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Scott Page

Professor at the University of Michigan and author of The Model Thinker. Expert in game theory, complex systems, and diversity.

Top 3 podcasts with Scott Page

Ranked by the Snipd community
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132 snips
Apr 2, 2019 • 1h 27min

#55 Scott Page: Becoming a Model Thinker

On this episode, Scott Page, 5x Author and Professor of Complex Systems at the University of Michigan explains the power mental models have in how we view the world, discover creative solutions and solve complex problems.   Go Premium: Members get early access, ad-free episodes, hand-edited transcripts, searchable transcripts, member-only episodes, and more. Sign up at: https://fs.blog/membership/   Every Sunday our newsletter shares timeless insights and ideas that you can use at work and home. Add it to your inbox: https://fs.blog/newsletter/   Follow Shane on Twitter at: https://twitter.com/ShaneAParrish   Learn more about your ad choices. Visit megaphone.fm/adchoices
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Sep 27, 2021 • 27min

Are All Models Wrong? | with Scott Page

Scott Page, Complexity, Social Science and Management professor at the University of Michigan, discusses the value of models and their uses in different disciplines. They explore the complexity of models, the importance of using multiple models to understand complex issues, and the role of models in decision-making. They also discuss problem-solving through game theory principles.
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May 26, 2019 • 48min

Mental Models with Scott Page

Scott Page, a professor at the University of Michigan and author of The Model Thinker, discusses the power of cognitive diversity in fostering innovative solutions. He explains why a wise crowd often outperforms individual experts and emphasizes that mastery lies in knowing when to use the right mental model. Page also dives into the evolution of basketball strategies, revealing parallels to collective decision-making. Listeners will find insights on improving venture capital through diverse perspectives and predictive modeling, making this conversation a must-listen for those interested in complex systems.