Fairlearn: Assessing and Improving Fairness of AI Systems
Abstract
Fairlearn provides tools to evaluate and enhance the fairness of AI systems, incorporating various algorithms and learning resources to address sociotechnical challenges.
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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Generate a summary explaining how Fairlearn helps ensure fairness in AI systems by detecting and mitigating bias across gender groups in income prediction tasks. Include an example using the Adult Income Dataset and explain how Demographic Parity Difference is calculated
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