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Surv."],"published-print":{"date-parts":[[2022,7,31]]},"abstract":"<jats:p>With the widespread use of artificial intelligence (AI) systems and applications in our everyday lives, accounting for fairness has gained significant importance in designing and engineering of such systems. AI systems can be used in many sensitive environments to make important and life-changing decisions; thus, it is crucial to ensure that these decisions do not reflect discriminatory behavior toward certain groups or populations. More recently some work has been developed in traditional machine learning and deep learning that address such challenges in different subdomains. With the commercialization of these systems, researchers are becoming more aware of the biases that these applications can contain and are attempting to address them. In this survey, we investigated different real-world applications that have shown biases in various ways, and we listed different sources of biases that can affect AI applications. We then created a taxonomy for fairness definitions that machine learning researchers have defined to avoid the existing bias in AI systems. In addition to that, we examined different domains and subdomains in AI showing what researchers have observed with regard to unfair outcomes in the state-of-the-art methods and ways they have tried to address them. There are still many future directions and solutions that can be taken to mitigate the problem of bias in AI systems. We are hoping that this survey will motivate researchers to tackle these issues in the near future by observing existing work in their respective fields.<\/jats:p>","DOI":"10.1145\/3457607","type":"journal-article","created":{"date-parts":[[2021,7,13]],"date-time":"2021-07-13T16:48:08Z","timestamp":1626194888000},"page":"1-35","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3513,"title":["A Survey on Bias and Fairness in Machine Learning"],"prefix":"10.1145","volume":"54","author":[{"given":"Ninareh","family":"Mehrabi","sequence":"first","affiliation":[{"name":"USC-ISI"}]},{"given":"Fred","family":"Morstatter","sequence":"additional","affiliation":[{"name":"USC-ISI"}]},{"given":"Nripsuta","family":"Saxena","sequence":"additional","affiliation":[{"name":"USC-ISI"}]},{"given":"Kristina","family":"Lerman","sequence":"additional","affiliation":[{"name":"USC-ISI"}]},{"given":"Aram","family":"Galstyan","sequence":"additional","affiliation":[{"name":"USC-ISI"}]}],"member":"320","published-online":{"date-parts":[[2021,7,13]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Proceedings of the International Conference on Machine Learning. 120\u2013129","author":"Agarwal Alekh","year":"2019"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33011418"},{"key":"e_1_2_1_3_1","volume-title":"Proceedings of the 11th ACM International Conference on Web Search and Data Mining. 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UCI Machine Learning Repository. Retrieved from http:\/\/www.ics.uci.edu\/$\u2216sim$mlearn\/{MLR}epository.html.  A. Asuncion and D. J. Newman. 2007. UCI Machine Learning Repository. Retrieved from http:\/\/www.ics.uci.edu\/$\u2216sim$mlearn\/{MLR}epository.html."},{"key":"e_1_2_1_8_1","volume-title":"Proceedings of the 36th International Conference on Machine Learning (Proceedings of Machine Learning Research), Kamalika Chaudhuri and Ruslan Salakhutdinov (Eds.)","volume":"97","author":"Backurs Arturs","year":"2019"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3209581"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2872427.2883083"},{"key":"e_1_2_1_11_1","volume-title":"Aleksandra Mojsilovic et\u00a0al","author":"Bellamy Rachel K. 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D. P. Binns. 2018. Fairness in machine learning: Lessons from political philosophy. J. Mach. Learn. Res. (2018)."