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The Limits of Group Fairness and Predictive Multiplicity

Offered By: Simons Institute via YouTube

Tags

Group Fairness Courses Machine Learning Courses Information Theory Courses Algorithmic Decision-Making Courses

Course Description

Overview

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Explore the boundaries of group fairness and predictive multiplicity in machine learning through this insightful lecture by Flavio Calmon from Harvard University. Delve into information-theoretic methods for developing trustworthy machine learning systems, examining the challenges and limitations of achieving fairness across different groups. Gain a deeper understanding of how multiple predictive models can impact decision-making processes and the implications for creating more equitable AI systems.

Syllabus

The Limits of Group Fairness and Predictive Multiplicity


Taught by

Simons Institute

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