Outcome indistinguishability
Cynthia Dwork, Michael P. Kim, Omer Reingold, Guy N. Rothblum, Gal Yona · 2021
Prediction algorithms assign numbers to individuals that are popularly understood as individual “probabilities”—what is the probability of 5-year survival after cancer diagnosis?—and which increasingly form the basis for life-altering decisions. Drawing on an understanding of computational indistinguishability developed in complexity theory and cryptography, we introduce Outcome Indistinguishability. Predictors that are Outcome Indistinguishable (OI) yield a generative model for outcomes that cannot be efficiently refuted on the basis of the real-life observations produced by .