{"id":"https://openalex.org/W4396786581","doi":"https://doi.org/10.1145/3630106.3658905","title":"A preprocessing Shapley value-based approach to detect relevant and disparity prone features in machine learning","display_name":"A preprocessing Shapley value-based approach to detect relevant and disparity prone features in machine learning","publication_year":2024,"publication_date":"2024-06-03","ids":{"openalex":"https://openalex.org/W4396786581","doi":"https://doi.org/10.1145/3630106.3658905"},"language":"en","primary_location":{"id":"doi:10.1145/3630106.3658905","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3630106.3658905","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3630106.3658905","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2024 ACM Conference on Fairness Accountability and Transparency","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3630106.3658905","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5040377739","display_name":"Guilherme Dean Pelegrina","orcid":"https://orcid.org/0000-0001-7301-6167"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]},{"id":"https://openalex.org/I18167132","display_name":"Universidade Presbiteriana Mackenzie","ror":"https://ror.org/006nc8n95","country_code":"BR","type":"education","lineage":["https://openalex.org/I18167132"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Guilherme Dean Pelegrina","raw_affiliation_strings":["School of Applied Sciences, University of Campinas, Brazil and Mackenzie Presbyterian University, Brazil"],"raw_orcid":"https://orcid.org/0000-0001-7301-6167","affiliations":[{"raw_affiliation_string":"School of Applied Sciences, University of Campinas, Brazil and Mackenzie Presbyterian University, Brazil","institution_ids":["https://openalex.org/I18167132","https://openalex.org/I181391015"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066732273","display_name":"Miguel Couceiro","orcid":"https://orcid.org/0000-0003-2316-7623"},"institutions":[{"id":"https://openalex.org/I121345201","display_name":"Instituto de Engenharia de Sistemas e Computadores Investiga\u00e7\u00e3o e Desenvolvimento","ror":"https://ror.org/04mqy3p58","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I121345201","https://openalex.org/I4210125590"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]},{"id":"https://openalex.org/I4210121838","display_name":"Laboratoire Lorrain de Recherche en Informatique et ses Applications","ror":"https://ror.org/02vnf0c38","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I277688954","https://openalex.org/I4210107720","https://openalex.org/I4210121838","https://openalex.org/I4210159245","https://openalex.org/I90183372"]},{"id":"https://openalex.org/I90183372","display_name":"Universit\u00e9 de Lorraine","ror":"https://ror.org/04vfs2w97","country_code":"FR","type":"education","lineage":["https://openalex.org/I90183372"]}],"countries":["FR","PT"],"is_corresponding":false,"raw_author_name":"Miguel Couceiro","raw_affiliation_strings":["CNRS, LORIA, Universit\u00e9 de Lorraine, France and INESC-ID, Instituto Superior T\u00e9cnico, Universidade de Lisboa, Portugal"],"raw_orcid":"https://orcid.org/0000-0003-2316-7623","affiliations":[{"raw_affiliation_string":"CNRS, LORIA, Universit\u00e9 de Lorraine, France and INESC-ID, Instituto Superior T\u00e9cnico, Universidade de Lisboa, Portugal","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I141596103","https://openalex.org/I90183372","https://openalex.org/I4210121838","https://openalex.org/I121345201"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047456733","display_name":"Leonardo Tomazeli Duarte","orcid":"https://orcid.org/0000-0003-0290-0080"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Leonardo Tomazeli Duarte","raw_affiliation_strings":["School of Applied Sciences, University of Campinas, Brazil"],"raw_orcid":"https://orcid.org/0000-0003-0290-0080","affiliations":[{"raw_affiliation_string":"School of Applied Sciences, University of Campinas, Brazil","institution_ids":["https://openalex.org/I181391015"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8211,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.76165169,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"279","last_page":"289"},"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":0.9965999722480774,"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":0.9965999722480774,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9909999966621399,"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/T13051","display_name":"Qualitative Comparative Analysis Research","score":0.9284999966621399,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7302299737930298},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.6917023658752441},{"id":"https://openalex.org/keywords/transparency","display_name":"Transparency (behavior)","score":0.6397039890289307},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6255661249160767},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.53912752866745},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5012540817260742},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.42037463188171387},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32295167446136475},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.16562819480895996}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7302299737930298},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.6917023658752441},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.6397039890289307},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6255661249160767},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.53912752866745},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5012540817260742},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.42037463188171387},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32295167446136475},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.16562819480895996}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3630106.3658905","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3630106.3658905","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3630106.3658905","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2024 ACM Conference on Fairness Accountability and