{"id":"https://openalex.org/W4391389316","doi":"https://doi.org/10.1561/2200000106","title":"Causal Fairness Analysis: A Causal Toolkit for Fair Machine Learning","display_name":"Causal Fairness Analysis: A Causal Toolkit for Fair Machine Learning","publication_year":2024,"publication_date":"2024-01-31","ids":{"openalex":"https://openalex.org/W4391389316","doi":"https://doi.org/10.1561/2200000106"},"language":"en","primary_location":{"id":"doi:10.1561/2200000106","is_oa":false,"landing_page_url":"https://doi.org/10.1561/2200000106","pdf_url":null,"source":{"id":"https://openalex.org/S4210188176","display_name":"Foundations and Trends\u00ae in Machine Learning","issn_l":"1935-8237","issn":["1935-8237","1935-8245"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318575","host_organization_name":"Now Publishers","host_organization_lineage":["https://openalex.org/P4310318575"],"host_organization_lineage_names":["Now Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Foundations and Trends\u00ae in Machine Learning","raw_type":"journal-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/A5077424830","display_name":"Drago Ple\u010dko","orcid":"https://orcid.org/0000-0002-5433-196X"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]},{"id":"https://openalex.org/I4210123467","display_name":"Institut f\u00fcr Angewandte Statistik","ror":"https://ror.org/03abd2075","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210123467"]}],"countries":["CH","DE"],"is_corresponding":true,"raw_author_name":"Drago Ple\u010dko","raw_affiliation_strings":["Seminar f\u00fcr Statistik , ETH Z\u00fcrich,","Seminar f\u00fcr Statistik, ETH Z\u00fcrich, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seminar f\u00fcr Statistik , ETH Z\u00fcrich,","institution_ids":["https://openalex.org/I35440088","https://openalex.org/I4210123467"]},{"raw_affiliation_string":"Seminar f\u00fcr Statistik, ETH Z\u00fcrich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039620960","display_name":"Elias Bareinboim","orcid":null},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]},{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Elias Bareinboim","raw_affiliation_strings":["Columbia University Department of Computer Science, ,","Department of Computer Science, Columbia University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University Department of Computer Science, ,","institution_ids":["https://openalex.org/I76835614","https://openalex.org/I78577930"]},{"raw_affiliation_string":"Department of Computer Science, Columbia University, USA","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5077424830"],"corresponding_institution_ids":["https://openalex.org/I35440088","https://openalex.org/I4210123467"],"apc_list":null,"apc_paid":null,"fwci":10.7809,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.98261565,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"17","issue":"3","first_page":"304","last_page":"589"},"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":0.9901999831199646,"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":0.9901999831199646,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5819189548492432},{"id":"https://openalex.org/keywords/causal-analysis","display_name":"Causal analysis","score":0.48759904503822327},{"id":"https://openalex.org/keywords/causal-model","display_name":"Causal model","score":0.4782910943031311},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4703543186187744},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4372398257255554},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.2358923852443695},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.19739806652069092},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12347447872161865},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08323624730110168}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5819189548492432},{"id":"https://openalex.org/C2987525970","wikidata":"https://www.wikidata.org/wiki/Q96374569","display_name":"Causal analysis","level":2,"score":0.48759904503822327},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.4782910943031311},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4703543186187744},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4372398257255554},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.2358923852443695},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.19739806652069092},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12347447872161865},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08323624730110168}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1561/2200000106","is_oa":false,"landing_page_url":"https://doi.org/10.1561/2200000106","pdf_url":null,"source":{"id":"https://openalex.org/S4210188176","display_name":"Foundations