{"id":"https://openalex.org/W3164652469","doi":"https://doi.org/10.1145/3461702.3462620","title":"Computer Vision and Conflicting Values: Describing People with Automated Alt Text","display_name":"Computer Vision and Conflicting Values: Describing People with Automated Alt Text","publication_year":2021,"publication_date":"2021-07-21","ids":{"openalex":"https://openalex.org/W3164652469","doi":"https://doi.org/10.1145/3461702.3462620","mag":"3164652469"},"language":"en","primary_location":{"id":"doi:10.1145/3461702.3462620","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3461702.3462620","pdf_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3461702.3462620&file=aiespp249aux.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3461702.3462620&file=aiespp249aux.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080065115","display_name":"Margot Hanley","orcid":null},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Margot Hanley","raw_affiliation_strings":["Cornell Tech, New York City , NY, USA"],"affiliations":[{"raw_affiliation_string":"Cornell Tech, New York City , NY, USA","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074825066","display_name":"Solon Barocas","orcid":"https://orcid.org/0000-0003-4577-466X"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Solon Barocas","raw_affiliation_strings":["Microsoft Research & Cornell University, New York City , NY, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research & Cornell University, New York City , NY, USA","institution_ids":["https://openalex.org/I1290206253","https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040228064","display_name":"Karen Levy","orcid":"https://orcid.org/0000-0003-3806-9161"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Karen Levy","raw_affiliation_strings":["Cornell University, Ithaca, NY, USA"],"affiliations":[{"raw_affiliation_string":"Cornell University, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060708945","display_name":"Shiri Azenkot","orcid":"https://orcid.org/0000-0002-6701-4066"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shiri Azenkot","raw_affiliation_strings":["Cornell Tech, New York City , NY, USA"],"affiliations":[{"raw_affiliation_string":"Cornell Tech, New York City , NY, USA","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011149012","display_name":"Helen Nissenbaum","orcid":"https://orcid.org/0000-0002-6485-6997"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Helen Nissenbaum","raw_affiliation_strings":["Cornell Tech, New York City , NY, USA"],"affiliations":[{"raw_affiliation_string":"Cornell Tech, New York City , NY, USA","institution_ids":["https://openalex.org/I205783295"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5080065115"],"corresponding_institution_ids":["https://openalex.org/I205783295"],"apc_list":null,"apc_paid":null,"fwci":1.8448,"has_fulltext":true,"cited_by_count":30,"citation_normalized_percentile":{"value":0.87374766,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"543","last_page":"554"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.974399983882904,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9703999757766724,"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/normative","display_name":"Normative","score":0.6738547086715698},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6205675005912781},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.5224953293800354},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.4390339255332947},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4251275956630707},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4224271774291992},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3457280397415161},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.32833296060562134},{"id":"https://openalex.org/keywords/epistemology","display_name":"Epistemology","score":0.09027016162872314}],"concepts":[{"id":"https://openalex.org/C44725695","wikidata":"https://www.wikidata.org/wiki/Q288156","display_name":"Normative","level":2,"score":0.6738547086715698},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6205675005912781},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.5224953293800354},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4390339255332947},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4251275956630707},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4224271774291992},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3457280397415161},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32833296060562134},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.09027016162872314},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3461702.3462620","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3461702.3462620","pdf_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3461702.3462620&file=aiespp249aux.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2105.12754","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2105.12754","pdf_url":"https://arxiv.org/pdf/2105.12754","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:10.1145/3461702.3462620","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3461702.3462620","pdf_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3461702.3462620&file=aiespp249aux.