Algorithmic Fairness and Individual Probabilities

Algorithmic Fairness and Individual Probabilities

Explore the theory of algorithmic fairness and its implications in this 54-minute conference talk by Cynthia Dwork from Harvard University. Delve into fundamental questions raised by algorithmic fairness, focusing on the concept of "individual probability." Examine the proposed notion of Outcome Indistinguishability and its wide-ranging applications. Gain insights into the intersection of mathematics, deep learning, and trustworthy artificial intelligence. Learn about emerging directions in AI accountability, fairness, privacy, and safety. Understand how this research impacts academia, industry, policymaking, and society at large.