{"id":"https://openalex.org/W4399363450","doi":"https://doi.org/10.1145/3630106.3658977","title":"The Impact of Differential Feature Under-reporting on Algorithmic Fairness","display_name":"The Impact of Differential Feature Under-reporting on Algorithmic Fairness","publication_year":2024,"publication_date":"2024-06-03","ids":{"openalex":"https://openalex.org/W4399363450","doi":"https://doi.org/10.1145/3630106.3658977"},"language":"en","primary_location":{"id":"doi:10.1145/3630106.3658977","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3630106.3658977","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3630106.3658977","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2024 ACM Conference on Fairness, Accountability, and Transparency","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/10.1145/3630106.3658977","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066940590","display_name":"Nil-Jana Akpinar","orcid":"https://orcid.org/0000-0002-8542-8270"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]},{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Nil-Jana Akpinar","raw_affiliation_strings":["Carnegie Mellon University, USA and Amazon Web Services, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, USA and Amazon Web Services, USA","institution_ids":["https://openalex.org/I1311688040","https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029448258","display_name":"Zachary C. Lipton","orcid":"https://orcid.org/0000-0002-3824-4241"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zachary Lipton","raw_affiliation_strings":["Carnegie Mellon Univeristy, United States of America"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon Univeristy, United States of America","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057438082","display_name":"Alexandra Chouldechova","orcid":"https://orcid.org/0000-0002-2337-9610"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexandra Chouldechova","raw_affiliation_strings":["Carnegie Mellon University, United States of America"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, United States of America","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5066940590"],"corresponding_institution_ids":["https://openalex.org/I1311688040","https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":0.3626,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.63429157,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1355","last_page":"1382"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10804","display_name":"Health Systems, Economic Evaluations, Quality of Life","score":0.988099992275238,"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/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9775000214576721,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6572041511535645},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.634716272354126},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.606085479259491},{"id":"https://openalex.org/keywords/medicaid","display_name":"Medicaid","score":0.6017805337905884},{"id":"https://openalex.org/keywords/differential","display_name":"Differential (mechanical device)","score":0.5967147350311279},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.5692571401596069},{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.5230339765548706},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4825977087020874},{"id":"https://openalex.org/keywords/public-sector","display_name":"Public sector","score":0.4510110318660736},{"id":"https://openalex.org/keywords/government","display_name":"Government (linguistics)","score":0.45069438219070435},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.40870213508605957},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.30540454387664795},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.11604803800582886},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09832876920700073}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6572041511535645},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.634716272354126},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.606085479259491},{"id":"https://openalex.org/C2776534028","wikidata":"https://www.wikidata.org/wiki/Q1141363","display_name":"Medicaid","level":3,"score":0.6017805337905884},{"id":"https://openalex.org/C93226319","wikidata":"https://www.wikidata.org/wiki/Q193137","display_name":"Differential (mechanical device)","level":2,"score":0.5967147350311279},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5692571401596069},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.5230339765548706},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4825977087020874},{"id":"https://openalex.org/C147859227","wikidata":"https://www.wikidata.org/wiki/Q294217","display_name":"Public sector","level":2,"score":0.4510110318660736},{"id":"https://openalex.org/C2778137410","wikidata":"https://www.wikidata.org/wiki/Q2732820","display_name":"Government (linguistics)","level":2,"score":0.45069438219070435},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.40870213508605957},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30540454387664795},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.11604803800582886},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09832876920700073},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3630106.3658977","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3630106.3658977","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3630106.3658977","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2024 ACM Conference on Fairness, Accountability, and Transparency","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3630106.3658977","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3630106.3658977","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3630106.3658977","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2024 ACM Conference on Fairness, Accountability, and Transparency","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4399363450.pdf","grobid_xml":"https://content.openalex.org/works/W4399363450.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W193946486","https://openalex.org/W321726205","https://openalex.org/W1556513643","https://openalex.org/W1992208280","https://openalex.org/W1992465642","https://openalex.org/W2067516326","https://openalex.org/W2067671041","https://openalex.org/W2100358124","https://openalex.org/W2118591763","https://openalex.org/W2123958887","https://openalex.org/W2131275242","https://openalex.org/W2135952904","https://openalex.org/W2320240088","https://openalex.org/W2338534893","https://openalex.org/W2591772459","https://openalex.org/W2599025709","https://openalex.org/W2605006890","https://openalex.org/W2765328135","https://openalex.org/W2789970635","https://openalex.org/W2885351631","https://openalex.org/W2888109941","https://openalex.org/W2902802452","https://openalex.org/W2913700606","https://openalex.org/W3044642125","https://openalex.org/W3106035388","https://openalex.org/W3121539865","https://openalex.org/W3136824354","https://openalex.org/W3169530247","https://openalex.org/W3172101419","https://openalex.org/W3186947646","https://openalex.org/W3187543315","https://openalex.org/W3188403602","https://openalex.org/W3195282848","https://openalex.org/W4224235178","https://openalex.org/W4229737049","https://openalex.org/W4250366701","https://openalex.org/W4251386577","https://openalex.org/W4283168161","https://openalex.org/W4291497561","https://openalex.org/W4312954250","https://openalex.org/W4313545745","https://openalex.org/W6633096910","https://openalex.org/W6700406951","https://openalex.org/W6791938659"],"related_works":["https://openalex.org/W2181530120","https://openalex.org/W4211215373","https://openalex.org/W2024529227","https://openalex.org/W2055961818","https://openalex.org/W1574575415","https://openalex.org/W3144172081","https://openalex.org/W3179858851","https://openalex.org/W3028371478","https://openalex.org/W2081476516","https://openalex.org/W2581984549"],"abstract_inverted_index":{"Predictive":[0],"risk":[1],"models":[2],"in":[3,72,155,173,189],"the":[4,27,53,92,111],"public":[5,24,58],"sector":[6,59],"are":[7,102],"commonly":[8],"developed":[9],"using":[10],"administrative":[11],"data":[12,79,114,148,176],"that":[13,19,101],"is":[14,37,108],"more":[15,20],"complete":[16],"for":[17,30,43,52],"subpopulations":[18],"greatly":[21],"rely":[22],"on":[23,33,140],"services.":[25],"In":[26,122],"United":[28],"States,":[29],"instance,":[31],"information":[32],"health":[34],"care":[35],"utilization":[36],"routinely":[38],"available":[39],"to":[40,135,152,193],"government":[41],"agencies":[42],"individuals":[44],"supported":[45],"by":[46],"Medicaid":[47],"and":[48,99,158,166],"Medicare,":[49],"but":[50],"not":[51],"privately":[54],"insured.":[55],"Critiques":[56],"of":[57,70,78,95,113,131,138,163],"algorithms":[60],"have":[61],"identified":[62],"such":[63],"\u201cdifferential":[64],"feature":[65,97,120,133,194],"under-reporting\u201d":[66],"as":[67,105],"a":[68,84,160],"driver":[69],"disparities":[71,191],"algorithmic":[73,141],"decision-making.":[74],"Yet":[75],"this":[76,123,156],"form":[77],"bias":[80,154],"remains":[81],"understudied":[82],"from":[83],"technical":[85],"viewpoint.":[86],"While":[87],"prior":[88],"work":[89],"has":[90],"examined":[91],"fairness":[93],"impacts":[94],"additive":[96],"noise":[98],"features":[100],"clearly":[103],"marked":[104],"missing,":[106],"little":[107],"known":[109],"about":[110],"setting":[112],"missingness":[115],"absent":[116],"indicators":[117],"(i.e.":[118],"differential":[119,132],"under-reporting).":[121],"work,":[124],"we":[125],"study":[126],"an":[127],"analytically":[128],"tractable":[129],"model":[130],"under-reporting":[134,178],"characterizethe":[136],"impact":[137],"under-report":[139],"fairness.":[142],"We":[143],"demonstrate":[144],"how":[145],"standard":[146],"missing":[147],"methods":[149,185],"typically":[150,179],"fail":[151],"mitigate":[153],"setting,":[157],"propose":[159],"new":[161],"set":[162],"augmented":[164],"loss":[165],"imputation":[167],"methods.":[168],"Our":[169],"results":[170],"show":[171,186],"that,":[172],"real":[174],"world":[175],"settings,":[177],"exacerbates":[180],"disparities.":[181],"The":[182],"proposed":[183],"solution":[184],"some":[187],"success":[188],"mitigating":[190],"attributable":[192],"under-reporting.":[195]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}