8 papers · 1 filter
FLARE-AI: Flaw Reporting for AI
Shayne Longpre, Elaine Zhu, Carson Ezell +15
Flaw reporting for deployed AI systems is fundamental to identifying system failures and improving AI safety. Yet the AI reporting ecosystem is fragmented: researchers who identify…
RCTs for Frontier AI Governance: Methodological Challenges and Solutions for Human Uplift Studies
Patricia Paskov, Kevin Wei, Shen Zhou Hong +7
Human uplift studies, or studies that measure the effects of AI access on human performance via randomized controlled trials (RCT) or similar methodologies, increasingly inform fro…
Dark Speculation: Combining Qualitative and Quantitative Understanding in Frontier AI Risk Analysis
Daniel Carpenter, Carson Ezell, Pratyush Mallick +1
Estimating catastrophic harms from frontier AI is hindered by deep ambiguity: many of its risks are not only unobserved but unanticipated by analysts. The central limitation of cur…
Incident Analysis for AI Agents
Carson Ezell, Xavier Roberts-Gaal, Alan Chan
As AI agents become more widely deployed, we are likely to see an increasing number of incidents: events involving AI agent use that directly or indirectly cause harm. For example,…
How Do AI Companies "Fine-Tune" Policy? Examining Regulatory Capture in AI Governance
Kevin Wei, Carson Ezell, Nick Gabrieli +1
Industry actors in the United States have gained extensive influence in conversations about the regulation of general-purpose artificial intelligence (AI) systems. Although industr…
An FDA for AI? Pitfalls and Plausibility of Approval Regulation for Frontier Artificial Intelligence
Daniel Carpenter, Carson Ezell
Observers and practitioners of artificial intelligence (AI) have proposed an FDA-style licensing regime for the most advanced AI models, or 'frontier' models. In this paper, we exp…