Advancing Societal Decision-making through Human-AI Collaboration (Oct 31)

Speaker: Yifang Wang

Date: Oct 31, 2:15 – 3:05 PM

Abstract: Societal decision-making involves high-stakes, long-term choices that shape the future of communities, nations, and human collectives. From science policy-makers accelerating technological innovation to urban planners tackling social segregation, addressing these challenges requires a systematic understanding and analysis of complex social issues and human behaviors. While the availability of massive data has revolutionized our understanding of these problems, its scale and heterogeneity present new challenges in capturing complex social mechanisms and exploring actionable insights. This talk will present a line of interdisciplinary research to develop computational methods, including visualization and AI techniques, and intuitive user interfaces, to enhance societal decision-making with human-AI collaboration. Three key modes of human-AI collaboration will be introduced: (1) Strong AI-driven decision support, where AI models assist humans in making efficient choices, demonstrated by a data-driven platform for accelerating the research commercialization process; (2) Weak AI as an analytical aid, where AI distills knowledge to help humans explore complex social questions; and (3) Generative AI for flexible human-AI collaboration, enabling more natural, adaptive, and efficient analysis workflows in data-driven discovery. The talk concludes with future directions for advancing data-driven discovery and decision-making through human–AI collaboration.

Location: LOV 307 and ZOOM