CHAI’s mission is to develop the conceptual and technical wherewithal to reorient the general thrust of AI research towards provably beneficial systems.
Highlights
Forget deepfake videos. Text and voice are this election’s true AI threat.
Jonathan Stray, Senior Scientist at CHAI, and Jessica Alter, tech entrepreneur and co-founder of Tech for Campaigns, wrote an op-ed for The Hill regarding the risks posed by AI in this current election cycle.
AI Alignment with Changing and Influenceable Reward Functions
CHAI Researchers, Micah Carroll, Davis Foote, Anand Siththaranjan, Stuart Russell, and Anca Dragan, wrote the paper, “AI Alignment with Changing and Influenceable Reward Functions” which was accepted to ICML.
Mitigating Partial Observability in Decision Processes via the Lambda Discrepancy
This paper investigates fundamental concepts related to detecting and mitigating partial observability by measuring misalignment between value function estimates. The paper was presented at the “Finding the Frame” workshop at RLC 2024 and the “Foundations of Reinforcement Learning and Control” workshop at ICML 2024.
Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback
Rachel Feedman, CHAI Phd Student, and Wes Holliday, CHAI Affiliate, published a paper at the International Conference on Machine Learning
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