Carnegie Paper: Frontier AI Regulation Should Target Developers, Not Models
Miles_Brundage · x · 2026-08-09
Miles Brundage shared a recent Carnegie Endowment paper on frontier AI governance, highlighting a shift towards a "modern view" of AI regulation that moves beyond mere pre-deployment testing.
The paper tackles the core debate in AI policy: whether to regulate the models themselves, their specific use cases, or the developing entities. Authors Dean W. Ball and Ketan Ramakrishnan argue that both traditional use-based and model-based regulatory paradigms face serious objections, such as high compliance costs deterring innovation.
Instead, they advocate for entity-based regulation, suggesting that regulatory statutes should focus on large AI developers rather than particular models or use cases. This approach concentrates the compliance burden effectively while allowing latitude for technology diffusion.
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