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Gender equality","score":0.5299999713897705,"id":"https://metadata.un.org/sdg/5"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3164652469.pdf","grobid_xml":"https://content.openalex.org/works/W3164652469.grobid-xml"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W1905882502","https://openalex.org/W1931639407","https://openalex.org/W2058556535","https://openalex.org/W2090048052","https://openalex.org/W2140006089","https://openalex.org/W2144883443","https://openalex.org/W2163284576","https://openalex.org/W2325920097","https://openalex.org/W2406012631","https://openalex.org/W2578190051","https://openalex.org/W2588822708","https://openalex.org/W2598764358","https://openalex.org/W2610316725","https://openalex.org/W2748163013","https://openalex.org/W2766927845","https://openalex.org/W2772495254","https://openalex.org/W2781265533","https://openalex.org/W2788481061","https://openalex.org/W2791213089","https://openalex.org/W2795908329","https://openalex.org/W2809795725","https://openalex.org/W2899136066","https://openalex.org/W2902633481","https://openalex.org/W2903410490","https://openalex.org/W2913974265","https://openalex.org/W2954112064","https://openalex.org/W2955037114","https://openalex.org/W2962953664","https://openalex.org/W2964091292","https://openalex.org/W2965816774","https://openalex.org/W2989168403","https://openalex.org/W2991618856","https://openalex.org/W2994026551","https://openalex.org/W2998746484","https://openalex.org/W3005511556","https://openalex.org/W3010110357","https://openalex.org/W3013451997","https://openalex.org/W3029264758","https://openalex.org/W3038911810","https://openalex.org/W3045524757","https://openalex.org/W3047564907","https://openalex.org/W3084611909","https://openalex.org/W3093541323","https://openalex.org/W3101298150","https://openalex.org/W3108115893","https://openalex.org/W3119746452","https://openalex.org/W3121464409","https://openalex.org/W3162205072","https://openalex.org/W3172707490","https://openalex.org/W4231815665","https://openalex.org/W4232486440","https://openalex.org/W4288083800","https://openalex.org/W4288083803","https://openalex.org/W4312286475","https://openalex.org/W4312769147"],"related_works":["https://openalex.org/W1989297139","https://openalex.org/W2342143608","https://openalex.org/W2496755843","https://openalex.org/W4213090964","https://openalex.org/W892323923","https://openalex.org/W952030982","https://openalex.org/W2128789995","https://openalex.org/W3038899278","https://openalex.org/W3106689948","https://openalex.org/W3210985794"],"abstract_inverted_index":{"Scholars":[0],"have":[1,61],"recently":[2],"drawn":[3],"attention":[4],"to":[5,37,41,105,120,144,162,184,197,209],"a":[6],"range":[7],"of":[8,15,22,65,74,150,160,187,206],"controversial":[9],"issues":[10],"posed":[11,202],"by":[12,58,178,203],"the":[13,54,63,97,115,135,169,199,204],"use":[14,64,83,205],"computer":[16,66,207],"vision":[17,47,67,80,208],"for":[18,43,68,76],"automatically":[19],"generating":[20],"descriptions":[21,73,149],"people":[23],"in":[24,124,134,146],"images.":[25],"Despite":[26],"these":[27,122,155,173,188],"concerns,":[28,189],"automated":[29],"image":[30],"description":[31],"has":[32,101],"become":[33],"an":[34,130,164],"important":[35],"tool":[36,88],"ensure":[38],"equitable":[39],"access":[40],"information":[42],"blind":[44,77],"and":[45,78,114],"low":[46,79],"people.":[48,81],"In":[49],"this":[50],"paper,":[51],"we":[52,95],"investigate":[53],"ethical":[55],"dilemmas":[56,201],"faced":[57],"companies":[59],"that":[60,99,167,182,191],"adopted":[62,102],"producing":[69],"alt":[70,86,125,147,211],"text:":[71],"textual":[72],"images":[75],"We":[82,127,153,176],"Facebook's":[84],"automatic":[85],"text":[87,148],"as":[89,109],"our":[90],"primary":[91],"case":[92],"study.":[93],"First,":[94],"analyze":[96],"policies":[98],"Facebook":[100],"with":[103],"respect":[104],"identity":[106],"categories,":[107],"such":[108],"race,":[110],"gender,":[111],"age,":[112],"etc.,":[113],"company's":[116],"decisions":[117],"about":[118],"whether":[119],"present":[121],"terms":[123],"text.":[126,212],"then":[128],"describe":[129],"alternative---and":[131],"manual---approach":[132],"practiced":[133],"museum":[136],"community,":[137],"focusing":[138],"on":[139],"how":[140],"museums":[141],"determine":[142],"what":[143],"include":[145],"cultural":[151],"artifacts.":[152],"compare":[154],"policies,":[156],"using":[157],"notable":[158],"points":[159],"contrast":[161],"develop":[163],"analytic":[165],"framework":[166],"characterizes":[168],"particular":[170],"apprehensions":[171],"behind":[172],"policy":[174],"choices.":[175],"conclude":[177],"considering":[179],"two":[180],"strategies":[181],"seem":[183],"sidestep":[185],"some":[186],"finding":[190],"there":[192],"are":[193],"no":[194],"easy":[195],"ways":[196],"avoid":[198],"normative":[200],"automate":[210]},"counts_by_year":[{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2021-06-07T00:00:00"}