Allen Lavoie
Ph.D. Candidate
Department of Computer Science
Washington University in St. Louis

"Quantifying Incentives in Collective Intelligence"

Monday, February 15, 4:00 PM
Packard Lab room 466

Abstract:  Social media facilitate interaction and information dissemination among an unprecedented number of participants. Why do users contribute, and why do they contribute to a specific venue? Does the information they receive cover all relevant points of view, or is it biased? The substantial and increasing importance of online communication makes these questions more pressing, but also puts answers within reach of automated methods. I will discuss scalable algorithms for understanding two classes of incentives which arise in collective intelligence: product incentives, which exist when contributors have a stake in the information delivered to other users, and process incentives, when users find contributing to be intrinsically rewarding.

Bio:   Allen Lavoie is a doctoral candidate in the Department of Computer Science at Washington University in St. Louis. His research interests are in artificial intelligence and machine learning, with applications to understanding large online social processes. His work has appeared in top venues, including AAAI, ICML, and AAMAS. He seeks a comprehensive understanding of collective intelligence, and to use this understanding to address emerging societal issues such as ideological polarization.

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