Fairlearn: Assessing and Improving Fairness of AI Systems
Hilde Weerts, Miroslav Dudík, Richard Edgar, Adrin Jalali, Roman Lutz, Michael Madaio; 24(257):1−8, 2023.
Abstract
Fairlearn is a project aimed at assisting practitioners in evaluating and enhancing the fairness of artificial intelligence (AI) systems. The fairlearn Python library, which accompanies the project, enables the assessment of a model’s output across different populations and includes multiple algorithms for addressing fairness concerns. Recognizing that fairness is a complex sociotechnical issue, the project incorporates learning resources that help practitioners consider the broader societal implications of a system.
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