4 papers
Quantifying the Necessity of Chain of Thought through Opaque Serial Depth
Jonah Brown-Cohen, David Lindner, Rohin Shah
Large language models (LLMs) tend to externalize their reasoning in their chain of thought, making the chain of thought a good target for monitoring. This is partially an inherent…
Debate is efficient with your time
Jonah Brown-Cohen, Geoffrey Irving, Simon C. Marshall +3
AI safety via debate uses two competing models to help a human judge verify complex computational tasks. Previous work has established what problems debate can solve in principle,…
Avoiding Obfuscation with Prover-Estimator Debate
Jonah Brown-Cohen, Geoffrey Irving, Georgios Piliouras +3
Training powerful AI systems to exhibit desired behaviors hinges on the ability to provide accurate human supervision on increasingly complex tasks. A promising approach to this pr…
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…