{"id":"https://openalex.org/W4283166422","doi":"https://doi.org/10.1145/3531146.3533101","title":"Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation","display_name":"Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation","publication_year":2022,"publication_date":"2022-06-20","ids":{"openalex":"https://openalex.org/W4283166422","doi":"https://doi.org/10.1145/3531146.3533101"},"language":"en","primary_location":{"id":"doi:10.1145/3531146.3533101","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3531146.3533101","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3531146.3533101","source":{"id":"https://openalex.org/S4363608463","display_name":"2022 ACM Conference on Fairness, Accountability, and Transparency","issn_l":null,"issn":null,"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":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 ACM Conference on Fairness Accountability and Transparency","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3531146.3533101","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002575847","display_name":"Angelina Wang","orcid":"https://orcid.org/0000-0001-9140-3523"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Angelina Wang","raw_affiliation_strings":["Princeton University, USA"],"affiliations":[{"raw_affiliation_string":"Princeton University, USA","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073539430","display_name":"V. Ramaswamy","orcid":"https://orcid.org/0000-0002-0552-5338"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vikram V Ramaswamy","raw_affiliation_strings":["Princeton University, USA"],"affiliations":[{"raw_affiliation_string":"Princeton University, USA","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022811687","display_name":"Olga Russakovsky","orcid":"https://orcid.org/0000-0001-5272-3241"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Olga Russakovsky","raw_affiliation_strings":["Princeton University, USA"],"affiliations":[{"raw_affiliation_string":"Princeton University, USA","institution_ids":["https://openalex.org/I20089843"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5002575847"],"corresponding_institution_ids":["https://openalex.org/I20089843"],"apc_list":null,"apc_paid":null,"fwci":7.4607,"has_fulltext":true,"cited_by_count":82,"citation_normalized_percentile":{"value":0.97122302,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"336","last_page":"349"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.9955999851226807,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.9955999851226807,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.9383000135421753,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7624698281288147},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7379406690597534},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6674572229385376},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.647147536277771},{"id":"https://openalex.org/keywords/intersectionality","display_name":"Intersectionality","score":0.6456225514411926},{"id":"https://openalex.org/keywords/normative","display_name":"Normative","score":0.5780532360076904},{"id":"https://openalex.org/keywords/constructive","display_name":"Constructive","score":0.490339994430542},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.45048782229423523},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4326162338256836},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.41224777698516846},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.40438318252563477},{"id":"https://openalex.org/keywords/sociology","display_name":"Sociology","score":0.11015185713768005},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09193918108940125}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7624698281288147},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7379406690597534},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6674572229385376},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.647147536277771},{"id":"https://openalex.org/C2780001913","wikidata":"https://www.wikidata.org/wiki/Q1516555","display_name":"Intersectionality","level":2,"score":0.6456225514411926},{"id":"https://openalex.org/C44725695","wikidata":"https://www.wikidata.org/wiki/Q288156","display_name":"Normative","level":2,"score":0.5780532360076904},{"id":"https://openalex.org/C2778701210","wikidata":"https://www.wikidata.org/wiki/Q28130034","display_name":"Constructive","level":3,"score":0.490339994430542},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.45048782229423523},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4326162338256836},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.41224777698516846},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.40438318252563477},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.11015185713768005},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09193918108940125},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C107993555","wikidata":"https://www.wikidata.org/wiki/Q1662673","display_name":"Gender