Please join the Decision Analysis Society for our next webinar, delivered by Professor Michael Lee from UC Irvine, on January 24, at 12pm EST.
You can register to the webinar here: https://us06web.zoom.us/meeting/register/tZIsduCqrT0rGdT8G3BY1l49PdaE-XGJdLnh#/registration
Michael Lee is a Professor of Cognitive Sciences at the University of California, Irvine. He is a former President of the Society of Mathematical Psychology, and winner of the William K Estes Award from that Society. His research involves the development, evaluation, and application of models of cognition including representation, memory, learning, and decision making, with a special focus on individual differences and collective cognition. His research emphasizes the use of naturally occurring behavioral data, and tries to pursue a solution-oriented approach to empirical science, in which the research questions are generated from real-world problems. His research methods focus on probabilistic generative modeling and Bayesian methods of computational analysis.
Talk Title: Using decision-making models to improve the wisdom of the crowd
Talk Abstract: The wisdom of the crowd is the idea that aggregated group decisions can outperform most or even all of the individuals in the group. We argue that cognitive models, built on an understanding of people's judgment and decision making, can further improve the wisdom of the crowd in four ways. The first way is that they can infer and upweight expertise among individuals. The second is that they can be used to debias cognitive processes by inferring what people know from how they behave. The third is that they can provide a representational scaffolding for combining knowledge that is multidimensional in nature and distributed across individuals. Finally, cognitive models can maintain the diversity of a crowd by producing predictions that act as surrogates for unavailable behavioral data. We demonstrate these ideas in a range of decision-making settings including probability estimation, ranking, spatial knowledge, competitive bidding, and sequential decision making. We also highlight how studying these applied knowledge aggregation problems helps identify new creative directions in the development of basic theories and models of decision making.
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Yael Grushka-Cockayne
Altec Styslinger Foundation Bicentennial Chair in Business Administration
University of Virginia
Charlottesville VA VA
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