Fairlearn: Assessing and Improving Fairness of AI Systems
About
Fairlearn is an open source project to help practitioners assess and improve fairness of artificial intelligence (AI) systems. The associated Python library, also named fairlearn, supports evaluation of a model's output across affected populations and includes several algorithms for mitigating fairness issues. Grounded in the understanding that fairness is a sociotechnical challenge, the project integrates learning resources that aid practitioners in considering a system's broader societal context.
Hilde Weerts, Miroslav Dud\'ik, Richard Edgar, Adrin Jalali, Roman Lutz, Michael Madaio• 2023
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Size-adaptive Hypothesis Testing for Fairness | Adult (subgroups) | Confidence Interval-0.13 | 28 |
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