1 citations · 1 across the 4 of their papers we have counts for
5 papers
GDM AI Control Roadmap
Mary Phuong, Erik Jenner, Laurent Simon +4
AI agents are rapidly accelerating work at frontier AI companies, helping with AI R&D, cyber-defence, and advancing scientific discoveries. As these agents become more tightly inte…
Realistic honeypot evaluations for scheming propensity
Victoria Krakovna, David Lindner, Lewis Ho +2
We introduce scheming honeypot evaluations, a framework for testing whether models will pursue instrumental goals if given the opportunity. Our scheming honeypot evaluations take t…
Comprehensive AI governance requires addressing non-model gains
Arthur Goemans, Dan Altman, Noemi Dreksler +8
Frontier AI governance often centres on the model-level governance paradigm, which assumes that a model's capability profile is primarily a function of the compute and data used du…
Evaluating Frontier Models for Stealth and Situational Awareness
Mary Phuong, Roland S. Zimmermann, Ziyue Wang +6
Recent work has demonstrated the plausibility of frontier AI models scheming -- knowingly and covertly pursuing an objective misaligned with its developer's intentions. Such behavi…
An Approach to Technical AGI Safety and Security
Rohin Shah, Alex Irpan, Alexander Matt Turner +27
Artificial General Intelligence (AGI) promises transformative benefits but also presents significant risks. We develop an approach to address the risk of harms consequential enough…