},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1972.10482387"},{"key":"e_1_2_1_19_1","volume-title":"Help Wanted: An Examination of Hiring Algorithms, Equity and Bias. Technical Report. 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Wasserstein fair classification. In Uncertainty in Artificial Intelligence. PMLR 862\u2013872.  Ray Jiang Aldo Pacchiano Tom Stepleton Heinrich Jiang and Silvia Chiappa. 2020. Wasserstein fair classification. In Uncertainty in Artificial Intelligence. PMLR 862\u2013872."},{"key":"e_1_2_1_74_1","volume-title":"Proceedings of the 2nd International Conference on Computer, Control and Communication. 1\u20136. DOI:DOI:https:\/\/doi.org\/10","author":"Kamiran F.","year":"2009"},{"key":"e_1_2_1_75_1","volume-title":"Proceedings of the 19th Machine Learning Conference. Citeseer, 1\u20136.","author":"Kamiran Faisal","year":"2010"},{"key":"e_1_2_1_76_1","volume-title":"Data preprocessing techniques for classification without discrimination. Knowl. Inf. 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Larson S. Mattu L. Kirchner and J. Angwin. 2016. Compas analysis. Retrieved from https:\/\/github.com\/propublica\/compas-analysis.  J. Larson S. Mattu L. Kirchner and J. Angwin. 2016. Compas analysis. Retrieved from https:\/\/github.com\/propublica\/compas-analysis."},{"key":"e_1_2_1_90_1","doi-asserted-by":"publisher","DOI":"10.1145\/3278721.3278779"},{"key":"e_1_2_1_91_1","doi-asserted-by":"publisher","DOI":"10.1007\/s42001-017-0007-4"},{"key":"e_1_2_1_92_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0098914"},{"key":"e_1_2_1_93_1","volume-title":"Does mitigating ML\u2019s disparate impact require disparate treatment?stat 1050","author":"Lipton Zachary C.","year":"2017"},{"key":"e_1_2_1_94_1","volume-title":"Proceedings of the 35th International Conference on Machine Learning.","author":"Liu Lydia T.","year":"2018"},{"key":"e_1_2_1_95_1","volume-title":"Causal reasoning for algorithmic fairness. arXiv preprint arXiv:1805.05859","author":"Loftus Joshua R.","year":"2018"},{"key":"e_1_2_1_96_1","volume-title":"The variational fair autoencoder. stat 1050","author":"Louizos Christos","year":"2016"},{"key":"e_1_2_1_97_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMsa1507092"},{"key":"e_1_2_1_98_1","first-page":"849","article-title":"The economics of racial discrimination: A survey","volume":"12","author":"Marshall Ray","year":"1974","journal-title":"J. Econ. Lit."},{"key":"e_1_2_1_99_1","volume-title":"On measuring social biases in sentence encoders. arXiv preprint arXiv:1903.10561","author":"May Chandler","year":"2019"},{"key":"e_1_2_1_100_1","volume-title":"Man is to person as woman is to location: Measuring gender bias in named entity recognition. arXiv preprint arXiv:1910.10872","author":"Mehrabi Ninareh","year":"2019"},{"key":"e_1_2_1_101_1","volume-title":"Debiasing community detection: The importance of lowly-connected nodes. arXiv preprint arXiv:1903.08136","author":"Mehrabi Ninareh","year":"2019"},{"key":"e_1_2_1_102_1","volume-title":"Proceedings of the 1st Conference on Fairness, Accountability and Transparency (Proceedings of Machine Learning Research), Sorelle A. Friedler and Christo Wilson (Eds.)","volume":"81","author":"Menon Aditya Krishna"},{"key":"e_1_2_1_103_1","volume-title":"Smith","author":"Merler Michele","year":"2019"},{"key":"e_1_2_1_104_1","volume-title":"Proceedings of the 10th International AAAI Conference on Web and Social Media.","author":"Miller Hannah Jean","year":"2016"},{"key":"e_1_2_1_105_1","doi-asserted-by":"crossref","unstructured":"I. Minchev G. Matijevic D. W. Hogg G. Guiglion M. Steinmetz F. Anders C. Chiappini M. Martig A. Queiroz and C. Scannapieco. 2019. Yule-Simpson\u2019s paradox in galactic archaeology. arXiv preprint arXiv:1902.01421 (2019).  I. Minchev G. Matijevic D. W. Hogg G. Guiglion M. Steinmetz F. Anders C. Chiappini M. Martig A. Queiroz and C. Scannapieco. 