{"id":"https://openalex.org/W2962186125","doi":"https://doi.org/10.1145/3306618.3314266","title":"Loss-Aversively Fair Classification","display_name":"Loss-Aversively Fair Classification","publication_year":2019,"publication_date":"2019-01-27","ids":{"openalex":"https://openalex.org/W2962186125","doi":"https://doi.org/10.1145/3306618.3314266","mag":"2962186125"},"language":"en","primary_location":{"id":"doi:10.1145/3306618.3314266","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3306618.3314266","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3306618.3314266","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3306618.3314266","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113944880","display_name":"Junaid Ali","orcid":null},"institutions":[{"id":"https://openalex.org/I4210121786","display_name":"Max Planck Institute for Software Systems","ror":"https://ror.org/02pe2kf23","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210121786"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Junaid Ali","raw_affiliation_strings":["Max Planck Institute for Software Systems, Saarbr\u00fccken, Germany"],"affiliations":[{"raw_affiliation_string":"Max Planck Institute for Software Systems, Saarbr\u00fccken, Germany","institution_ids":["https://openalex.org/I4210121786"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102901191","display_name":"Muhammad Bilal Zafar","orcid":"https://orcid.org/0000-0001-8347-7813"},"institutions":[{"id":"https://openalex.org/I4210121786","display_name":"Max Planck Institute for Software Systems","ror":"https://ror.org/02pe2kf23","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210121786"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Muhammad Bilal Zafar","raw_affiliation_strings":["Max Planck Institute for Software Systems, Saarbr\u00fccken, Germany"],"affiliations":[{"raw_affiliation_string":"Max Planck Institute for Software Systems, Saarbr\u00fccken, Germany","institution_ids":["https://openalex.org/I4210121786"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027711113","display_name":"Adish Singla","orcid":"https://orcid.org/0000-0001-9922-0668"},"institutions":[{"id":"https://openalex.org/I4210121786","display_name":"Max Planck Institute for Software Systems","ror":"https://ror.org/02pe2kf23","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210121786"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Adish Singla","raw_affiliation_strings":["Max Planck Institute for Software Systems, Saarbr\u00fccken, Germany"],"affiliations":[{"raw_affiliation_string":"Max Planck Institute for Software Systems, Saarbr\u00fccken, Germany","institution_ids":["https://openalex.org/I4210121786"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067688305","display_name":"Krishna P. Gummadi","orcid":"https://orcid.org/0000-0003-1256-8800"},"institutions":[{"id":"https://openalex.org/I4210121786","display_name":"Max Planck Institute for Software Systems","ror":"https://ror.org/02pe2kf23","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210121786"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Krishna P. Gummadi","raw_affiliation_strings":["Max Planck Institute for Software Systems, Saarbr\u00fccken, Germany"],"affiliations":[{"raw_affiliation_string":"Max Planck Institute for Software Systems, Saarbr\u00fccken, Germany","institution_ids":["https://openalex.org/I4210121786"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5113944880"],"corresponding_institution_ids":["https://openalex.org/I4210121786"],"apc_list":null,"apc_paid":null,"fwci":2.4648,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.90166734,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"211","last_page":"218"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10646","display_name":"Experimental Behavioral Economics Studies","score":0.9860000014305115,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10646","display_name":"Experimental Behavioral Economics Studies","score":0.9860000014305115,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10315","display_name":"Decision-Making and Behavioral Economics","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/1800","display_name":"General Decision Sciences"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.9695000052452087,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/status-quo","display_name":"Status quo","score":0.874836802482605},{"id":"https://openalex.org/keywords/proxy","display_name":"Proxy (statistics)","score":0.7494233846664429},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6561287045478821},{"id":"https://openalex.org/keywords/affect","display_name":"Affect (linguistics)","score":0.48430004715919495},{"id":"https://openalex.org/keywords/prioritization","display_name":"Prioritization","score":0.48216694593429565},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4808119535446167},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4780057966709137},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.44548100233078003},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4375723600387573},{"id":"https://openalex.org/keywords/loss-aversion","display_name":"Loss aversion","score":0.41296496987342834},{"id":"https://openalex.org/keywords/behavioral-economics","display_name":"Behavioral economics","score":0.4100651443004608},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.27638566493988037},{"id":"https://openalex.org/keywords/management-science","display_name":"Management science","score":0.19535741209983826},{"id":"https://openalex.org/keywords/microeconomics","display_name":"Microeconomics","score":0.15202021598815918},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.13429105281829834}],"concepts":[{"id":"https://openalex.org/C2776748549","wikidata":"https://www.wikidata.org/wiki/Q201610","display_name":"Status quo","level":2,"score":0.874836802482605},{"id":"https://openalex.org/C2780148112","wikidata":"https://www.wikidata.org/wiki/Q1432581","display_name":"Proxy (statistics)","level":2,"score":0.7494233846664429},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6561287045478821},{"id":"https://openalex.org/C2776035688","wikidata":"https://www.wikidata.org/wiki/Q1606558","display_name":"Affect (linguistics)","level":2,"score":0.48430004715919495},{"id":"https://openalex.org/C2777615720","wikidata":"https://www.wikidata.org/wiki/Q11888847","display_name":"Prioritization","level":2,"score":0.48216694593429565},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4808119535446167},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4780057966709137},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.44548100233078003},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4375723600387573},{"id":"https://openalex.org/C2778174566","wikidata":"https://www.wikidata.org/wiki/Q2874240","display_name":"Loss aversion","level":2,"score":0.41296496987342834},{"id":"https://openalex.org/C109574028","wikidata":"https://www.wikidata.org/wiki/Q647525","display_name":"Behavioral economics","level":2,"score":0.4100651443004608},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.27638566493988037},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.19535741209983826},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.15202021598815918},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.13429105281829834},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.0},{"id":"https://openalex.org/C34447519","wikidata":"https://www.wikidata.org/wiki/Q179522","display_name":"Market economy","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3306618.3314266","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3306618.3314266","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3306618.3314266","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.mpg.de:item_3217034","is_oa":false,"landing_page_url":"http://hdl.handle.net/21.11116/0000-0005-F651-A","pdf_url":null,"source":{"id":"https://openalex.org/S4306400654","display_name":"MPG.PuRe (Max Planck Society)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149899117","host_organization_name":"Max Planck Society","host_organization_lineage":["https://openalex.org/I149899117"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"doi:10.1145/3306618.3314266","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3306618.3314266","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3306618.3314266","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5238669936","display_name":"Foundations for Fair Social Computing","funder_award_id":"789373","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8051717526","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8318064016","display_name":null,"funder_award_id":"Horizon","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320332999","display_name":"Horizon 2020 Framework Programme","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2962186125.pdf","grobid_xml":"https://content.openalex.org/works/W2962186125.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1506859583","https://openalex.org/W1599449303","https://openalex.org/W1996886879","https://openalex.org/W2014352947","https://openalex.org/W2026019770","https://openalex.org/W2039416646","https://openalex.org/W2100960835","https://openalex.org/W2133469585","https://openalex.org/W2162670686","https://openalex.org/W2166454173","https://openalex.org/W2290452516","https://openalex.org/W2540757487","https://openalex.org/W2584805976","https://openalex.org/W2732098159","https://openalex.org/W2732560823","https://openalex.org/W2787991113","https://openalex.org/W2949979136","https://openalex.org/W2950538796","https://openalex.org/W2963992001","https://openalex.org/W3023309920","https://openalex.org/W3102518922","https://openalex.org/W3104475013","https://openalex.org/W3121654114","https://openalex.org/W3123374861","https://openalex.org/W4289258088","https://openalex.org/W4297825594","https://openalex.org/W4300482433"],"related_works":["https://openalex.org/W4386106790","https://openalex.org/W2884356503","https://openalex.org/W3203759014","https://openalex.org/W3020359174","https://openalex.org/W3012140912","https://openalex.org/W3128374809","https://openalex.org/W2975121825","https://openalex.org/W4399768124","https://openalex.org/W2940703624","https://openalex.org/W2054376643"],"abstract_inverted_index":{"The":[0],"use":[1],"of":[2,17,48,65,79,101,145,148],"algorithmic":[3],"(learning-based)":[4],"decision":[5,23,52,82],"making":[6,24,53,83],"in":[7,89,142],"scenarios":[8],"that":[9,104,134,176],"affect":[10],"human":[11],"lives":[12],"has":[13],"motivated":[14],"a":[15,49,99,146],"number":[16],"recent":[18],"studies":[19,56],"to":[20,107,116,122,125,139],"investigate":[21],"such":[22,29],"systems":[25],"for":[26,165,183],"potential":[27],"unfairness,":[28],"as":[30,108],"discrimination":[31],"against":[32],"subjects":[33,123],"based":[34],"on":[35,62],"their":[36,184],"sensitive":[37],"features":[38],"like":[39],"gender":[40],"or":[41],"race.":[42],"However,":[43],"when":[44],"judging":[45],"the":[46,70,74,80,114,126,143,177],"fairness":[47],"newly":[50],"designed":[51],"system,":[54],"these":[55],"have":[57],"overlooked":[58],"an":[59],"important":[60],"influence":[61],"people's":[63],"perceptions":[64],"fairness,":[66],"which":[67],"is":[68],"how":[69,155],"new":[71],"algorithm":[72],"changes":[73],"status":[75,127],"quo,":[76],"i.e.,":[77],"decisions":[78],"existing":[81,163],"system.":[84],"Motivated":[85],"by":[86],"extensive":[87],"literature":[88],"behavioral":[90,93],"economics":[91],"and":[92,150,172],"psychology":[94],"(prospect":[95],"theory),":[96],"we":[97,105],"propose":[98,130],"notion":[100,138],"fair":[102],"updates":[103,112,115],"refer":[106],"loss-averse":[109],"updates.":[110],"Loss-averse":[111],"constrain":[113],"yield":[117],"improved":[118],"(more":[119],"beneficial)":[120],"outcomes":[121],"compared":[124],"quo.":[128],"We":[129,153],"tractable":[131],"proxy":[132,157,179],"measures":[133,158,164,180],"would":[135],"allow":[136],"this":[137],"be":[140,160],"incorporated":[141],"training":[144,166],"variety":[147],"linear":[149],"non-linear":[151],"classifiers.":[152],"show":[154],"our":[156],"can":[159],"combined":[161],"with":[162],"nondiscriminatory":[167],"classifiers.Our":[168],"evaluation":[169],"using":[170],"synthetic":[171],"real-world":[173],"datasets":[174],"demonstrates":[175],"proposed":[178],"are":[181],"effective":[182],"desired":[185],"tasks.":[186]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}