studies","level":1,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3531146.3533101","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3531146.3533101","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3531146.3533101","source":{"id":"https://openalex.org/S4363608463","display_name":"2022 ACM Conference on Fairness, Accountability, and Transparency","issn_l":null,"issn":null,"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":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 ACM Conference on Fairness Accountability and Transparency","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2205.04610","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2205.04610","pdf_url":"https://arxiv.org/pdf/2205.04610","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3531146.3533101","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3531146.3533101","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3531146.3533101","source":{"id":"https://openalex.org/S4363608463","display_name":"2022 ACM Conference on Fairness, Accountability, and Transparency","issn_l":null,"issn":null,"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":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 ACM Conference on Fairness Accountability and Transparency","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6800000071525574,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G2993750879","display_name":null,"funder_award_id":"1763642","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7292658760","display_name":null,"funder_award_id":"1763642, 2112562, 2039656","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8377316191","display_name":null,"funder_award_id":"2112562","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"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4283166422.pdf","grobid_xml":"https://content.openalex.org/works/W4283166422.grobid-xml"},"referenced_works_count":120,"referenced_works":["https://openalex.org/W49050529","https://openalex.org/W85350352","https://openalex.org/W158181695","https://openalex.org/W384142327","https://openalex.org/W398859631","https://openalex.org/W599053428","https://openalex.org/W1193411788","https://openalex.org/W1511298626","https://openalex.org/W1577069963","https://openalex.org/W1578490632","https://openalex.org/W1977578104","https://openalex.org/W1977655452","https://openalex.org/W1979769549","https://openalex.org/W1986792585","https://openalex.org/W2005061283","https://openalex.org/W2009551222","https://openalex.org/W2022385316","https://openalex.org/W2029964646","https://openalex.org/W2067516326","https://openalex.org/W2074794468","https://openalex.org/W2087621263","https://openalex.org/W2100960835","https://openalex.org/W2112482501","https://openalex.org/W2115763562","https://openalex.org/W2130485851","https://openalex.org/W2131360899","https://openalex.org/W2140403750","https://openalex.org/W2145382344","https://openalex.org/W2148143831","https://openalex.org/W2152409773","https://openalex.org/W2162068690","https://openalex.org/W2178843456","https://openalex.org/W2522273567","https://openalex.org/W2530395818","https://openalex.org/W2579162260","https://openalex.org/W2751222915","https://openalex.org/W2751465153","https://openalex.org/W2765564115","https://openalex.org/W2768894107","https://openalex.org/W2771421168","https://openalex.org/W2782641821","https://openalex.org/W2787991113","https://openalex.org/W2795282075","https://openalex.org/W2795908329","https://openalex.org/W2803648878","https://openalex.org/W2805956788","https://openalex.org/W2889989236","https://openalex.org/W2890436397","https://openalex.org/W2896659017","https://openalex.org/W2897154134","https://openalex.org/W2900885930","https://openalex.org/W2901823434","https://openalex.org/W2902633481","https://openalex.org/W2909334458","https://openalex.org/W2937400655","https://openalex.org/W2946294136","https://openalex.org/W2955620426","https://openalex.org/W2962925443","https://openalex.org/W2963104135","https://openalex.org/W2963917042","https://openalex.org/W2976948333","https://openalex.org/W2989096391","https://openalex.org/W2989168403","https://openalex.org/W2992319600","https://openalex.org/W3001248429","https://openalex.org/W3006437051","https://openalex