{"id":"https://openalex.org/W4386302153","doi":"https://doi.org/10.1145/3582269.3615599","title":"Gender bias and stereotypes in Large Language Models","display_name":"Gender bias and stereotypes in Large Language Models","publication_year":2023,"publication_date":"2023-10-13","ids":{"openalex":"https://openalex.org/W4386302153","doi":"https://doi.org/10.1145/3582269.3615599"},"language":"en","primary_location":{"id":"doi:10.1145/3582269.3615599","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3582269.3615599","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of The ACM Collective Intelligence Conference","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2308.14921","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067913601","display_name":"Hadas Kotek","orcid":"https://orcid.org/0009-0006-0360-2105"},"institutions":[{"id":"https://openalex.org/I4210153776","display_name":"Apple (United States)","ror":"https://ror.org/059hsda18","country_code":"US","type":"company","lineage":["https://openalex.org/I4210153776"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hadas Kotek","raw_affiliation_strings":["Apple and MIT, USA"],"affiliations":[{"raw_affiliation_string":"Apple and MIT, USA","institution_ids":["https://openalex.org/I4210153776"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090390811","display_name":"Rikker Dockum","orcid":"https://orcid.org/0000-0002-6640-808X"},"institutions":[{"id":"https://openalex.org/I118020396","display_name":"Swarthmore College","ror":"https://ror.org/012dg8a96","country_code":"US","type":"education","lineage":["https://openalex.org/I118020396"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rikker Dockum","raw_affiliation_strings":["Swarthmore College, USA"],"affiliations":[{"raw_affiliation_string":"Swarthmore College, USA","institution_ids":["https://openalex.org/I118020396"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066826683","display_name":"David Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I4210153776","display_name":"Apple (United States)","ror":"https://ror.org/059hsda18","country_code":"US","type":"company","lineage":["https://openalex.org/I4210153776"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Sun","raw_affiliation_strings":["Apple, USA"],"affiliations":[{"raw_affiliation_string":"Apple, USA","institution_ids":["https://openalex.org/I4210153776"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5067913601"],"corresponding_institution_ids":["https://openalex.org/I4210153776"],"apc_list":null,"apc_paid":null,"fwci":51.5139,"has_fulltext":true,"cited_by_count":298,"citation_normalized_percentile":{"value":0.99914209,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"12","last_page":"24"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9786999821662903,"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/T10028","display_name":"Topic Modeling","score":0.9786999821662903,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.9666000008583069,"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"}},{"id":"https://openalex.org/T13629","display_name":"Text Readability and Simplification","score":0.9309999942779541,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.6968581676483154},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5451854467391968},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5301904082298279},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.4844365417957306},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.45827174186706543},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.43935197591781616},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.3985607624053955},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20425835251808167},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.19500237703323364}],"concepts":[{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.6968581676483154},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5451854467391968},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5301904082298279},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.4844365417957306},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.45827174186706543},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.43935197591781616},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.3985607624053955},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20425835251808167},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.19500237703323364},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3582269.3615599","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3582269.3615599","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of