{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,18]],"date-time":"2024-10-18T04:28:30Z","timestamp":1729225710091,"version":"3.27.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643685489","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,10,16]],"date-time":"2024-10-16T00:00:00Z","timestamp":1729036800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,10,16]]},"abstract":"<jats:p>The issue of fairness in AI arises from discriminatory practices in applications like job recommendations and risk assessments, emphasising the need for algorithms that do not discriminate based on group characteristics. This concern is also pertinent to auctions, commonly used for resource allocation, which necessitate fairness considerations. Our study examines auctions with groups distinguished by specific attributes, seeking to (1) define a fairness notion that ensures equitable treatment for all, (2) identify mechanisms that adhere to this fairness while preserving incentive compatibility, and (3) explore the balance between fairness and seller\u2019s revenue. We introduce two fairness notions\u2014group fairness and individual fairness\u2014and propose two corresponding auction mechanisms: the Group Probability Mechanism, which meets group fairness and incentive criteria, and the Group Score Mechanism, which also encompasses individual fairness. Through experiments, we validate these mechanisms\u2019 effectiveness in promoting fairness and examine their implications for seller revenue.<\/jats:p>","DOI":"10.3233\/faia240872","type":"book-chapter","created":{"date-parts":[[2024,10,17]],"date-time":"2024-10-17T13:35:34Z","timestamp":1729172134000},"source":"Crossref","is-referenced-by-count":0,"title":["Balancing Efficiency with Equality: Auction Design with Group Fairness Concerns"],"prefix":"10.3233","author":[{"given":"Fengjuan","family":"Jia","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, University of Electronic Science and Technology of China, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mengxiao","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, University of Electronic Science and Technology of China, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiamou","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Science, The University of Auckland, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bakh","family":"Khoussainov","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, University of Electronic Science and Technology of China, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2024"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA240872","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,17]],"date-time":"2024-10-17T13:35:34Z","timestamp":1729172134000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA240872"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,16]]},"ISBN":["9781643685489"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia240872","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,16]]}}}