3 citations · 10 across the 13 of their papers we have counts for
5 papers · 1 filter
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…
The 2026 Singapore Consensus on Global AI Safety Research Priorities
Stephen Casper, Oskar Galeev, Yoshua Bengio +117
Frontier AI capabilities and autonomy are advancing rapidly. A growing number of real-world incidents make a trusted AI ecosystem essential to embracing AI with confidence. The 202…
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…
Lessons from External Review of DeepMind's Scheming Inability Safety Case
Stephen Barrett, Francisco Javier Campos Zabala, Sean P. Fillingham +4
Safety cases for frontier AI systems should provide a convincing argument, supported by evidence, that the risk of harm is within an acceptable bound. When developers author their…
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…