59 citations · 214 across the 11 of their papers we have counts for
4 papers · 1 filter
Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data
Nahema Marchal, Rachel Xu, Rasmi Elasmar +3
Generative, multimodal artificial intelligence (GenAI) offers transformative potential across industries, but its misuse poses significant risks. Prior research has shed light on t…
STAR: SocioTechnical Approach to Red Teaming Language Models
Laura Weidinger, John Mellor, Bernat Guillen Pegueroles +9
This research introduces STAR, a sociotechnical framework that improves on current best practices for red teaming safety of large language models. STAR makes two key contributions:…
Sociotechnical Safety Evaluation of Generative AI Systems
Laura Weidinger, Maribeth Rauh, Nahema Marchal +10
Generative AI systems produce a range of risks. To ensure the safety of generative AI systems, these risks must be evaluated. In this paper, we make two main contributions toward e…
Model evaluation for extreme risks
Toby Shevlane, Sebastian Farquhar, Ben Garfinkel +18
Current approaches to building general-purpose AI systems tend to produce systems with both beneficial and harmful capabilities. Further progress in AI development could lead to ca…