{"id":"https://openalex.org/W3080638064","doi":"https://doi.org/10.1145/3394486.3406708","title":"Dealing with Bias and Fairness in Data Science Systems","display_name":"Dealing with Bias and Fairness in Data Science Systems","publication_year":2020,"publication_date":"2020-08-20","ids":{"openalex":"https://openalex.org/W3080638064","doi":"https://doi.org/10.1145/3394486.3406708","mag":"3080638064"},"language":"en","primary_location":{"id":"doi:10.1145/3394486.3406708","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3394486.3406708","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3394486.3406708","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","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/10.1145/3394486.3406708","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039038824","display_name":"Pedro Saleiro","orcid":"https://orcid.org/0000-0003-2750-1692"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Pedro Saleiro","raw_affiliation_strings":["Feedzai, Lisbon, Portugal"],"affiliations":[{"raw_affiliation_string":"Feedzai, Lisbon, Portugal","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026014943","display_name":"Kit T. Rodolfa","orcid":"https://orcid.org/0000-0002-0829-1282"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kit T. Rodolfa","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081839926","display_name":"Rayid Ghani","orcid":"https://orcid.org/0000-0003-0235-1843"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rayid Ghani","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5039038824"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.8487,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.94008508,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3513","last_page":"3514"},"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":0.9995999932289124,"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":0.9995999932289124,"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":0.9883000254631042,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9753000140190125,"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/computer-science","display_name":"Computer science","score":0.8030077219009399},{"id":"https://openalex.org/keywords/audit","display_name":"Audit","score":0.661013126373291},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.6208240985870361},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.6124710440635681},{"id":"https://openalex.org/keywords/fairness-measure","display_name":"Fairness measure","score":0.5913886427879333},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5255626440048218},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5248724818229675},{"id":"https://openalex.org/keywords/management-science","display_name":"Management science","score":0.32942819595336914},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.1693885624408722},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.0856063961982727}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8030077219009399},{"id":"https://openalex.org/C199521495","wikidata":"https://www.wikidata.org/wiki/Q181487","display_name":"Audit","level":2,"score":0.661013126373291},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.6208240985870361},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.6124710440635681},{"id":"https://openalex.org/C11867375","wikidata":"https://www.wikidata.org/wiki/Q5430671","display_name":"Fairness measure","level":4,"score":0.5913886427879333},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5255626440048218},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5248724818229675},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.32942819595336914},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.1693885624408722},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0856063961982727},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"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/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3394486.3406708","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3394486.3406708","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3394486.3406708","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3394486.3406708","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3394486.3406708","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3394486.3406708","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7599999904632568,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G5814275596","display_name":null,"funder_award_id":"1762045","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":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3080638064.pdf","grobid_xml":"https://content.openalex.org/works/W3080638064.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1981276685","https://openalex.org/W2014352947","https://openalex.org/W2540757487","https://openalex.org/W2594166818","https://openalex.org/W2597425331","https://openalex.org/W2605800822","https://openalex.org/W2612690371","https://openalex.org/W2750585749","https://openalex.org/W2753845591","https://openalex.org/W2788284633","https://openalex.org/W2790628304","https://openalex.org/W2809878087","https://openalex.org/W2810542350","https://openalex.org/W2890416412","https://openalex.org/W2900572965","https://openalex.org/W2900885930","https://openalex.org/W2949200088","https://openalex.org/W2962718185","https://openalex.org/W2963178340","https://openalex.org/W2964031043","https://openalex.org/W3000952406","https://openalex.org/W3097529099","https://openalex.org/W3102708241","https://openalex.org/W3123374861","https://openalex.org/W3141075872","https://openalex.org/W4289258088","https://openalex.org/W6728551298","https://openalex.org/W6734300861","https://openalex.org/W6748377460","https://openalex.org/W6765646913","https://openalex.org/W6809680140"],"related_works":["https://openalex.org/W2770234245","https://openalex.org/W96612179","https://openalex.org/W4229499248","https://openalex.org/W2566006169","https://openalex.org/W1567818861","https://openalex.org/W2987774938","https://openalex.org/W4256492088","https://openalex.org/W632915154","https://openalex.org/W2055733372","https://openalex.org/W2767394639"],"abstract_inverted_index":{"Tackling":[0],"issues":[1,73],"of":[2,27,39,49,74,86,144],"bias":[3,75,80,134,154],"and":[4,8,35,42,56,61,76,81,88,91,117,127,157,170],"fairness":[5,82],"when":[6],"building":[7],"deploying":[9],"data":[10,43,102],"science":[11],"systems":[12],"has":[13,30],"received":[14],"increased":[15],"attention":[16],"from":[17,125],"the":[18,28,113,137,142,148],"research":[19,29,116],"community":[20],"in":[21,173],"recent":[22],"years,":[23],"yet":[24],"a":[25,47,165],"lot":[26],"focused":[31],"on":[32,64,168],"theoretical":[33],"aspects":[34],"very":[36],"limited":[37],"set":[38],"application":[40],"areas":[41],"sets.":[44],"There":[45],"is":[46,97],"lack":[48],"1)":[50],"practical":[51,130],"training":[52],"materials,":[53],"2)":[54],"methodologies,":[55],"3)":[57],"tools":[58,158],"for":[59,101],"researchers":[60],"developers":[62],"working":[63],"real-world":[65],"algorithmic":[66,123],"decision":[67],"making":[68,162],"system":[69,176],"to":[70,111,129,159],"deal":[71],"with":[72,153],"fairness.":[77],"Today,":[78],"treating":[79],"as":[83],"primary":[84],"metrics":[85,96,126],"interest,":[87],"building,":[89],"selecting,":[90],"validating":[92],"models":[93],"using":[94,136],"those":[95],"not":[98],"standard":[99],"practice":[100],"scientists.":[103],"In":[104],"this":[105,145],"hands-on":[106,146],"tutorial":[107],"we":[108],"will":[109,150,177],"try":[110],"bridge":[112],"gap":[114],"between":[115],"practice,":[118],"by":[119],"deep":[120],"diving":[121],"into":[122],"fairness,":[124],"definitions":[128],"case":[131],"studies,":[132],"including":[133],"audits":[135],"Aequitas":[138],"toolkit":[139],"(http://github.com/dssg/aequitas).":[140],"By":[141],"end":[143],"tutorial,":[147],"audience":[149],"be":[151,178],"familiar":[152],"mitigation":[155],"frameworks":[156],"help":[160],"them":[161],"decisions":[163],"during":[164],"project":[166],"based":[167],"intervention":[169],"deployment":[171],"contexts":[172],"which":[174],"their":[175],"used.":[179]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
