{"version":"1.0","type":"rich","provider_name":"Acast","provider_url":"https://acast.com","height":250,"width":700,"html":"<iframe src=\"https://embed.acast.com/$/61e878a1419a9b0013b27134/699d156bdc0d51c3f1561d40?\" frameBorder=\"0\" width=\"700\" height=\"250\"></iframe>","title":"Can AI Make AI Regulation Cheaper?, with Cullen O'Keefe and Kevin Frazier","description":"<p>Alan Rozenshtein, research director at Lawfare, spoke with Cullen O'Keefe, research director at the Institute for Law &amp; 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,&nbsp;<a href=\"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6017756\" rel=\"noopener noreferrer\" target=\"_blank\">\"Automated Compliance and the Regulation of AI\"</a>&nbsp;(and&nbsp;<a href=\"https://www.lawfaremedia.org/article/ai-will-automate-compliance.-how-can-ai-policy-capitalize\" rel=\"noopener noreferrer\" target=\"_blank\">associated Lawfare article</a>), which argues that AI systems can automate many regulatory compliance tasks, loosening the trade-off between safety and innovation in AI policy.</p><p><br></p><p>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.</p><p><br></p>","author_name":"Lawfare & University of Texas Law School"}