Repairing Regressors for Fair Binary Classification at Any Decision Threshold

no code implementations • 14 Mar 2022 • Kweku Kwegyir-Aggrey, A. Feder Cooper, Jessica Dai, John Dickerson, Keegan Hines, Suresh Venkatasubramanian

We study the problem of post-processing a supervised machine-learned regressor to maximize fair binary classification at all decision thresholds.

Binary Classification Classification +1

Model Selection's Disparate Impact in Real-World Deep Learning Applications

no code implementations • 1 Apr 2021 • Jessica Zosa Forde, A. Feder Cooper, Kweku Kwegyir-Aggrey, Chris De Sa, Michael Littman

Algorithmic fairness has emphasized the role of biased data in automated decision outcomes.

Fairness Model Selection

Everything is Relative: Understanding Fairness with Optimal Transport

no code implementations • 20 Feb 2021 • Kweku Kwegyir-Aggrey, Rebecca Santorella, Sarah M. Brown

To study discrimination in automated decision-making systems, scholars have proposed several definitions of fairness, each expressing a different fair ideal.

Decision Making Fairness