Anthropic and some US politicians want to restrict open-weight AI models. The policy would slow American research without stopping China's progress, critics argue.
America can win the race to superintelligence. The bigger risk is that it defeats itself.
Bans and restrictions on open-weight AI models are already under consideration in Washington. Politicians and Anthropic have floated versions of this idea. If enacted, the effect would be the opposite of what supporters intend: it would slow American progress while doing nothing to stop China's.
An open-source AI model publishes its code publicly. Anyone anywhere can adapt it, fix errors, or retool it for specific tasks. A closed-source model keeps code proprietary to protect the underlying technology. Many leading US AI companies take that route with their frontier models, betting that secrecy supports margins.
The middle ground is an open-weights model. The training data and proprietary recipes stay secret. The model architecture code and parameter weights go public for anyone to run, modify, or build on.
The trend that has caught the industry's attention is China's release of prominent open-weight models. Those releases have let Beijing close the gap on America's leading frontier models faster than most US players expected.
My Parkview Institute colleague John Tamny uses a football-stadium analogy. "While you may be the smartest person in a football stadium, collectively, the stadium is a lot smarter than you," he said. China is crowdsourcing improvements on its AI systems to the entire globe. Many US companies rely strictly on in-house talent. Even the brightest employees of major AI players face a hard time competing against the global crowd.
Some policymakers have drawn the wrong conclusion from this. Anthropic's stance looks like "if you can't beat them, ban them." The company has urged restrictions on open models. The flaw in that logic is straightforward: nothing about restricting open models in America will cause Beijing to stop developing them.
Even if the US restricted such usage domestically, China would still have the rest of the world improving its technology. American independent researchers and computer engineers would be cut off from the ability to analyze and learn from those models.
Against that backdrop, it was welcome news that leading AI companies recently signed a letter urging policymakers to avoid heavy-handed regulations on open-weights models. Nvidia, Microsoft, Meta, Alphabet, and OpenAI were among the signatories. Elon Musk voiced his "full support" on X.
The letter made a critical point: closed models are not inherently safer. When OpenAI's frontier model was caught breaking out of its sandbox to launch a cyberattack on another company, an open-weight model helped contain the intrusion.
Some argue that open-source models are more dangerous because users can change the code. Those changes often include fixes that strengthen security. If a company suffers from tunnel vision and overlooks certain vulnerabilities, the rest of the world can help fix them.
For America to lead in AI, it needs to compete in both open and closed models. Banning competition does not make it go away.
The preeminent supply-side economist Robert Mundell put it well: "The only closed economy is the world economy." That is especially true for AI.
Jon Decker is the Executive Director of American Commitment.
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