{"id":"https://openalex.org/W2897042519","doi":"https://doi.org/10.1145/3287560.3287596","title":"Model Cards for Model Reporting","display_name":"Model Cards for Model Reporting","publication_year":2019,"publication_date":"2019-01-09","ids":{"openalex":"https://openalex.org/W2897042519","doi":"https://doi.org/10.1145/3287560.3287596","mag":"2897042519"},"language":"en","primary_location":{"id":"doi:10.1145/3287560.3287596","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3287560.3287596","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Conference on Fairness, Accountability, and Transparency","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1810.03993","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Margaret Mitchell","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Margaret Mitchell","raw_affiliation_strings":[""],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Simone Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Simone Wu","raw_affiliation_strings":[""],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Andrew Zaldivar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Andrew Zaldivar","raw_affiliation_strings":[""],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Parker Barnes","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Parker Barnes","raw_affiliation_strings":[""],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lucy Vasserman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lucy Vasserman","raw_affiliation_strings":[""],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ben Hutchinson","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ben Hutchinson","raw_affiliation_strings":[""],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Elena Spitzer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Elena Spitzer","raw_affiliation_strings":[""],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Inioluwa Deborah Raji","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Inioluwa Deborah Raji","raw_affiliation_strings":[""],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Timnit Gebru","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Timnit Gebru","raw_affiliation_strings":[""],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":119.2405,"has_fulltext":false,"cited_by_count":1567,"citation_normalized_percentile":{"value":0.9997311,"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":"220","last_page":"229"},"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":0.9940999746322632,"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":0.9940999746322632,"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/T13643","display_name":"Artificial Intelligence in Law","score":0.9794999957084656,"subfield":{"id":"https://openalex.org/subfields/3320","display_name":"Political Science and International Relations"},"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9520999789237976,"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/context","display_name":"Context (archaeology)","score":0.5332000255584717},{"id":"https://openalex.org/keywords/transparency","display_name":"Transparency (behavior)","score":0.51419997215271},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.4221000075340271},{"id":"https://openalex.org/keywords/documentation","display_name":"Documentation","score":0.3474000096321106},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.3221000134944916},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.2678999900817871}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7401000261306763},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7366999983787537},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7289999723434448},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5332000255584717},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.51419997215271},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.4221000075340271},{"id":"https://openalex.org/C56666940","wikidata":"https://www.wikidata.org/wiki/Q788790","display_name":"Documentation","level":2,"score":0.3474000096321106},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.3221000134944916},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.26330000162124634},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.26010000705718994}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3287560.3287596","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3287560.3287596","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Conference on Fairness, Accountability, and Transparency","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1810.03993","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1810.03993","pdf_url":"https://arxiv.org/pdf/1810.03993","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":"pmh:oai:arXiv.org:1810.03993","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1810.03993","pdf_url":"https://arxiv.org/pdf/1810.03993","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1584308190","https://openalex.org/W1834627138","https://openalex.org/W1978642336","https://openalex.org/W2078271269","https://openalex.org/W2101105183","https://openalex.org/W2745294951","https://openalex.org/W2791170418","https://openalex.org/W2809878087","https://openalex.org/W2906183835","https://openalex.org/W2963615251","https://openalex.org/W6824583106"],"related_works":[],"abstract_inverted_index":{"Trained":[0],"machine":[1,30,84,165,188,231,255],"learning":[2,31,85,166,189,232,256],"models":[3,32,50,86,143,167,257],"are":[4,42,79,128,144],"increasingly":[5],"used":[6,183],"to":[7,23,71,130,146,184,204,213,258],"perform":[8],"high-impact":[9],"tasks":[10],"in":[11,37,91,141,168,208,217],"areas":[12],"such":[13,73,96],"as":[14,97,223],"law":[15],"enforcement,":[16],"medicine,":[17],"education,":[18],"and":[19,33,114,119,123,155,175,210,233,267],"employment.":[20],"In":[21,59],"order":[22],"clarify":[24],"the":[25,131,139,151,169,193,227],"intended":[26,132,145],"use":[27],"cases":[28],"of":[29,94,150,172,230],"minimize":[34],"their":[35,56],"usage":[36],"contexts":[38],"for":[39,198],"which":[40,142],"they":[41],"not":[43],"well":[44,242],"suited,":[45],"we":[46,62,67,160,195],"recommend":[47],"that":[48,66,87,127],"released":[49],"be":[51,147,182],"accompanied":[52],"by":[53],"documentation":[54],"detailing":[55],"performance":[57,152],"characteristics.":[58],"this":[60,179,249],"paper,":[61],"propose":[63,220],"a":[64,92,224],"framework":[65,180],"call":[68],"model":[69,75,221,260],"cards,":[70],"encourage":[72],"transparent":[74],"reporting.":[76],"Model":[77,135],"cards":[78,136,197,222],"short":[80],"documents":[81],"accompanying":[82],"trained":[83,187,203,212,254],"provide":[88,196],"benchmarked":[89],"evaluation":[90,153,265],"variety":[93],"conditions,":[95],"across":[98],"different":[99],"cultural,":[100],"demographic,":[101],"or":[102,121],"phenotypic":[103],"groups":[104,116],"(e.g.,":[105,117],"race,":[106,120],"geographic":[107],"location,":[108],"sex,":[109],"Fitzpatrick":[110,124],"skin":[111,125],"type":[112],"[15])":[113],"intersectional":[115],"age":[118],"sex":[122],"type)":[126],"relevant":[129,157,269],"application":[133,170],"domains.":[134],"also":[137],"disclose":[138],"context":[140],"used,":[148],"details":[149],"procedures,":[154],"other":[156,268],"information.":[158],"While":[159],"focus":[161],"primarily":[162],"on":[163],"human-centered":[164],"fields":[171],"computer":[173],"vision":[174],"natural":[176],"language":[177],"processing,":[178],"can":[181],"document":[185],"any":[186],"model.":[190],"To":[191],"solidify":[192],"concept,":[194],"two":[199],"supervised":[200],"models:":[201],"One":[202],"detect":[205,214],"smiling":[206],"faces":[207],"images,":[209],"one":[211],"toxic":[215],"comments":[216],"text.":[218],"We":[219,247],"step":[225],"towards":[226],"responsible":[228],"democratization":[229],"related":[234],"artificial":[235,243],"intelligence":[236,244],"technology,":[237],"increasing":[238],"transparency":[239],"into":[240],"how":[241],"technology":[245],"works.":[246],"hope":[248],"work":[250],"encourages":[251],"those":[252],"releasing":[253],"accompany":[259],"releases":[261],"with":[262],"similar":[263],"detailed":[264],"numbers":[266],"documentation.":[270]},"counts_by_year":[{"year":2026,"cited_by_count":203},{"year":2025,"cited_by_count":381},{"year":2024,"cited_by_count":318},{"year":2023,"cited_by_count":277},{"year":2022,"cited_by_count":171},{"year":2021,"cited_by_count":145},{"year":2020,"cited_by_count":50},{"year":2019,"cited_by_count":21},{"year":2012,"cited_by_count":1}],"updated_date":"2026-05-07T13:39:58.223016","created_date":"2018-10-26T00:00:00"}
