{"id":"https://openalex.org/W4404518243","doi":"https://doi.org/10.1609/aies.v7i1.31705","title":"Hidden or Inferred: Fair Learning-To-Rank With Unknown Demographics","display_name":"Hidden or Inferred: Fair Learning-To-Rank With Unknown Demographics","publication_year":2024,"publication_date":"2024-10-16","ids":{"openalex":"https://openalex.org/W4404518243","doi":"https://doi.org/10.1609/aies.v7i1.31705"},"language":"en","primary_location":{"id":"doi:10.1609/aies.v7i1.31705","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1609/aies.v7i1.31705","pdf_url":"https://ojs.aaai.org/index.php/AIES/article/download/31705/33872","source":{"id":"https://openalex.org/S5407048695","display_name":"Proceedings of the AAAI/ACM Conference on AI Ethics and Society","issn_l":"3065-8365","issn":["3065-8365"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://ojs.aaai.org/index.php/AIES/article/download/31705/33872","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034293010","display_name":"Oluseun Olulana","orcid":null},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Oluseun Olulana","raw_affiliation_strings":["Worcester Polytechnic Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041530401","display_name":"Kathleen Cachel","orcid":"https://orcid.org/0000-0002-1260-0914"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kathleen Cachel","raw_affiliation_strings":["Worcester Polytechnic Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021734616","display_name":"Fabr\u00edcio Murai","orcid":"https://orcid.org/0000-0003-4487-6381"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fabricio Murai","raw_affiliation_strings":["Worcester Polytechnic Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008269094","display_name":"Elke A. Rundensteiner","orcid":"https://orcid.org/0000-0001-5375-9254"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Elke Rundensteiner","raw_affiliation_strings":["Worcester Polytechnic Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute","institution_ids":["https://openalex.org/I107077323"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I107077323"],"apc_list":null,"apc_paid":null,"fwci":4.3228,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.94449159,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"7","issue":null,"first_page":"1088","last_page":"1099"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13789","display_name":"Global Education Systems and Policies","score":0.4699000120162964,"subfield":{"id":"https://openalex.org/subfields/3304","display_name":"Education"},"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/T13789","display_name":"Global Education Systems and Policies","score":0.4699000120162964,"subfield":{"id":"https://openalex.org/subfields/3304","display_name":"Education"},"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/T10208","display_name":"Labor market dynamics and wage inequality","score":0.4645000100135803,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13844","display_name":"Higher Education Learning Practices","score":0.42149999737739563,"subfield":{"id":"https://openalex.org/subfields/3304","display_name":"Education"},"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/demographics","display_name":"Demographics","score":0.8988787531852722},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5657099485397339},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.36696407198905945},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.34183716773986816},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.3285946846008301},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2633569836616516},{"id":"https://openalex.org/keywords/demography","display_name":"Demography","score":0.25879424810409546},{"id":"https://openalex.org/keywords/sociology","display_name":"Sociology","score":0.12825322151184082},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.11812174320220947}],"concepts":[{"id":"https://openalex.org/C2780084366","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demographics","level":2,"score":0.8988787531852722},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5657099485397339},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.36696407198905945},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.34183716773986816},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.3285946846008301},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2633569836616516},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.25879424810409546},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.12825322151184082},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.11812174320220947}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aies.v7i1.31705","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1609/aies.v7i1.31705","pdf_url":"https://ojs.aaai.org/index.php/AIES/article/download/31705/33872","source":{"id":"https://openalex.org/S5407048695","display_name":"Proceedings