{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T07:37:09Z","timestamp":1767339429371,"version":"3.41.0"},"publisher-location":"Cham","reference-count":44,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031926471","type":"print"},{"value":"9783031926488","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-3-031-92648-8_4","type":"book-chapter","created":{"date-parts":[[2025,5,30]],"date-time":"2025-05-30T16:28:20Z","timestamp":1748622500000},"page":"53-67","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Fairness of\u00a0AI Systems in\u00a0the\u00a0Legal Context"],"prefix":"10.1007","author":[{"given":"Veronica","family":"Paternolli","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2761-4347","authenticated-orcid":false,"given":"Mila","family":"Dalla Preda","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9582-3960","authenticated-orcid":false,"given":"Roberto","family":"Giacobazzi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,5,12]]},"reference":[{"key":"4_CR1","doi-asserted-by":"publisher","first-page":"050","DOI":"10.30574\/gscarr.2024.18.3.0088","volume":"18","author":"O Akinrinola","year":"2024","unstructured":"Akinrinola, O., Okoye, C., Ofodile, O., Ugochukwu, C.: Navigating and reviewing ethical dilemmas in AI development strategies for transparency, fairness, and accountability. GSC Adv. Res. Rev. 18, 050\u2013058 (2024). https:\/\/doi.org\/10.30574\/gscarr.2024.18.3.0088","journal-title":"GSC Adv. Res. Rev."},{"key":"4_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2023.101805","volume":"99","author":"S Ali","year":"2023","unstructured":"Ali, S., et al.: Explainable artificial intelligence (XAI): what we know and what is left to attain trustworthy artificial intelligence. Inf. Fusion 99, 101805 (2023). https:\/\/doi.org\/10.1016\/j.inffus.2023.101805","journal-title":"Inf. Fusion"},{"key":"4_CR3","unstructured":"Ethics guidelines for trustworthy AI on\u00a0Artificial\u00a0Intelligence (2019). https:\/\/ec.europa.eu\/newsroom\/dae\/document.cfm?doc_id=60419. Accessed 28 June 2024"},{"key":"4_CR4","doi-asserted-by":"publisher","unstructured":"Bringas\u00a0Colmenarejo, A., et al.: Fairness in agreement with European values: an interdisciplinary perspective on AI regulation. In: Proceedings of the 2022 AAAI\/ACM Conference on AI, Ethics, and Society. AIES 2022, ACM, July 2022. https:\/\/doi.org\/10.1145\/3514094.3534158","DOI":"10.1145\/3514094.3534158"},{"key":"4_CR5","unstructured":"Buolamwini, J., Gebru, T.: Gender shades: intersectional accuracy disparities in commercial gender classification. In: Conference on Fairness, Accountability and Transparency, pp. 77\u201391 (2018)"},{"key":"4_CR6","unstructured":"Buolamwini, J., Gebru, T.: Gender shades: intersectional accuracy disparities in commercial gender classification. In: Friedler, S.A., Wilson, C. (eds.) Proceedings of the 1st Conference on Fairness, Accountability and Transparency. Proceedings of Machine Learning Research, vol.\u00a081, pp. 77\u201391. PMLR, 23\u201324 February 2018. https:\/\/proceedings.mlr.press\/v81\/buolamwini18a.html"},{"key":"4_CR7","doi-asserted-by":"publisher","unstructured":"Calvi, A., Malgieri, G., Kotzinos, D.: The unfair side of privacy enhancing technologies: addressing the trade-offs between pets and fairness. Association for Computing Machinery, New York, NY, USA (2024). https:\/\/doi.org\/10.1145\/3630106.3659024,","DOI":"10.1145\/3630106.3659024"},{"key":"4_CR8","unstructured":"Commission, E.: Liability rules for artificial intelligence (2022). https:\/\/commission.europa.eu\/business-economy-euro\/doing-business-eu\/contract-rules\/digital-contracts\/liability-rules-artificial-intelligence_en. Accessed 08 July 2024"},{"issue":"8","key":"4_CR9","doi-asserted-by":"publisher","first-page":"5209","DOI":"10.1109\/tpami.2024.3361979","volume":"46","author":"I Dominguez-Catena","year":"2024","unstructured":"Dominguez-Catena, I., Paternain, D., Galar, M.: Metrics for dataset demographic bias: a case study on facial expression recognition. IEEE Trans. Pattern Anal. Mach. Intell. 