{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,11]],"date-time":"2025-07-11T11:10:07Z","timestamp":1752232207477,"version":"3.41.2"},"publisher-location":"Cham","reference-count":8,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031703706"},{"type":"electronic","value":"9783031703713"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-70371-3_31","type":"book-chapter","created":{"date-parts":[[2024,8,31]],"date-time":"2024-08-31T23:31:13Z","timestamp":1725147073000},"page":"413-417","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Subgroup Harm Assessor: Identifying Potential Fairness-Related Harms and\u00a0Predictive Bias"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-7232-0487","authenticated-orcid":false,"given":"Adam","family":"Dubowski","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2046-1299","authenticated-orcid":false,"given":"Hilde","family":"Weerts","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-9003-2378","authenticated-orcid":false,"given":"Anouk","family":"Wolters","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4955-0743","authenticated-orcid":false,"given":"Mykola","family":"Pechenizkiy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,8,22]]},"reference":[{"key":"31_CR1","doi-asserted-by":"crossref","unstructured":"Barocas, S., Selbst, A.D.: Big data\u2019s disparate impact. California Law Rev. 671\u2013732 (2016)","DOI":"10.2139\/ssrn.2477899"},{"key":"31_CR2","unstructured":"Bellamy, R.K.E., et al.: AI fairness 360: an extensible toolkit for detecting, understanding, and mitigating unwanted algorithmic bias (2018). https:\/\/arxiv.org\/abs\/1810.01943"},{"key":"31_CR3","unstructured":"Kearns, M., Neel, S., Roth, A., Wu, Z.S.: Preventing fairness gerrymandering: auditing and learning for subgroup fairness. In: International Conference on Machine Learning. PMLR (2018)"},{"key":"31_CR4","unstructured":"Lundberg, S.M., Lee, S.I.: A unified approach to interpreting model predictions. In: Advances in Neural Information Processing Systems (2017)"},{"key":"31_CR5","doi-asserted-by":"crossref","unstructured":"Petersen, E., Ganz, M., Holm, S., Feragen, A.: On (assessing) the fairness of risk score models. In: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, pp. 817\u2013829 (2023)","DOI":"10.1145\/3593013.3594045"},{"key":"31_CR6","unstructured":"Pulizzi, M.: Identification of unequally treated subgroups in machine learning models through top-k subgroup discovery techniques. tue.nl (2021)"},{"key":"31_CR7","unstructured":"Weerts, H., Dud\u00edk, M., Edgar, R., Jalali, A., Lutz, R., Madaio, M.: Fairlearn: assessing and improving fairness of AI systems. arXiv:2303.16626 (2023)"},{"key":"31_CR8","doi-asserted-by":"crossref","unstructured":"Weerts, H., Xenidis, R., Tarissan, F., Olsen, H.P., Pechenizkiy, M.: Algorithmic unfairness through the lens of EU non-discrimination law: or why the law is not a decision tree. In: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, pp. 805\u2013816 (2023)","DOI":"10.1145\/3593013.3594044"}],"container-title":["Lecture Notes in Computer Science","Machine Learning and Knowledge Discovery in Databases. Research Track and Demo Track"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-70371-3_31","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,11]],"date-time":"2025-07-11T10:40:24Z","timestamp":1752230424000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-70371-3_31"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031703706","9783031703713"],"references-count":8,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-70371-3_31","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"22 August 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECML PKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vilnius","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lithuania","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 September 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecml2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/2024.ecmlpkdd.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}