Transparency","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-04568343v1","is_oa":true,"landing_page_url":"https://inria.hal.science/hal-04568343","pdf_url":"https://inria.hal.science/hal-04568343v1/file/facct2024-final95.pdf","source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT 2024), Fabro Steibel, Meg Young, Ricardo Baeza-Yates, Jun 2024, Rio de Janeiro (BR), Brazil. pp.279-289, &#x27E8;10.1145/3630106.3658905&#x27E9;","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"doi:10.1145/3630106.3658905","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3630106.3658905","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3630106.3658905","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2024 ACM Conference on Fairness Accountability and Transparency","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1842668522","display_name":null,"funder_award_id":"2020/09838-0","funder_id":"https://openalex.org/F4320320997","funder_display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo"},{"id":"https://openalex.org/G2194796483","display_name":null,"funder_award_id":"2020/09838","funder_id":"https://openalex.org/F4320320997","funder_display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo"},{"id":"https://openalex.org/G3600004211","display_name":null,"funder_award_id":"2020/10572-5","funder_id":"https://openalex.org/F4320320997","funder_display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo"},{"id":"https://openalex.org/G3857068732","display_name":"Intrinsic and Extrinsic evaluation of biases in large language models","funder_award_id":"ANR-23-IAS1-0004","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"},{"id":"https://openalex.org/G6438247056","display_name":null,"funder_award_id":"2021/","funder_id":"https://openalex.org/F4320320997","funder_display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo"},{"id":"https://openalex.org/G8262628548","display_name":null,"funder_award_id":"2021/11086-0","funder_id":"https://openalex.org/F4320320997","funder_display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo"}],"funders":[{"id":"https://openalex.org/F4320320883","display_name":"Agence Nationale de la Recherche","ror":"https://ror.org/00rbzpz17"},{"id":"https://openalex.org/F4320320997","display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","ror":"https://ror.org/02ddkpn78"},{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4396786581.pdf"},"referenced_works_count":57,"referenced_works":["https://openalex.org/W108417620","https://openalex.org/W1638081485","https://openalex.org/W1971916086","https://openalex.org/W2008818676","https://openalex.org/W2101267652","https://openalex.org/W2101753511","https://openalex.org/W2103459159","https://openalex.org/W2116666691","https://openalex.org/W2127538534","https://openalex.org/W2127658298","https://openalex.org/W2156204103","https://openalex.org/W2560674852","https://openalex.org/W2561618607","https://openalex.org/W2618851150","https://openalex.org/W2726539084","https://openalex.org/W2787955716","https://openalex.org/W2797800832","https://openalex.org/W2805655805","https://openalex.org/W2809878087","https://openalex.org/W2883468738","https://openalex.org/W2892741787","https://openalex.org/W2925507233","https://openalex.org/W2962862931","https://openalex.org/W2963116854","https://openalex.org/W2979506454","https://openalex.org/W2996404781","https://openalex.org/W2997591727","https://openalex.org/W2999615587","https://openalex.org/W3082455399","https://openalex.org/W3105959310","https://openalex.org/W3121787084","https://openalex.org/W3123056373","https://openalex.org/W3126453897","https://openalex.org/W3133726592","https://openalex.org/W3135028703","https://openalex.org/W3135649946","https://openalex.org/W3146613606","https://openalex.org/W3157730516","https://openalex.org/W3195149063","https://openalex.org/W3203878893","https://openalex.org/W3207627539","https://openalex.org/W3208152093","https://openalex.org/W3211208090","https://openalex.org/W4214634230","https://openalex.org/W4214835294","https://openalex.org/W4226022484","https://openalex.org/W4226346920","https://openalex.org/W4285605356","https://openalex.org/W4287200665","https://openalex.org/W4289258088","https://openalex.org/W4298289188","https://openalex.org/W4384284068","https://openalex.org/W4385223560","https://openalex.org/W4386865177","https://openalex.org/W4388657765","https://openalex.org/W6605758687","https://openalex.org/W6678992168"],"related_works":["https://openalex.org/W2329500892","https://openalex.org/W4382930947","https://openalex.org/W28991112","https://openalex.org/W3081288631","https://openalex.org/W3152382318","https://openalex.org/W2370726991","https://openalex.org/W3004686567","https://openalex.org/W2738656338","https://openalex.org/W2603787370","https://openalex.org/W2555400967"],"abstract_inverted_index":{"Decision":[0],"support":[1],"systems":[2],"became":[3],"ubiquitous":[4],"in":[5],"every":[6],"aspect":[7],"of":[8,31,40,59],"human":[9],"lives.":[10],"Their":[11],"reliance":[12],"on":[13,64,102],"increasingly":[14],"complex":[15],"and":[16,23,46,117],"opaque":[17],"machine":[18],"learning":[19],"models":[20],"raises":[21],"transparency":[22],"fairness":[24,60,99],"concerns":[25],"with":[26,56,67],"respect":[27,68],"to":[28,37,47,69,113],"unprivileged":[29],"groups":[30],"people.":[32],"This":[33],"motivated":[34],"several":[35],"efforts":[36],"estimate":[38],"importance":[39],"features":[41,71,77,110],"towards":[42],"the":[43,103],"models\u2019":[44],"performance":[45,65],"detect":[48],"unfair/disparate":[49],"decisions.":[50],"The":[51],"latter":[52],"is":[53,96],"often":[54],"dealt":[55],"by":[57],"means":[58],"metrics":[61,66,100],"that":[62,72,111,118],"rely":[63],"predefined":[70],"are":[73],"considered":[74],"protected":[75],"(salient":[76],"such":[78,93],"as":[79,87],"age,":[80],"gender,":[81],"ethnicity,":[82],"etc.)":[83],"and/or":[84],"sensitive":[85],"(such":[86],"education,":[88],"/occupation,":[89],"banking":[90],"information).":[91],"However,":[92],"an":[94],"approach":[95],"subjective":[97],"(as":[98],"depend":[101],"choice":[104],"features),":[105],"there":[106],"may":[107,119],"be":[108],"other":[109],"lead":[112],"unfair":[114],"(disparate)":[115],"decisions":[116],"ask":[120],"for":[121],"suitable":[122],"interpretations.":[123]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2024-05-10T00:00:00"}