The ACM Collective Intelligence Conference","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2308.14921","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2308.14921","pdf_url":"https://arxiv.org/pdf/2308.14921","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"},{"id":"pmh:oai:dspace.mit.edu:1721.1/153131","is_oa":true,"landing_page_url":"https://hdl.handle.net/1721.1/153131","pdf_url":"https://dspace.mit.edu/bitstream/1721.1/153131/1/3582269.3615599.pdf","source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Association for Computing Machinery","raw_type":"http://purl.org/eprint/type/ConferencePaper"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2308.14921","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2308.14921","pdf_url":"https://arxiv.org/pdf/2308.14921","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"},"sustainable_development_goals":[{"display_name":"Gender equality","id":"https://metadata.un.org/sdg/5","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386302153.pdf"},"referenced_works_count":103,"referenced_works":["https://openalex.org/W122836236","https://openalex.org/W634116457","https://openalex.org/W1581527173","https://openalex.org/W1599016936","https://openalex.org/W1605758875","https://openalex.org/W1819662813","https://openalex.org/W1987090026","https://openalex.org/W1995270163","https://openalex.org/W2023678302","https://openalex.org/W2025440555","https://openalex.org/W2042275498","https://openalex.org/W2050331636","https://openalex.org/W2058271572","https://openalex.org/W2069480704","https://openalex.org/W2089871587","https://openalex.org/W2102225743","https://openalex.org/W2144163256","https://openalex.org/W2145307225","https://openalex.org/W2146213370","https://openalex.org/W2165957179","https://openalex.org/W2171255076","https://openalex.org/W2234124789","https://openalex.org/W2236770054","https://openalex.org/W2299921203","https://openalex.org/W2507971793","https://openalex.org/W2580263176","https://openalex.org/W2607719644","https://openalex.org/W2769358515","https://openalex.org/W2783995097","https://openalex.org/W2802105481","https://openalex.org/W2804815760","https://openalex.org/W2889624842","https://openalex.org/W2893425640","https://openalex.org/W2920766663","https://openalex.org/W2926555354","https://openalex.org/W2950018712","https://openalex.org/W2950888501","https://openalex.org/W2950939981","https://openalex.org/W2952328691","https://openalex.org/W2959360485","https://openalex.org/W2962787423","https://openalex.org/W2962990575","https://openalex.org/W2963078909","https://openalex.org/W2963457723","https://openalex.org/W2963526187","https://openalex.org/W2969958763","https://openalex.org/W2971307358","https://openalex.org/W2972413484","https://openalex.org/W2972668795","https://openalex.org/W2972972637","https://openalex.org/W2991870143","https://openalex.org/W3025838439","https://openalex.org/W3034656957","https://openalex.org/W3034937117","https://openalex.org/W3037831233","https://openalex.org/W3123374861","https://openalex.org/W3128232076","https://openalex.org/W3133702157","https://openalex.org/W3148522987","https://openalex.org/W3172415559","https://openalex.org/W3173446448","https://openalex.org/W3173465197","https://openalex.org/W3176477796","https://openalex.org/W3184144760","https://openalex.org/W3215123583","https://openalex.org/W4220993274","https://openalex.org/W4223578676","https://openalex.org/W4233923252","https://openalex.org/W4234999116","https://openalex.org/W4239236427","https://openalex.org/W4245560825","https://openalex.org/W4246270365","https://openalex.org/W4250499230","https://openalex.org/W4255461308","https://openalex.org/W4256387735","https://openalex.org/W4285183888","https://openalex.org/W4285199616","https://openalex.org/W4301369855","https://openalex.org/W4312341782","https://openalex.org/W4318014888","https://openalex.org/W4318719246","https://openalex.org/W4319301432","https://openalex.org/W4319793302","https://openalex.org/W4319863236","