Scott E. Page

John Seely Brown Distinguished University Professor of Complexity, Social Science, and Management | Williamson Family Professor of Business Administration, Ross School of Business, University of Michigan-Ann Arbor | External Faculty, Santa Fe Institute

Scott E Page’s research focuses on the function of diversity in complex social systems, the potential for collective intelligence, and the design of institutions for a complex world.

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A recipient of a Guggenheim Fellowship, a fellowship at the Center for Advanced Studies in the Behavioral Sciences at Stanford, Scott was elected tothe National Academy of Sciences in 2025 and a fellow of the American Academy of Arts and Sciences in 2011, and in 2019, he was awarded a Distinguished University Professorship from the University of Michigan.

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He is the author of more than ninety research papers in a variety of fields including: game theory, economics, political theory, formal political science, sociology, psychology, philosophy, physics, public health, geography, computer science, and management. Scott is an editor of the Collective Intelligence journal.

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His fifth book, The Model Thinker (2018), has been an Amazon Best Seller in more than ten categories and is being translated into five languages. His previous books include, the Axios award winning, The Diversity Bonus,(2017) with Princeton University Press and the Mellon Foundation, The Difference: How the Power of Diversity Creates Better Groups, Firms,Schools, and Societies (2008) and was re-released by Princeton Press Classic in 2025, and Complex Adaptive Social Systems(2009).

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Scott has also filmed two video series for The Great Courses and his online course Model Thinking has attracted over a million participants. A frequent public speaker, Scott has presented to the CIA, NASA, Bloomberg, Google, Boeing, the IMF, Genentech, Gilead, and AT Kearney. Scott has also been a featured speaker at The New York Times New Work Summit, Google Re:Work, The World Economic Forum — Davos, and The Aspen Ideas Festival. Scott has consulted with the Federal Reserve System, the White House office of Personnel, Yahoo! Ford, DARPA, Procter and Gamble, BlackRock, and AB InBev.

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A native of Yankee Springs Michigan, Scott holds a BA in mathematics from The University of Michigan, and MA from The University of Wisconsin, and an MS and PhD in managerial economics and decision sciences from the Kellogg School at Northwestern University.

Topics

Model Thinking: One to Many & Many to One

Each new model that a person masters becomes a tool that can be applied in many contexts. For example, a model of negative feedbacks can help us both understand and design thermostats, markets, and braking systems. By definition, models simplify — they isolate and highlight the important parts of a system. But the world in which we now live has become complex, and no one simple model can capture all of the important parts. The intelligent response to that complexity lies not in making our models ever more complex, but in applying ensembles of models. We should strive to become many model thinkers.

Leveraging Diversity

Why can teams of people find better solutions than brilliant individuals working alone? And why are the best group decisions and predictions those that draw upon the very qualities that make each of us unique? The answers lie in diversity—not what we look like outside, but what we look like within, our distinct tools and abilities. In this lecture, Scott Page explains how to use diversity to improve an organization’s predictions, decisions and problem-solving capabilities. Moving beyond the politics that cloud standard debates about diversity, Scott discusses why difference beats out homogeneity, whether you're talking about citizens in a democracy or scientists in the laboratory, and why diversity trumps ability. He examines practical ways to apply diversity's logic to a host of problems, and along the way offers surprising examples, from the redesign of the Chicago "El" to the truth about where we store our ketchup. The talk links to smart mobs, wise crowds, identity diversity, globalization, and interdisciplinary science. The same logic that shows how cognitive diversity improves the performance of a predictive market can show how including identity diverse — and experientially and vocationally diverse — people improves the performance of a problem-solving team.