3 citations · 4 across the 6 of their papers we have counts for
6 papers
Open Problems in AI Risk Modeling: Insights from a Workshop on the Technical Foundations of AI Risk Modeling
Krystal Jackson, Deepika Raman, Jakub Kryś +8
We investigate the design of robust risk models to assess societal risks posed by advanced AI systems, an emerging area in AI governance. Many regulatory proposals increasingly req…
Prioritization of Risks from Artificial Intelligence: A Delphi Study of 272 International Experts
Alexander K. Saeri, Jess Graham, Michael Noetel +185
Artificial intelligence poses many risks, ranging from familiar present-day harms to unprecedented and potentially catastrophic ones. Effective risk management requires prioritizat…
Open Problems in Frontier AI Risk Management
Marta Ziosi, Miro Plueckebaum, Stephen Casper +26
Frontier AI both amplifies existing risks and introduces qualitatively novel challenges. Not only is there a notable lack of stable scientific consensus resulting from the rapid pa…
Frontier AI Auditing: Toward Rigorous Third-Party Assessment of Safety and Security Practices at Leading AI Companies
Miles Brundage, Noemi Dreksler, Aidan Homewood +45
We outline a vision for frontier AI auditing, which we define as rigorous third-party verification of frontier AI developers' safety and security claims, and evaluation of their sy…
Evaluating AI Providers' Frontier Safety Frameworks
Lily Stelling, Malcolm Murray, Bruno Galizzi +3
Following the AI Seoul Summit in 2024, twelve AI companies published frontier AI safety frameworks (Frameworks) outlining their approaches to managing catastrophic risks from advan…
Third-party compliance reviews for frontier AI safety frameworks
Aidan Homewood, Sophie Williams, Noemi Dreksler +11
Safety frameworks have emerged as a best practice for managing risks from frontier artificial intelligence (AI) systems. However, it may be difficult for stakeholders to know if co…