267 citations · 958 across the 28 of their papers we have counts for
3 papers · 1 filter
A comparative study of fairness-enhancing interventions in machine learning
Sorelle A. Friedler, Carlos Scheidegger, Suresh Venkatasubramanian +3
Computers are increasingly used to make decisions that have significant impact in people's lives. Often, these predictions can affect different population subgroups disproportionat…
Auditing Black-box Models for Indirect Influence
Philip Adler, Casey Falk, Sorelle A. Friedler +4
Data-trained predictive models see widespread use, but for the most part they are used as black boxes which output a prediction or score. It is therefore hard to acquire a deeper u…
Certifying and removing disparate impact
Michael Feldman, Sorelle Friedler, John Moeller +2
What does it mean for an algorithm to be biased? In U.S. law, unintentional bias is encoded via disparate impact, which occurs when a selection process has widely different outcome…