Fairness in machine learning:definition,testing,debugging,and application

Xuanqi GAO ¹Chao SHEN ¹Weipeng JIANG ¹Chenhao LIN ¹Qian LI ¹Qian WANG ²Qi LI ³Xiaohong GUAN¹

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作者信息

1. Faculty of Electronic and Information Engineering,Xi'an Jiaotong University,Xi'an 710049,China
2. School of Cyber Science and Engineering,Wuhan University,Wuhan 430072,China
3. Institute for Network Sciences and Cyberspace,Tsinghua University,Beijing 100084,China
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Abstract

In recent years,artificial intelligence technology has been widely used in many fields,such as computer vision,natural language processing and autonomous driving.Machine learning algorithms,as the core technique of AI,have significantly facilitated people's lives.However,underlying fairness issues in machine learning systems can pose risks to individual fairness and social security.Studying fairness definitions,sources of problems,and testing and debugging methods of fairness can help ensure the fairness of machine learning systems and promote the wide application of artificial intelligence technology in various fields.This paper introduces relevant definitions of machine learning fairness and analyzes the sources of fairness problems.Besides,it provides guidance on fairness testing and debugging methods and summarizes popular datasets.This paper also discusses the technical advancements in machine learning fairness and highlights future challenges in this area.

Key words

artificial intelligence security/machine learning security/machine learning fairness/model test-ing/model debugging

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基金项目

National Key R&D Program of China(2020AAA0107702)

National Natural Science Foundation of China(U21B2018)

National Natural Science Foundation of China(62161160337)

National Natural Science Foundation of China(62132011)

National Natural Science Foundation of China(62206217)

National Natural Science Foundation of China(62376210)

National Natural Science Foundation of China(62006181)

National Natural Science Foundation of China(U20B2049)

National Natural Science Foundation of China(U20A20177)

Shaanxi Province Key Industry Innovation Program(2023-ZDLGY-38)

Shaanxi Province Key Industry Innovation Program(2021ZDLGY01-02)

China Postdoctoral Science Foundation(2022M722530)

China Postdoctoral Science Foundation(2023T160512)

Fundamental Research Funds for the Central Universities(xtr052023004)

Fundamental Research Funds for the Central Universities(xtr022019002)

Fundamental Research Funds for the Central Universities(xzy012022082)

出版年

2024

中国科学:信息科学(英文版)

中国科学院

中国科学:信息科学(英文版)

CSTPCDEI

影响因子：0.715

ISSN：1674-733X

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