# Can AI Make AI Regulation Cheaper?, with Cullen O'Keefe and Kevin Frazier

An episode of [Scaling Laws](https://invisiblenetwork.ai/podcast/1607949880), 24 Feb 2026, 52 min.

Audio: https://sphinx.acast.com/p/open/s/61e878a1419a9b0013b27134/e/699d156bdc0d51c3f1561d40/media.mp3

Alan Rozenshtein, research director at Lawfare, spoke with Cullen O'Keefe, research director at the Institute for Law & AI, and Kevin Frazier, AI Innovation and Law Fellow at the University of Texas at Austin School of Law and senior editor at Lawfare, about their paper, "Automated Compliance and the Regulation of AI" (and associated Lawfare article), which argues that AI systems can automate many regulatory compliance tasks, loosening the trade-off between safety and innovation in AI policy. The conversation covered the disproportionate burden of compliance costs on startups versus large firms; the limitations of compute thresholds as a proxy for targeting AI regulation; how AI can automate tasks like transparency reporting, model evaluations, and incident disclosure; the Goodhart's Law objection to automated compliance; the paper's proposal for "automatability triggers" that condition regulation on the availability of cheap compliance tools; analogies to sunrise clauses in other areas of law; incentive problems in developing compliance-automating AI; the speculative future of automated compliance meeting automated governance; and how co-authoring the paper shifted each author's views on the AI regulation debate. Hosted on Acast. See acast.com/privacy for more information.

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