting Chinese A.I. as an incalculable menace, U.S. demands for a mutual slowdown are interpreted in China as an extension of Cold War-style containment. On both sides, there is simply too much distrust.
But America’s vision of the A.I. race elides something fundamental. For years, the powers in Silicon Valley and D.C. have conjured an image of China barrelling toward superintelligence. The irony of this is twofold. First, Chinese A.I. policy remains focussed primarily on diffusion: how to drive A.I. into public and commercial life. (It’s rare to hear a Chinese leader mention the risks of runaway, self-improving A.I.) Second, as Matt Sheehan, a researcher at Carnegie focussed on global technology issues, recently observed on Ezra Klein’s podcast, in the years in which Chinese A.I. companies caught up to the American frontier, they also had to accommodate their own government, home to “the world’s strictest, most comprehensive, most burdensome A.I. regulations.”
In February, 2023, a Chinese competitor to ChatGPT was suspended from the WeChat platform, for reasons that people suspected had to do with political censorship; the chatbot had called Russia’s invasion of Ukraine a “war of aggression.” As part of a years-long regulatory barrage, China forced A.I. companies to register their algorithms for review, and other policies targeted A.I. misinformation, deceptive claims of human identity, and the manipulation of minors. I asked several experts what would happen if, à la Hugging Face, Chinese agents were found breaching the data hull of another Chinese company, and all of them predicted that the government would take decisive action. “That would be a big deal,” Graham Webster, a research scholar focussed on China and technology at Stanford, told me. But “nobody would be, like, ‘We’re all gonna die,’ ” he added. China “would just go and address the actual problem while publicly shaming the company.”
Partly, this might be because Chinese engineers grew up in a culture that prized problem-solving over wayward speculation. And their most prominent philosophers, the Confucians, preached a morality that radiated outward: order yourself before ordering others. A complaint I heard time and again from experts is that “But China” arguments tend to treat the world as a theoretical construct. This is a hazard of Western analytic philosophy, where sensible premises, like recursive self-improvement, slip into sci-fi absurdity—killer-robot armies, ethnically targeted bioweapons, genetically modified super-soldiers. Now we are made to choose between a world that might be and the world as it is. If we want to win the A.I. “race,” then perhaps it’s time to get our house in order first. ♦