Data, algorithms, and systems have biases embedded within them reflecting designers' explicit and implicit choices, historical biases, and societal priorities. They form, literally and inexorably, a codification of values. "Unfairness" of algorithms – for tasks ranging from advertising to recidivism prediction – has attracted considerable attention in the popular press. The talk will discuss the nascent mathematically rigorous study of fairness in classification and scoring.
Cynthia Dwork is the Gordon McKay Professor of Computer Science at the Paulson School of Engineering and Applied Sciences, the Radcliffe Alumnae Professor at the Radcliffe Institute for Advanced Study, and an Affiliated Faculty Member at Harvard Law School. She has done seminal work in disributed computing, cryptography, and privacy-preserving data analysis. Her most recent foci include stability in adaptive data analysis (especially via differential privacy) and fairness in classification.