IEEE Std 3198-2025 IEEE 机器学习公平性评估方法标准

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IEEE Standard for Evaluaon Method

of Machine Learning Fairness

IEEE Std 3198™-2025

IEEE Computer Society

Developed by the

Arcial Intelligence Standards Commiee

STANDARDS

IEEE Std 3198™-2025

IEEE Standard for Evaluation Method

of Machine Learning Fairness

Developed by the

Artificial Intelligence Standards Committee

of the

IEEE Computer Society

Approved 12 February 2025

IEEE SA Standards Board

Abstract: A method for evaluating the fairness of machine learning is specified in this standard.

Multiple causes contribute to the unfairness of machine learning. These causes of machine learning

unfairness are categorized. The widely recognized and used definitions of machine learning fairness

are presented. Various metrics corresponding to the definitions, and how to calculate the metrics

are specified in this standard. Detailed conditions and procedures to set up the tests for evaluating

machine learning fairness are given by the test cases in this document.

Keywords: bias, evaluation method, evaluation metric, fairness, IEEE 3198™, machine learning

The Institute of Electrical and Electronics Engineers, Inc.

3 Park Avenue, New York, NY 10016-5997, USA

Published 26 May 2025. Printed in the United States of America.

IEEE is a registered trademark in the U.S. Patent & Trademark Oce, owned by The Institute of Electrical and Electronics Engineers,

Incorporated.

PDF: ISBN 979-8-8557-2176-8 STD27916

Print: ISBN 979-8-8557-2177-5 STDPD27916

IEEE prohibits discrimination, harassment, and bullying.

For more information, visit https:// www .ieee .org/ about/ corporate/ governance/ p9 -26 .html.

No part of this publication may be reproduced in any form, in an electronic retrieval system or otherwise, without the prior written permission

of the publisher.

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标签： #评估 #评估方法 #机器

摘要：

IEEE Std 3198-2025 是电气电子工程师学会（IEEE）发布的关于机器学习公平性评估方法的国际标准。该标准旨在为开发、部署和审计人工智能系统的组织提供系统化、可操作的公平性评估框架，涵盖数据偏差检测、模型歧视分析、多种公平性指标计算（如均等几率、差异性影响）以及审计报告生成等环节。标准适用于金融、医疗、司法、招聘等高风险应用场景，帮助利益相关方识别并缓解因种族、性别、年龄等敏感属性导致的算法偏见，确保AI决策在技术合规与社会伦理层面符合公平性要求。通过遵循本标准，企业可提升模型透明

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IEEE Std 3198-2025 IEEE 机器学习公平性评估方法标准

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