Jason Wei—Emergent abilities of language models
Martin Wattenberg —Emergent world models and instrumenting AI systems
Been Kim—Alignment, setbacks and beyond alignment
Jascha Sohl-Dickstein—More intelligent agents behave less coherently
Ethan Perez—Model-written evals
Daniel Brown—Challenges and progress towards efficient and causal preference-based reward learning
Boaz Barak—For both alignment and utility: focus on the medium term
Ellie Pavlick—Comparing neural networks' conceptual representations to humans’
Percy Liang—Transparency and standards for language model evaluation

(Note: some parts of the video with audience questions are inaudible)

Sam Bowman—Measuring progress on scalable oversight for large language models
Zico Kolter—"Safe Mode": the case for (manually) verifying the output of LLMs
Roger Grosse—Understanding LLM generalization using influence functions
Scott Niekum—Models of human preferences for learning reward functions
Aleksander Madry—Faster datamodels as a new approach to alignment
Andreas Stuhlmuller—Iterated decomposition: improving science Q&A by supervising reasoning processes
Paul Christiano—Mechanistic anomaly detection
Lionel Levine—Social dynamics of reinforcement learners
Vincent Conitzer—Foundations of cooperative AI lab
Scott Aaronson—Cryptographic backdoors in large language models

(Note: some parts of the video with audience questions are inaudible)