Proposed AI safety regulations could create a 'regulatory moat' for giants like Google. The high cost and complexity of navigating an approval process can stifle smaller open-source projects, which lack regulatory budgets. In contrast, large, well-funded companies can absorb these costs, solidifying their market dominance.

The US government's intervention in Anthropic's model release has established a new regulatory playbook that OpenAI is now preemptively adopting. This signals a shift toward government-gated AI deployment, where companies seek federal approval before releasing powerful new models to a select group of trusted partners.

As the capability gap between internal and public models widens, the most critical decisions about safety will be made pre-release. This internal frontier lacks a governance framework, as current regulations are only triggered by public deployment.

Gurley argues against heavy-handed U.S. AI regulation, like banning models with Chinese open-source components. He fears this could create a "fence around the U.S.," leading to a scenario where Chinese AI platforms, not American ones, dominate the global market, reversing the dynamic of the internet era.

Instead of establishing clear regulations, the White House is intervening directly in AI rollouts, limiting access to new models like OpenAI's on a case-by-case basis due to national security. This high-touch approach gives the government immense control but creates uncertainty and is viewed by some safety advocates as a 'worst of both worlds' scenario.

The vulnerabilities in Anthropic's Fable 5 model "spooked" the Trump administration, softening its previous opposition to global AI governance. The incident has created momentum for multilateral discussions on setting baseline international safety standards for powerful AI, a significant shift in US policy.

An FDA-style regulatory model would force AI companies to make a quantitative safety case for their models before deployment. This shifts the burden of proof from regulators to creators, creating powerful financial incentives for labs to invest heavily in safety research, much like pharmaceutical companies invest in clinical trials.

For AI safety, Demis Hassabis advocates for an international regulatory body, similar to the International Atomic Energy Agency. This body would have technical experts who audit frontier models against agreed-upon benchmarks, checking for undesirable properties like deception and ensuring public confidence through independent verification.

While the US government is reacting chaotically to domestic AI models, it has no corresponding strategy for ensuring global AI infrastructure is safe. This policy vacuum is critical as other countries will soon develop frontier capabilities without US-style safeguards, creating a global proliferation risk that isn't being addressed.