Omer Reingold (Stanford) Talk - Irif's Distinguished Talk Series

On May 14, 2024 IRIF welcomed Omer Reingold (Stanford) for a talk about " The multitude of group affiliations: Algorithmic Fairness, Loss Minimization and Outcome Indistinguishability"
Abstract: We will survey a rather recent and very fruitful line of research in algorithmic fairness, coined multi-group fairness. We will focus on risk prediction, where a machine learning algorithm tries to learn a predictor to answer questions of the form “what is the probability that patient x will experience a particular medical condition?” Training a risk predictor to minimize a loss function fixed in advance is the dominant paradigm in machine learning. However, global loss minimization may create predictions that are mis-calibrated on sub-populations, causing harm to individuals of these populations. Multi-group fairness tries to prevent forms of discrimination to a rich (possibly exponential) collection of arbitrarily intersecting groups. In a sense, it provides a computational perspective on the meaning of individual risks and the classical tension between clinical prediction, which uses individual-level traits, and actuarial prediction, which uses group-level traits.
While motivated in fairness, this alternative paradigm for training an indistinguishable predictor is finding a growing number of appealing applications, where the same predictor can later be used to optimize one of a large set of loss functions, under a family of capacity and fairness constraints and instance distributions.
Based on a sequence of works joint with (subsets of) Cynthia Dwork, Shafi Goldwasser, Parikshit Gopalan, Úrsula Hébert-Johnson, Lunjia Hu, Adam Kalai, Christoph Kern, Michael P. Kim, Frauke Kreuter, Guy N. Rothblum, Vatsal Sharan, Udi Wieder, Gal Yona and others.
__________________________
BIOGRAPHY
Omer Reingold is the Rajeev Motwani professor of computer science at Stanford University and the director of the Simons Collaboration on the Theory of Algorithmic Fairness.
Past positions include the Weizmann Institute of Science, Microsoft Research, the Institute for Advanced Study in Princeton, NJ, AT&T Labs and Samsung Research America.
His research is in the foundations of computer science and most notably in computational complexity, cryptography and the societal impact of computation. He is an ACM Fellow and a Simons Investigator. Among his distinctions are the 2005 Grace Murray Hopper Award and the 2009 Gödel Prize.