of the AAAI/ACM Conference on AI Ethics and Society","issn_l":"3065-8365","issn":["3065-8365"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aies.v7i1.31705","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1609/aies.v7i1.31705","pdf_url":"https://ojs.aaai.org/index.php/AIES/article/download/31705/33872","source":{"id":"https://openalex.org/S5407048695","display_name":"Proceedings of the AAAI/ACM Conference on AI Ethics and Society","issn_l":"3065-8365","issn":["3065-8365"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1203145028","display_name":"III: Small: Fair Decision Making by Consensus: Interactive Bias Mitigation Technology","funder_award_id":"2007932","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4639191150","display_name":"III:Small: Outlier Discovery Paradigm","funder_award_id":"1910880","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5945190869","display_name":"Collaborative Research: ELEMENTS: Tuning-free Anomaly Detection Service","funder_award_id":"2103832","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6249850884","display_name":"REU SITE: DATA SCIENCE RESEARCH FOR HEALTHY COMMUNITIES IN THE DIGITAL AGE","funder_award_id":"1852498","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320308335","display_name":"American Association of University Women","ror":"https://ror.org/05hrczs03"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4404518243.pdf","grobid_xml":"https://content.openalex.org/works/W4404518243.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W3121380072","https://openalex.org/W2058403539","https://openalex.org/W2333615638","https://openalex.org/W2602311653","https://openalex.org/W2964230772","https://openalex.org/W2768231286","https://openalex.org/W2973958681"],"abstract_inverted_index":{"As":[0,54],"learning-to-rank":[1,21],"models":[2,25,121],"are":[3,85,211,228],"increasingly":[4],"deployed":[5],"for":[6],"decision-making":[7],"in":[8,40,95],"areas":[9],"with":[10,137,177],"profound":[11],"life":[12],"implications,":[13],"the":[14,28,65,99,167,200],"FairML":[15],"community":[16],"has":[17],"been":[18],"developing":[19],"fair":[20,104,130,135,150,208],"(LTR)":[22],"models.":[23],"These":[24],"rely":[26],"on":[27],"availability":[29],"of":[30,67,102,129,161,224],"sensitive":[31,169],"demographic":[32,73,96,117,140],"features":[33,69,141],"such":[34,116],"as":[35,189],"race":[36],"or":[37,70],"sex.":[38],"However,":[39],"practice,":[41],"regulatory":[42],"obstacles":[43],"and":[44,52,138,180,221],"privacy":[45],"concerns":[46],"protect":[47],"this":[48,87],"data":[49],"from":[50,120,134],"collection":[51],"use.":[53],"a":[55,127,154],"result,":[56],"practitioners":[57],"may":[58,203],"either":[59],"need":[60],"to":[61,72,76,78,90,114,145,214],"promote":[62],"fairness":[63,100,197],"despite":[64],"absence":[66],"these":[68,83],"turn":[71],"inference":[74,97,162,183,190,215],"tools":[75,84],"attempt":[77],"infer":[79,123],"them.":[80],"Given":[81],"that":[82,188,195],"fallible,":[86],"paper":[88],"aims":[89],"further":[91],"understand":[92],"how":[93],"errors":[94,163],"impact":[98],"performance":[101],"popular":[103,181],"LTR":[105,131,136,147],"strategies.":[106],"In":[107,206],"which":[108],"cases":[109],"would":[110],"it":[111],"be":[112],"better":[113],"keep":[115],"attributes":[118],"hidden":[119,142],"versus":[122,143],"them?":[124],"We":[125,152,171],"examine":[126],"spectrum":[128],"strategies":[132,210],"ranging":[133],"without":[139],"inferred":[144,168],"fairness-unaware":[146],"followed":[148],"by":[149,164],"re-ranking.":[151],"conduct":[153],"controlled":[155],"empirical":[156],"investigation":[157],"modeling":[158],"different":[159],"levels":[160],"systematically":[165],"perturbing":[166],"attribute.":[170],"also":[172],"perform":[173],"three":[174],"case":[175],"studies":[176],"real-world":[178],"datasets":[179],"open-source":[182],"methods.":[184],"Our":[185],"findings":[186],"reveal":[187],"noise":[191],"grows,":[192],"LTR-based":[193],"methods":[194],"incorporate":[196],"considerations":[198],"into":[199],"learning":[201],"process":[202],"increase":[204],"bias.":[205],"contrast,":[207],"re-ranking":[209],"more":[212],"robust":[213],"errors.":[216],"All":[217],"source":[218],"code,":[219],"data,":[220],"experimental":[222,226],"artifacts":[223],"our":[225],"study":[227],"available":[229],"here:":[230],"https://github.com/sewen007/hoiltr.git":[231]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-19T15:00:24.278416","created_date":"2025-10-10T00:00:00"}