Active PAR

P3198

Standard for Evaluation Method of Machine Learning Fairness

This standard specifies a method for evaluating the fairness of machine learning. Multiple causes contribute to the unfairness of machine learning. In the standard, these causes of machine leaning unfairness are categorized. The widely recognized and used definitions of machine learning are presented. The standard also specifies various metrics corresponding to the definitions, and how to calculate the metrics. Test cases in the standard give detailed conditions and procedures to set up tests for evaluating machine learning fairness.

Sponsor Committee
C/AISC - Artificial Intelligence Standards Committee
Status
Active PAR
PAR Approval
2022-11-10

Working Group Details

Society
IEEE Computer Society
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Sponsor Committee
C/AISC - Artificial Intelligence Standards Committee
Working Group
AIFE-WG - AI Fairness Evaluation Working Group
Learn More About AIFE-WG - AI Fairness Evaluation Working Group
IEEE Program Manager
Christy Bahn
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Working Group Chair
Juan Deng

Other Activities From This Working Group

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No Active Projects

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These standards are removed from active status through an administrative process for standards that have not undergone a revision process within 10 years.


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