2019. Yule-Simpson\u2019s paradox in galactic archaeology. arXiv preprint arXiv:1902.01421 (2019).","DOI":"10.1093\/mnras\/stz1239"},{"key":"e_1_2_1_106_1","doi-asserted-by":"publisher","DOI":"10.1145\/3287560.3287596"},{"key":"e_1_2_1_107_1","volume-title":"Carley","author":"Morstatter Fred","year":"2013"},{"key":"e_1_2_1_108_1","volume-title":"Proceedings of the International Conference on Advances in Neural Information Processing Systems. 9084\u20139093","author":"Moyer Daniel","year":"2018"},{"key":"e_1_2_1_109_1","doi-asserted-by":"publisher","DOI":"10.1111\/1475-3995.00375"},{"key":"e_1_2_1_110_1","doi-asserted-by":"publisher","DOI":"10.1162\/rest.2003.85.1.205"},{"key":"e_1_2_1_111_1","volume-title":"Learning optimal fair policies. arXiv preprint arXiv:1809.02244","author":"Nabi Razieh","year":"2018"},{"key":"e_1_2_1_112_1","volume-title":"Proceedings of the 32nd AAAI Conference on Artificial Intelligence.","author":"Nabi Razieh","year":"2018"},{"key":"e_1_2_1_113_1","volume-title":"Filippo Menczer, and Alessandro Flammini.","author":"Nematzadeh Azadeh","year":"2017"},{"key":"e_1_2_1_114_1","volume-title":"Twitter. In Proceedings of the 7th International AAAI Conference on Weblogs and Social Media (ICWSM \u201913)","author":"Nguyen Dong-Phuong","year":"2013"},{"key":"e_1_2_1_115_1","doi-asserted-by":"crossref","volume-title":"The Routledge Handbook of Corpus Linguistics","author":"O\u2019Keeffe Anne","DOI":"10.4324\/9780367076399"},{"key":"e_1_2_1_116_1","doi-asserted-by":"publisher","DOI":"10.3389\/fdata.2019.00013"},{"key":"e_1_2_1_117_1","volume-title":"Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy","author":"O\u2019Neil Cathy"},{"key":"e_1_2_1_118_1","doi-asserted-by":"publisher","DOI":"10.1145\/3306618.3314255"},{"key":"e_1_2_1_119_1","volume-title":"Osoba and William Welser IV","author":"Osonde","year":"2017"},{"key":"e_1_2_1_120_1","first-page":"659","article-title":"The statistical theory of racism and sexism","volume":"62","author":"Phelps Edmund S.","year":"1972","journal-title":"Amer. Econ. 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UCI Machine Learning Repository : Retrieved from http:\/\/www.ics.uci.edu\/mlearn\/MLRepository.html."},{"key":"e_1_2_1_126_1","first-page":"583","article-title":"Race, gender, redlining, and the discriminatory access to loans, credit, and insurance: An historical and empirical analysis of consumers who sued lenders and insurers in federal and state courts, 1950\u20131995","volume":"33","author":"Rice Willy E.","year":"1996","journal-title":"San Diego L. 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([n.\u00a0d.])."},{"key":"e_1_2_1_140_1","volume-title":"Guttag","author":"Suresh Harini","year":"2019"},{"key":"e_1_2_1_141_1","doi-asserted-by":"publisher","DOI":"10.1145\/3322640.3326705"},{"key":"e_1_2_1_142_1","volume-title":"Proceedings of the 8th International AAAI Conference on Weblogs and Social Media.","author":"Tufekci Zeynep","year":"2014"},{"key":"e_1_2_1_143_1","volume-title":"Proceedings of the 36th International Conference on Machine Learning (Proceedings of Machine Learning Research), Kamalika Chaudhuri and Ruslan Salakhutdinov (Eds.)","volume":"97","author":"Ustun Berk","year":"2019"},{"key":"e_1_2_1_144_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D18-1334"},{"key":"e_1_2_1_145_1","doi-asserted-by":"publisher","DOI":"10.1145\/3194770.3194776"},{"key":"e_1_2_1_146_1","volume-title":"Chen Jr","author":"Vickers Selwyn","year":"2014"},{"key":"e_1_2_1_147_1","doi-asserted-by":"publisher","DOI":"10.1089\/big.2014.0063"},{"key":"e_1_2_1_148_1","first-page":"799","article-title":"The disparate impact model of discrimination: Theory and limits","volume":"34","author":"Willborn Steven L.","year":"1984","journal-title":"Amer. 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