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AI Regulation: Decentralizing Power and Protecting Innovation

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Thanks Gavin for an especially thoughtful exchange. I don't usually spend much time on social media but I wanted to engage here because it really brings out the heart of an important conversation. First, on regulation, I think that “either concentrate it in the hands of a chosen few companies and politicians via regulation or distribute it widely” is a false choice.

Regulation is not simply a tool for concentrating power; objective and fair institutional processes can decentralize it. Anthropic has always made its policy proposals carefully, aiming to disadvantage frontier AI companies while advantaging smaller competitors. California’s SB53 (supported) and the much‑maledict SB 1047 exempt companies below $500M in revenue or training costs from coverage. The testing process we advocated at CAISI and the White House calls for more rigorous tests for frontier models, giving challengers an edge.

The “Pacing the Frontier” letter envisions modulating the pace of the best models while leaving room for open‑weights. AI is structurally a technology that tends to concentrate power because of scaling laws, but the right rules can address cyber, bio, and alignment risks, constrain frontier labs, and still allow open‑weights models. I support the Trump administration’s pre‑deployment testing for frontier models and Demis Hassabis’ idea of a FINRA‑like entity, contrasting the industry’s previous push for borderless state regulation.