https://openalex.org/W4320009650","https://openalex.org/W4320009668","https://openalex.org/W4321392130","https://openalex.org/W4321648737","https://openalex.org/W4327672398","https://openalex.org/W4327946446","https://openalex.org/W4361985454","https://openalex.org/W4362655923","https://openalex.org/W4365211776","https://openalex.org/W4375958700","https://openalex.org/W4380575774","https://openalex.org/W4380879558","https://openalex.org/W4381252028","https://openalex.org/W4382619745","https://openalex.org/W4385574250","https://openalex.org/W4386566857","https://openalex.org/W4387356888","https://openalex.org/W4392669753","https://openalex.org/W6604084370"],"related_works":["https://openalex.org/W2353179089","https://openalex.org/W2923538289","https://openalex.org/W2353125546","https://openalex.org/W2470643824","https://openalex.org/W2349635380","https://openalex.org/W4353089801","https://openalex.org/W2353819554","https://openalex.org/W2359488321","https://openalex.org/W2389866386","https://openalex.org/W2087303720"],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"have":[4],"made":[5],"substantial":[6],"progress":[7],"in":[8,16,65,92,131,137,146,157,164],"the":[9,42,66,126,140,149,162,174,190,223],"past":[10],"several":[11],"months,":[12],"shattering":[13],"state-of-the-art":[14],"benchmarks":[15],"many":[17],"domains.":[18],"This":[19,205],"paper":[20,94],"investigates":[21],"LLMs\u2019":[22],"behavior":[23],"with":[24,112,120,125,222,229,242],"respect":[25],"to":[26,40,62,105,234,256],"gender":[27,45,56],"stereotypes,":[28],"a":[29,37,53,113,207],"known":[30],"issue":[31],"for":[32,180],"prior":[33],"models.":[34],"We":[35,72],"use":[36],"simple":[38],"paradigm":[39],"test":[41,73],"presence":[43],"of":[44,69,161,201,210,226,245],"bias,":[46],"building":[47],"on":[48,216],"but":[49,168],"differing":[50],"from":[51],"WinoBias,":[52],"commonly":[54],"used":[55],"bias":[57,141],"dataset,":[58],"which":[59],"is":[60,144],"likely":[61,104,188],"be":[63,253],"included":[64],"training":[67],"data":[68],"current":[70],"LLMs.":[71],"four":[74],"recently":[75],"published":[76],"LLMs":[77,99,136,153,177,213,251],"and":[78,87,187,263],"demonstrate":[79],"that":[80,109,183,250,258],"they":[81,172,198,232,259],"express":[82],"biased":[83,203],"assumptions":[84],"about":[85],"men":[86],"women\u2019s":[88],"occupations.":[89],"Our":[90],"contributions":[91],"this":[93],"are":[95,100,184,214],"as":[96,129,219],"follows:":[97],"(a)":[98],"3-6":[101],"times":[102],"more":[103],"choose":[106],"an":[107],"occupation":[108],"stereotypically":[110],"aligns":[111],"person\u2019s":[114],"gender;":[115],"(b)":[116],"these":[117,211],"choices":[118,182],"align":[119],"people\u2019s":[121],"perceptions":[122,147],"better":[123],"than":[124],"ground":[127,150],"truth":[128],"reflected":[130,145],"official":[132],"job":[133],"statistics;":[134],"(c)":[135],"fact":[138],"amplify":[139],"beyond":[142],"what":[143],"or":[148],"truth;":[151],"(d)":[152],"ignore":[154],"crucial":[155],"ambiguities":[156],"sentence":[158],"structure":[159],"95%":[160],"time":[163],"our":[165],"study":[166],"items,":[167],"when":[169],"explicitly":[170],"prompted,":[171],"recognize":[173],"ambiguity;":[175],"(e)":[176],"provide":[178,199],"explanations":[179],"their":[181,194,202],"factually":[185],"inaccurate":[186],"obscure":[189],"true":[191],"reason":[192],"behind":[193],"predictions.":[195],"That":[196],"is,":[197],"rationalizations":[200],"behavior.":[204],"highlights":[206],"key":[208],"property":[209],"models:":[212],"trained":[215],"imbalanced":[217],"datasets;":[218],"such,":[220],"even":[221],"recent":[224],"successes":[225],"reinforcement":[227],"learning":[228],"human":[230],"feedback,":[231],"tend":[233],"reflect":[235],"those":[236],"imbalances":[237],"back":[238],"at":[239],"us.":[240],"As":[241],"other":[243],"types":[244],"societal":[246],"biases,":[247],"we":[248],"suggest":[249],"must":[252],"carefully":[254],"tested":[255],"ensure":[257],"treat":[260],"minoritized":[261],"individuals":[262],"communities":[264],"equitably.":[265]},"counts_by_year":[{"year":2026,"cited_by_count":33},{"year":2025,"cited_by_count":162},{"year":2024,"cited_by_count":97},{"year":2023,"cited_by_count":5},{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-07T14:57:38.498316","created_date":"2025-10-10T00:00:00"}