46(8), 5209\u20135226 (2024). https:\/\/doi.org\/10.1109\/tpami.2024.3361979","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"4_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/tpami.2024.3361979","volume":"46","author":"I Dominguez-Catena","year":"2024","unstructured":"Dominguez-Catena, I., Paternain, D., Galar, M.: Metrics for dataset demographic bias: a case study on facial expression recognition. IEEE Trans. Pattern Anal. Mach. Intell. 46, 1\u201318 (2024). https:\/\/doi.org\/10.1109\/tpami.2024.3361979","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"4_CR11","doi-asserted-by":"publisher","unstructured":"Dressel, J., Farid, H.: The accuracy, fairness, and limits of predicting recidivism. Sci. Adv. 4(1), eaao5580 (2018). https:\/\/doi.org\/10.1126\/sciadv.aao5580","DOI":"10.1126\/sciadv.aao5580"},{"key":"4_CR12","unstructured":"Dulhanty, C., Wong, A.: Auditing imagenet: towards a model-driven framework for annotating demographic attributes of large-scale image datasets. CoRR abs\/1905.01347 (2019). http:\/\/arxiv.org\/abs\/1905.01347"},{"key":"4_CR13","doi-asserted-by":"crossref","unstructured":"Dwork, C., Hardt, M., Pitassi, T., Reingold, O., Zemel, R.: Fairness through awareness (2011)","DOI":"10.1145\/2090236.2090255"},{"key":"4_CR14","unstructured":"Article 21 of the European convention on human rights (ECHR) of\u00a0Europe (1950). https:\/\/www.echr.coe.int\/Documents\/Convention_ENG.pdf. Accessed 28 June 2024"},{"key":"4_CR15","unstructured":"European Papers: AI regulation through the lens of fundamental rights (2024). https:\/\/www.europeanpapers.eu\/en\/europeanforum\/ai-regulation-through-the-lens-of-fundamental-rights. Accessed 30 June 2024"},{"key":"4_CR16","unstructured":"European Union: Regulation (EU) 2016\/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95\/46\/EC (General Data Protection Regulation) (2016). https:\/\/eur-lex.europa.eu\/eli\/reg\/2016\/679\/oj. Accessed 07 July 2024"},{"key":"4_CR17","unstructured":"European Union, European Parliament, and Council of the European Union: Regulation (EU) 2024\/... of the European Parliament and of the Council laying down harmonised rules on artificial intelligence and amending Regulations (EC) No 300\/2008, (EU) No 167\/2013, (EU) No 168\/2013, (EU) 2018\/858, (EU) 2018\/1139 and (EU) 2019\/2144 and Directives 2014\/90\/EU, (EU) 2016\/797 and (EU) 2020\/1828 (Artificial Intelligence Act) (2024). https:\/\/eur-lex.europa.eu\/legal-content\/EN\/TXT\/?uri=CELEX%3A52021PC0206"},{"key":"4_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11948-020-00276-4","volume":"26","author":"H Felzmann","year":"2020","unstructured":"Felzmann, H., Fosch-Villaronga, E., Lutz, C., Tam\u00f2-Larrieux, A.: Towards transparency by design for artificial intelligence. Sci. Eng. Ethics 26, 1\u201329 (2020). https:\/\/doi.org\/10.1007\/s11948-020-00276-4","journal-title":"Sci. Eng. Ethics"},{"key":"4_CR19","doi-asserted-by":"publisher","unstructured":"Fleisher, W.: What\u2019s fair about individual fairness? In: Association for Computing Machinery, New York, NY, USA (2021). https:\/\/doi.org\/10.1145\/3461702.3462621","DOI":"10.1145\/3461702.3462621"},{"key":"4_CR20","doi-asserted-by":"crossref","unstructured":"Hacker, P.: Teaching fairness to artificial intelligence: existing and novel strategies against algorithmic discrimination under EU law. Common Market Law Rev. 55, 1143\u20131186 (2018). https:\/\/ssrn.com\/abstract=3164973","DOI":"10.54648\/COLA2018095"},{"key":"4_CR21","unstructured":"Jiang, Z., Han, X., Fan, C., Yang, F., Mostafavi, A., Hu, X.: Generalized demographic parity for group fairness (2022)"},{"key":"4_CR22","doi-asserted-by":"publisher","unstructured":"John-Mathews, J., Cardon, D., Balagu\u00e9, C.: From reality to world. A critical perspective on AI fairness. J. Bus. Ethics 178(4), 945\u2013959 (2022). https:\/\/doi.org\/10.1007\/s10551-022-05055-8","DOI":"10.1007\/s10551-022-05055-8"},{"key":"4_CR23","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1257\/pandp.20181018","volume":"108","author":"J Kleinberg","year":"2018","unstructured":"Kleinberg, J., Ludwig, J., Mullainathan, S., Rambachan, A.: Algorithmic fairness. AEA Papers Proc. 108, 22\u201327 (2018)","journal-title":"AEA Papers Proc."},{"key":"4_CR24","unstructured":"Lapowsky, I.: Google autocomplete still makes vile suggestions. Wired (2018). https:\/\/www.wired.com\/story\/google-autocomplete-still-makes-vile-suggestions\/"},{"key":"4_CR25","unstructured":"Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K., Galstyan, A.: A survey on bias and fairness in machine learning. CoRR abs\/1908.09635 (2019). http:\/\/arxiv.org\/abs\/1908.09635"},{"key":"4_CR26","unstructured":"Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K., Galstyan, A.: A survey on bias and fairness in machine learning. CoRR abs\/1908.09635 (2019). http:\/\/arxiv.org\/abs\/1908.09635"},{"key":"4_CR27","unstructured":"Parliament, E.: Resolution of 20 October 2020 on the framework of ethical aspects of artificial intelligence, robotics and related technologies (2020). https:\/\/www.europarl.europa.eu\/doceo\/document\/TA-9-2020-0276_IT.html#title1. Accessed 12 June 2024"},{"key":"4_CR28","doi-asserted-by":"publisher","unstructured":"R\u00e4z, T.: Group fairness: Independence revisited. Association for Computing Machinery, New York, NY, USA (2021). https:\/\/doi.org\/10.1145\/3442188.3445876","DOI":"10.1145\/3442188.3445876"},{"key":"4_CR29","doi-asserted-by":"publisher","unstructured":"Rodrigues, R.: Legal and human rights issues of AI: Gaps, challenges and vulnerabilities. J. Responsib. Technol. 4, 100005 (2020). https:\/\/doi.org\/10.1016\/j.jrt.2020.100005","DOI":"10.1016\/j.jrt.2020.100005"},{"key":"4_CR30","doi-asserted-by":"publisher","first-page":"1130559","DOI":"10.3389\/frai.2023.1130559","volume":"6","author":"A Rotolo","year":"2023","unstructured":"Rotolo, A., Sartor, G.: Argumentation and explanation in the law. Front. Artif. Intell. 6, 1130559 (2023). https:\/\/doi.org\/10.3389\/frai.2023.1130559","journal-title":"Front. Artif. Intell."},{"key":"4_CR31","doi-asserted-by":"publisher","unstructured":"Rychener, Y., Ta\u015fkesen, B., Kuhn, D.: Metrizing fairness (2022). https:\/\/doi.org\/10.48550\/arXiv.2205.15049","DOI":"10.48550\/arXiv.2205.15049"},{"key":"4_CR32","unstructured":"Samadi, S., Tantipongpipat, U.T., Morgenstern, J., Singh, M., Vempala, S.S.: The price of fair PCA: one extra dimension. CoRR abs\/1811.00103 (2018). http:\/\/arxiv.org\/abs\/1811.00103"},{"key":"4_CR33","doi-asserted-by":"publisher","unstructured":"Schwartz, R., Vassilev, A., Greene, K., Perine, L., Burt, A., Hall, P.: Towards a standard for identifying and managing bias in artificial intelligence. Special publication (NIST SP), National Institute of Standards and Technology, Gaithersburg, MD (2022). https:\/\/doi.org\/10.6028\/NIST.SP.1270, https:\/\/tsapps.nist.gov\/publication\/get_pdf.cfm?pub_id=934464. Accessed 9 Aug 2024","DOI":"10.6028\/NIST.SP.1270"},{"key":"4_CR34","doi-asserted-by":"publisher","unstructured":"Sovrano, F., Sapienza, S., Palmirani, M., Vitali, F.: Metrics, explainability and the European AI act proposal. J 5, 126\u2013138 (2022). https:\/\/doi.org\/10.3390\/j5010010","DOI":"10.3390\/j5010010"},{"key":"4_CR35","unstructured":"Suresh, H., Guttag, J.V.: A framework for understanding unintended consequences of machine learning. CoRR abs\/1901.10002 (2019). http:\/\/arxiv.org\/abs\/1901.10002"},{"key":"4_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s00146-021-01154-8","volume":"37","author":"A Tsamados","year":"2021","unstructured":"Tsamados, A., et al.: The ethics of algorithms: key problems and solutions. AI & Soc. 37, 1\u201316 (2021). https:\/\/doi.org\/10.1007\/s00146-021-01154-8","journal-title":"AI & Soc."},{"key":"4_CR37","doi-asserted-by":"publisher","unstructured":"Tsamados, A., Floridi, L., Taddeo, M.: Human control of AI systems: from supervision to teaming. AI and Ethics ( 2024). https:\/\/doi.org\/10.1007\/s43681-024-00489-4","DOI":"10.1007\/s43681-024-00489-4"},{"key":"4_CR38","unstructured":"Union, E.: Article 21 of the EU charter of fundamental rights of the European union (CFREU) (2000). https:\/\/eur-lex.europa.eu\/legal-content\/EN\/TXT\/?uri=CELEX%3A120"},{"key":"4_CR39","unstructured":"Union, E.: Regulation (EU) 2021\/0106 on a European approach for artificial intelligence (2024).https:\/\/eur-lex.europa.eu\/legal-content\/EN\/TXT\/?uri=CELEX:52021PC0206. Accessed 12 June 2024"},{"key":"4_CR40","doi-asserted-by":"publisher","unstructured":"Verma, S., Rubin, J.: Fairness definitions explained. In: Proceedings of the International Workshop on Software Fairness, pp. 1\u20137. FairWare 2018, Association for Computing Machinery, New York, NY, USA (2018). https:\/\/doi.org\/10.1145\/3194770.3194776","DOI":"10.1145\/3194770.3194776"},{"key":"4_CR41","doi-asserted-by":"publisher","first-page":"149","DOI":"10.2139\/ssrn.4099100","volume":"97","author":"S Wachter","year":"2022","unstructured":"Wachter, S.: The theory of artificial immutability: protecting algorithmic groups under anti-discrimination law. Tulane Law Rev. 97, 149 (2022). https:\/\/doi.org\/10.2139\/ssrn.4099100","journal-title":"Tulane Law Rev."},{"key":"4_CR42","doi-asserted-by":"publisher","DOI":"10.1016\/j.clsr.2021.105567","volume":"41","author":"S Wachter","year":"2021","unstructured":"Wachter, S., Mittelstadt, B., Russell, C.: Why fairness cannot be automated: Bridging the gap between EU non-discrimination law and AI. Comput. Law Secur. Rev. 41, 105567 (2021). https:\/\/doi.org\/10.1016\/j.clsr.2021.105567","journal-title":"Comput. Law Secur. Rev."},{"key":"4_CR43","unstructured":"Wang, H., Grgic-Hlaca, N., Lahoti, P., Gummadi, K.P., Weller, A.: An empirical study on learning fairness metrics for compas data with human supervision (2019). https:\/\/arxiv.org\/abs\/1910.10255"},{"key":"4_CR44","unstructured":"Zhao, Y., Zhang, X., Tang, X., Qin, C., Zhu, H.: Embedding fairness into the AI-based talent recruitment systems: the perspective of environment cycle and knowledge cycle. In: PACIS 2021 Proceedings, No.\u00a015 (2021). https:\/\/aisel.aisnet.org\/pacis2021\/15"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2024 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-92648-8_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,30]],"date-time":"2025-05-30T16:28:51Z","timestamp":1748622531000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-92648-8_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031926471","9783031926488"],"references-count":44,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-92648-8_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"12 May 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Milan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","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":"29 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2024.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}