560 citations · 2.1k across the 38 of their papers we have counts for
4 papers · 1 filter
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
Michael Kearns, Seth Neel, Aaron Roth +1
The most prevalent notions of fairness in machine learning are statistical definitions: they fix a small collection of pre-defined groups, and then ask for parity of some statistic…
A Convex Framework for Fair Regression
Richard Berk, Hoda Heidari, Shahin Jabbari +5
We introduce a flexible family of fairness regularizers for (linear and logistic) regression problems. These regularizers all enjoy convexity, permitting fast optimization, and the…
Fairness Incentives for Myopic Agents
Sampath Kannan, Michael Kearns, Jamie Morgenstern +4
We consider settings in which we wish to incentivize myopic agents (such as Airbnb landlords, who may emphasize short-term profits and property safety) to treat arriving clients fa…
Fairness in Criminal Justice Risk Assessments: The State of the Art
Richard A. Berk, Hoda Heidari, Shahin Jabbari +2
Objectives: Discussions of fairness in criminal justice risk assessments typically lack conceptual precision. Rhetoric too often substitutes for careful analysis. In this paper, we…