{"id":"https://openalex.org/W4385568026","doi":"https://doi.org/10.1145/3580305.3599215","title":"2nd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI)","display_name":"2nd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI)","publication_year":2023,"publication_date":"2023-08-04","ids":{"openalex":"https://openalex.org/W4385568026","doi":"https://doi.org/10.1145/3580305.3599215"},"language":"en","primary_location":{"id":"doi:10.1145/3580305.3599215","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599215","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100767050","display_name":"Chen Zhao","orcid":"https://orcid.org/0000-0002-6400-0048"},"institutions":[{"id":"https://openalex.org/I157394403","display_name":"Baylor University","ror":"https://ror.org/005781934","country_code":"US","type":"education","lineage":["https://openalex.org/I157394403"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chen Zhao","raw_affiliation_strings":["Baylor University, Waco, TX, USA"],"affiliations":[{"raw_affiliation_string":"Baylor University, Waco, TX, USA","institution_ids":["https://openalex.org/I157394403"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100352703","display_name":"Feng Chen","orcid":"https://orcid.org/0000-0002-4508-5963"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Feng Chen","raw_affiliation_strings":["University of Texas at Dallas, Richardson, TX, USA"],"affiliations":[{"raw_affiliation_string":"University of Texas at Dallas, Richardson, TX, USA","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008463509","display_name":"Xintao Wu","orcid":"https://orcid.org/0000-0002-2823-3063"},"institutions":[{"id":"https://openalex.org/I78715868","display_name":"University of Arkansas at Fayetteville","ror":"https://ror.org/05jbt9m15","country_code":"US","type":"education","lineage":["https://openalex.org/I78715868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xintao Wu","raw_affiliation_strings":["University of Arkansas, Fayetteville, NC, USA"],"affiliations":[{"raw_affiliation_string":"University of Arkansas, Fayetteville, NC, USA","institution_ids":["https://openalex.org/I78715868"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004514673","display_name":"Haifeng Chen","orcid":"https://orcid.org/0000-0003-3934-7311"},"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":"Haifeng Chen","raw_affiliation_strings":["NEC Laboratories America, Princeton, NJ, USA"],"affiliations":[{"raw_affiliation_string":"NEC Laboratories America, Princeton, NJ, USA","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047215778","display_name":"Jiayu Zhou","orcid":"https://orcid.org/0000-0003-4336-6777"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiayu Zhou","raw_affiliation_strings":["Michigan State University, East Lansing, MI, USA"],"affiliations":[{"raw_affiliation_string":"Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100767050"],"corresponding_institution_ids":["https://openalex.org/I157394403"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12512692,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5903","last_page":"5904"},"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":0.9983999729156494,"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":0.9983999729156494,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9864000082015991,"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":0.9829999804496765,"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/popularity","display_name":"Popularity","score":0.778448224067688},{"id":"https://openalex.org/keywords/ethical-issues","display_name":"Ethical issues","score":0.6922853589057922},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.5720136165618896},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5105003118515015},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5041080713272095},{"id":"https://openalex.org/keywords/engineering-ethics","display_name":"Engineering ethics","score":0.5001506805419922},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3322448134422302},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.20815584063529968},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.19673305749893188},{"id":"https://openalex.org/keywords/law","display_name":"Law","score":0.10071733593940735}],"concepts":[{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.778448224067688},{"id":"https://openalex.org/C2986663376","wikidata":"https://www.wikidata.org/wiki/Q9465","display_name":"Ethical issues","level":2,"score":0.6922853589057922},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.5720136165618896},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5105003118515015},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5041080713272095},{"id":"https://openalex.org/C55587333","wikidata":"https://www.wikidata.org/wiki/Q1133029","display_name":"Engineering ethics","level":1,"score":0.5001506805419922},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3322448134422302},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.20815584063529968},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.19673305749893188},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.10071733593940735},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3580305.3599215","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599215","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5921281487","display_name":null,"funder_award_id":"number","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7055289205","display_name":null,"funder_award_id":"2147375","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","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":false,"pdf":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W3003257608","https://openalex.org/W3086700537","https://openalex.org/W3165956705","https://openalex.org/W4281492493"],"related_works":["https://openalex.org/W4300506154","https://openalex.org/W2177530805","https://openalex.org/W3211386016","https://openalex.org/W4255784647","https://openalex.org/W2060969805","https://openalex.org/W2779160393","https://openalex.org/W4392104646","https://openalex.org/W191070824","https://openalex.org/W250348290","https://openalex.org/W43864903"],"abstract_inverted_index":{"Ethical":[0],"AI":[1,47,70,99],"has":[2,8,77,139],"become":[3],"increasingly":[4],"important,":[5],"and":[6,14,38,74,92,110,128,157,168],"it":[7],"been":[9,140],"attracting":[10],"attention":[11],"from":[12,159],"academia":[13],"industry,":[15],"due":[16],"to":[17,54,57,125,134,162],"its":[18],"increased":[19],"popularity":[20],"in":[21,35,71,143,171],"real-world":[22],"applications":[23],"with":[24],"fairness":[25],"concerns.":[26],"It":[27],"also":[28,78],"places":[29],"fundamental":[30],"importance":[31],"on":[32,165],"ethical":[33,46,69,98,136,172],"considerations":[34],"determining":[36],"legitimate":[37],"illegitimate":[39],"uses":[40],"of":[41,63,68,82,108],"AI.":[42,173],"Organizations":[43],"that":[44],"apply":[45],"have":[48],"clearly":[49],"stated":[50],"well-defined":[51],"review":[52],"processes":[53],"ensure":[55],"adherence":[56],"legal":[58],"guidelines.":[59],"Therefore,":[60],"the":[61,66],"wave":[62],"research":[64,156],"at":[65,131],"intersection":[67],"data":[72],"mining":[73],"machine":[75],"learning":[76,116],"influenced":[79],"other":[80],"fields":[81],"science,":[83],"including":[84],"computer":[85],"vision,":[86],"natural":[87],"language":[88],"processing,":[89],"reinforcement":[90],"learning,":[91],"social":[93],"science.":[94],"Despite":[95],"these":[96],"successes,":[97],"still":[100],"faces":[101],"many":[102],"challenges,":[103,167],"such":[104],"as":[105],"a":[106,151],"lack":[107],"interpretable":[109],"explainable":[111],"methods":[112],"for":[113,154],"fairness-aware":[114],"deep":[115],"models,":[117],"etc.":[118],"Consequently,":[119],"there":[120],"is":[121],"an":[122],"urgent":[123],"need":[124],"bring":[126],"experts":[127],"researchers":[129],"together":[130],"prestigious":[132],"venues":[133],"discuss":[135],"AI,":[137],"which":[138],"rarely":[141],"seen":[142],"previous":[144],"KDD":[145],"conferences.":[146],"This":[147],"workshop":[148],"will":[149],"provide":[150],"premium":[152],"platform":[153],"both":[155],"industry":[158],"different":[160],"backgrounds":[161],"exchange":[163],"ideas":[164],"opportunities,":[166],"cutting-edge":[169],"techniques":[170]},"counts_by_year":[],"updated_date":"2026-03-15T09:29:46.208133","created_date":"2025-10-10T00:00:00"}
