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Watch a thought-provoking lecture from Chenhao Tan, assistant professor at the University of Chicago, exploring how human goals can better guide AI development than human preferences alone. Discover innovative approaches to AI development through two key examples: leveraging controlled hallucination for scientific hypothesis generation and developing case-based explanations for AI-assisted decision making. Learn how compromising strict faithfulness to achieve specific human objectives can lead to more effective complementary AI systems. Explore the critical balance between innovation and faithfulness in AI development, particularly in identifying bias mechanisms. Benefit from Tan's extensive expertise in human-centered AI, natural language processing, and computational social science, supported by his impressive academic background and numerous prestigious awards including a Sloan research fellowship and NSF CAREER award.
