Fairlearn: Assessing and Improving Fairness of AI Systems

TL;DR

Fairlearn is an open source toolkit that enables practitioners to evaluate and enhance the fairness of AI systems, incorporating societal context and mitigation algorithms.

Contribution

It introduces a Python library with fairness assessment tools and mitigation algorithms, emphasizing societal considerations in AI fairness.

Findings

Provides tools for fairness evaluation across populations

Includes algorithms for mitigating fairness issues

Supports societal context integration

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.