On Dec. ninth, U.S. President Donald Trump introduced that the U.S. would permit Nvidia’s H200 processors to be exported to China, topic to a 25% price on all gross sales. The transfer has despatched ripples by the American institution, with many (together with Senator Elizabeth Warren) charging that Trump is “promoting out” nationwide safety.
There isn’t a scarcity of such zero-sum or aggressive framing on the subject of the worldwide AI area. Certainly, whereas Anthropic has emphasised AI security at dwelling, the corporate’s co-founder and CEO, Dario Amodei, has stoked a story of an arms race overseas, arguing that export controls are important to decelerate China’s growth and make sure that the U.S. wins the AI race. Equally, Chip Battle creator Chris Miller argues that the U.S. chip export controls, such because the prohibition on the sale to China of probably the most superior GPUs just like the NVIDIA H100s, have “succeeded … [by] considerably gradual[ing] the expansion of China’s chipmaking functionality”. Certainly, Trump himself declared in July that America began the AI race, and it’ll win it.
Such arguments counsel that the 2 nice powers are engaged in a two-player race—that certainly one of them will win and the opposite will lose—and that the winner will get hold of vital advantages on the expense of the loser. But from a rational selection perspective, the “AI race” is a misnomer. A two-party race sometimes entails an setting characterised by a rivalrous useful resource (which can’t be loved by each events) that’s non-excludable (neither participant can simply forestall the opposite from utilizing it), and the gamers compete over who would be the first to that useful resource.
Within the 1955 movie, Insurgent And not using a Trigger, Jim Stark (James Dean) races towards a cliff towards his nemesis Buzz (Corey Allen). If each youngsters drive straight, they each die. The one who swerves first loses. If one driver swerves and the opposite continues racing to the cliff’s edge, neither can enhance his place by altering technique—we name this a Nash Equilibrium. This final result is non-cooperative: If one swerves, the opposite ought to race; but when one switches to racing, the opposite ought to swerve.
The geopolitical AI ecosystem just isn’t like this. The usage of AI fashions is excludable—certainly, final yr Sam Altman determined to exclude Chinese language customers from OpenAI’s GPT—however such use just isn’t strictly rivalrous (DeepSeek’s fashions are launched underneath open-source licenses and may be run domestically by anybody). A mannequin’s implementations are arguably rivalrous, in that the marginal person imposes an vitality/information value, however that was not the motivating concern for Altman’s choice: He excluded Chinese language customers as a result of he believed that the U.S. shouldn’t cooperate with China.
So maybe the argument is that promoting chips to China would embolden Beijing and render the U.S. worse off. But this ignores the advantages accrued to odd U.S. middle-class households by better entry to main electronics at decrease costs, or the amount of leverage afforded by international dependence on the American tech panorama.
Some economists consult with a scenario characterised by non-rivalrous however excludable assets, as an alternative of rivalrous however non-excludable assets, as a “stag hunt”, drawing upon a parable in thinker Jean-Jacques Rousseau’s A Discourse on Inequality. Take into account a gaggle of hunters who can select to hunt a big prey collectively (the stag), or a small prey alone (the rabbit). The trick is that they will solely catch the stag in the event that they cooperate whereas everybody can hunt a rabbit on their very own. This sport has two Nash equilibria: Both we work collectively to hunt the stag, or we every work alone to catch a single rabbit. But certainly one of these equilibria is healthier than the opposite: We should always work collectively to hunt the stag.
International AI competitors appears to be like extra like a stag hunt than it does like a race. Whether or not in coverage, governance, or commerce, cooperation between nations can yield better advantages than working alone. In distinction, a breakdown in communication breeds distrust, which may give rise to dangerous errors, akin to an escalatory spiral from overestimating the risk posed by the opposite facet, or a reckless deployment of AI in conflicts. The “stag” within the U.S.-China AI sport, subsequently, lies partially with the mutual prevention of such errors and the positive factors from mutually advantageous industrial growth of AI for the advantage of the broader public.
There exist loads of frequent challenges that China, the U.S., and the world should confront, from AI manipulation, deception, and coercion, to the displacement of labor caused by AI’s implementation within the workforce. Such mutually helpful cooperation requires belief, transparency, and cooperation, versus erratic politicization—that is how we transfer from looking the rabbit, to looking the stag.
To get there, policymakers should search to domesticate efficient multilateral AI governance establishments, together with establishing and monitoring dispute decision mechanisms. Bargaining capital additionally arises by unconventional alignments of medium-size powers, every with their distinctive niches.
For example, energy-rich Saudi Arabia is striving to develop into the third largest AI market on this planet, whereas main gamers in France and Israel are pledging to steer in specialised AI functions. With its immense inhabitants and rising emphasis upon schooling, India is shaping to be among the many major suppliers of engineering and laptop science expertise.
The worldwide order is turning into extra multi-polar, and the AI world isn’t any exception. As a substitute of making an attempt to “win the AI race” at any value towards its rival, each the U.S. and China ought to construct bridges and search frequent floor with pals and rivals alike.
This essay is tailored from the authors’ forthcoming ebook, Geopolitics of Synthetic Intelligence, to be revealed in 2026 by Cambridge College Press as a part of its Components collection.
The opinions expressed in Fortune.com commentary items are solely the views of their authors and don’t essentially replicate the opinions and beliefs of Fortune.