.org/W3013451997","https://openalex.org/W3013571594","https://openalex.org/W3013778941","https://openalex.org/W3017048210","https://openalex.org/W3023702633","https://openalex.org/W3030030520","https://openalex.org/W3032340379","https://openalex.org/W3034115845","https://openalex.org/W3036033115","https://openalex.org/W3037441821","https://openalex.org/W3095351420","https://openalex.org/W3101449958","https://openalex.org/W3103677873","https://openalex.org/W3105992983","https://openalex.org/W3106000504","https://openalex.org/W3106253243","https://openalex.org/W3119098945","https://openalex.org/W3120740533","https://openalex.org/W3125277052","https://openalex.org/W3125306662","https://openalex.org/W3127314936","https://openalex.org/W3132748670","https://openalex.org/W3132771424","https://openalex.org/W3133802387","https://openalex.org/W3133874049","https://openalex.org/W3133953502","https://openalex.org/W3134225450","https://openalex.org/W3139492312","https://openalex.org/W3146079624","https://openalex.org/W3157598734","https://openalex.org/W3162683674","https://openalex.org/W3168398407","https://openalex.org/W3184924454","https://openalex.org/W3185212449","https://openalex.org/W3213978703","https://openalex.org/W4207060737","https://openalex.org/W4230906437","https://openalex.org/W4231665006","https://openalex.org/W4239181501","https://openalex.org/W4240080389","https://openalex.org/W4245446973","https://openalex.org/W4247511804","https://openalex.org/W4247606792","https://openalex.org/W4287071928","https://openalex.org/W4287393742","https://openalex.org/W4288029087","https://openalex.org/W4288083800","https://openalex.org/W4289438483","https://openalex.org/W4293875341","https://openalex.org/W4297795193","https://openalex.org/W4301730562","https://openalex.org/W4388064047","https://openalex.org/W4393292946","https://openalex.org/W4394666657"],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2059640416","https://openalex.org/W1490753184","https://openalex.org/W2284465472","https://openalex.org/W2291782699","https://openalex.org/W1993948687","https://openalex.org/W2000169967","https://openalex.org/W2112883198"],"abstract_inverted_index":{"Research":[0],"in":[1,158],"machine":[2,36,106,191],"learning":[3,37,107],"fairness":[4,80],"has":[5],"historically":[6],"considered":[7],"a":[8],"single":[9],"binary":[10],"demographic":[11,44,48,122,136],"attribute;":[12],"however,":[13],"the":[14,35,59,97,105,132,156,159,172],"reality":[15],"is":[16],"of":[17,34,63,135],"course":[18],"far":[19],"more":[20,82,169],"complicated.":[21],"In":[22],"this":[23],"work,":[24],"we":[25,87,110,139,162,176],"grapple":[26],"with":[27,116],"questions":[28],"that":[29],"arise":[30],"along":[31],"three":[32,181],"stages":[33],"pipeline":[38],"when":[39,77,119,187],"incorporating":[40,188],"intersectionality":[41,189],"as":[42,52],"multiple":[43],"attributes:":[45],"(1)":[46],"which":[47,121,167],"attributes":[49],"to":[50,57,71,125],"include":[51],"dataset":[53],"labels,":[54],"(2)":[55],"how":[56,70],"handle":[58],"progressively":[60],"smaller":[61],"size":[62],"subgroups":[64],"during":[65],"model":[66,79],"training,":[67],"and":[68,100,151],"(3)":[69],"move":[72],"beyond":[73],"existing":[74],"evaluation":[75,91,165],"metrics":[76,166],"benchmarking":[78],"for":[81,104,112,171],"subgroups.":[83],"For":[84],"each":[85],"question,":[86],"provide":[88,177],"thorough":[89],"empirical":[90,117],"on":[92,131,180],"tabular":[93],"datasets":[94],"derived":[95],"from":[96],"US":[98],"Census,":[99],"present":[101],"constructive":[102],"recommendations":[103],"community.":[108],"First,":[109],"advocate":[111],"supplementing":[113],"domain":[114],"knowledge":[115],"validation":[118],"choosing":[120],"attribute":[123],"labels":[124],"train":[126],"on,":[127],"while":[128],"always":[129],"evaluating":[130],"full":[133],"set":[134],"attributes.":[137],"Second,":[138],"warn":[140],"against":[141],"using":[142,155],"data":[143],"imbalance":[144],"techniques":[145],"without":[146],"considering":[147],"their":[148],"normative":[149],"implications":[150],"suggest":[152],"an":[153],"alternative":[154],"structure":[157],"data.":[160],"Third,":[161],"introduce":[163],"new":[164],"are":[168],"appropriate":[170],"intersectional":[173],"setting.":[174],"Overall,":[175],"substantive":[178],"suggestions":[179],"necessary":[182],"(albeit":[183],"not":[184],"sufficient!)":[185],"considerations":[186],"into":[190],"learning.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":24},{"year":2024,"cited_by_count":26},{"year":2023,"cited_by_count":23},{"year":2022,"cited_by_count":3}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
