Fairlearn: Assessing and Improving Fairness of AI Systems

2023/03/29 by Hilde Weerts, Weerts, Hilde, Miroslav Dudı́k +9 · 19 citations
Social Sciences · #Artificial Intelligence (cs.AI) #Computers and Society (cs.CY) #Ethics and Social Impacts of AI #FOS: Computer and information sciences #Machine Learning (cs.LG)

paper · pdf · doi:10.48550/arxiv.2303.16626

openalex publication_date 2023/03/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

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.

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