JAMES PETHOKOUKIS: America’s AI Regulation Should Be Rooted in Free Enterprise Principles.
If you think super-advanced AI isn’t on the horizon—which is the forecast of five out of six AI technologists, according to one recent survey—then we can treat AI models and their corporate creators in a more “normal” fashion. These open and near-frontier models should be treated as engines of competition and diffusion. As tech analyst Ben Thompson argues, the economic panic over Chinese models like Kimi K3 mostly misreads market economics:
Right now there is a price umbrella that is downstream of the lack of compute; I highly doubt that Chinese models are cheaper to serve on a marginal cost basis, they just seem cheaper because Anthropic and OpenAI are so supply constrained that they are charging far more than they would if there were sufficient supply to meet the demand for intelligence.
Washington should think hard about how policy currently works against a proliferation of advanced American models—starting with the informal national-security review process that, as tech policy analyst Adam Thierer has explained, can hold up a model’s release with little public explanation or transparent process. That’s a dicey situation for a wealthy frontier AI company—and an impossible one for an open-model startup.
There are genuine security problems here. My AEI colleague Ryan Fedasiuk has usefully catalogued many of them, such as user data flowing to Chinese servers subject to Beijing’s National Intelligence Law and tampered model files in the supply chain. The right response is targeted rules on AI models used in government systems, sensitive data, and what major American platforms distribute. So an argument for safeguards, not suppression.
I’d add that rules and regulations written in the heat of a panic are even worse than those that aren’t — and the ones that aren’t rarely work as intended.