and Trends\u00ae in Machine Learning","issn_l":"1935-8237","issn":["1935-8237","1935-8245"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318575","host_organization_name":"Now Publishers","host_organization_lineage":["https://openalex.org/P4310318575"],"host_organization_lineage_names":["Now Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Foundations and Trends\u00ae in Machine Learning","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1516659296","https://openalex.org/W1563313569","https://openalex.org/W1974906010","https://openalex.org/W1977570006","https://openalex.org/W1981457167","https://openalex.org/W2014373672","https://openalex.org/W2024894923","https://openalex.org/W2026019770","https://openalex.org/W2031668171","https://openalex.org/W2039811614","https://openalex.org/W2048087720","https://openalex.org/W2059141064","https://openalex.org/W2075308865","https://openalex.org/W2080061756","https://openalex.org/W2085293969","https://openalex.org/W2093065590","https://openalex.org/W2097246321","https://openalex.org/W2111640236","https://openalex.org/W2116984840","https://openalex.org/W2132917208","https://openalex.org/W2137370054","https://openalex.org/W2144512268","https://openalex.org/W2150997454","https://openalex.org/W2157928966","https://openalex.org/W2158161318","https://openalex.org/W2162068690","https://openalex.org/W2166454173","https://openalex.org/W2168683373","https://openalex.org/W2197153126","https://openalex.org/W2571311322","https://openalex.org/W2788651580","https://openalex.org/W2797566965","https://openalex.org/W2911964244","https://openalex.org/W2962977061","https://openalex.org/W2963887880","https://openalex.org/W2964012073","https://openalex.org/W2964031043","https://openalex.org/W2996483157","https://openalex.org/W3206637938","https://openalex.org/W4220858968","https://openalex.org/W4246671941"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4313488044","https://openalex.org/W3209574120","https://openalex.org/W4312192474","https://openalex.org/W4210805261"],"abstract_inverted_index":{"Decision-making":[0],"systems":[1,36],"based":[2],"on":[3],"AI":[4],"and":[5,23,58,69,85,109,180,192,211,236,251],"machine":[6],"learning":[7],"have":[8],"been":[9],"used":[10],"throughout":[11],"a":[12,32,92,155],"wide":[13],"range":[14],"of":[15,56,101,113,121,130,144,162,177,183,195,248],"real-world":[16],"scenarios,":[17],"including":[18],"healthcare,":[19],"law":[20],"enforcement,":[21],"education,":[22],"finance.":[24],"It":[25],"is":[26],"no":[27],"longer":[28],"far-fetched":[29],"to":[30,49,126,169,189,209,244],"envision":[31],"future":[33],"where":[34],"autonomous":[35],"will":[37,124],"drive":[38],"entire":[39],"business":[40],"decisions":[41,63,76],"and,":[42],"more":[43],"broadly,":[44],"support":[45],"large-scale":[46],"decision-making":[47,116],"infrastructure":[48],"solve":[50,170],"society\u2019s":[51],"most":[52],"challenging":[53],"problems.":[54],"Issues":[55],"unfairness":[57],"discrimination":[59],"are":[60,64,72,77,228],"pervasive":[61],"when":[62,75],"being":[65],"made":[66,78],"by":[67],"humans,":[68],"remain":[70],"(or":[71],"potentially":[73],"amplified)":[74],"using":[79],"machines":[80],"with":[81,98,138],"little":[82],"transparency,":[83],"accountability,":[84],"fairness.":[86],"In":[87,167],"this":[88,104],"monograph,":[89],"we":[90,157,173,223],"introduce":[91],"framework":[93],"for":[94,231],"causal":[95,145,226,233],"fairness":[96,114,184,234],"analysis":[97,235],"the":[99,128,131,135,139,149,152,159,171,175,196,202,205,213,220,238,246],"intent":[100],"filling":[102],"in":[103,115,134,151,201,219],"gap,":[105],"i.e.,":[106],"understanding,":[107],"modeling,":[108],"possibly":[110],"solving":[111],"issues":[112],"settings.":[117],"The":[118],"main":[119],"insight":[120],"our":[122],"approach":[123],"be":[125],"link":[127],"quantification":[129],"disparities":[132],"present":[133],"observed":[136],"data":[137],"underlying,":[140],"often":[141],"unobserved,":[142],"collection":[143],"mechanisms":[146,191],"that":[147,185],"generate":[148],"disparity":[150],"first":[153,206],"place,":[154],"challenge":[156],"call":[158],"Fundamental":[160],"Problem":[161],"Causal":[163],"Fairness":[164,203,239],"Analysis":[165],"(FPCFA).":[166],"order":[168],"FPCFA,":[172],"study":[174,224],"problem":[176],"decomposing":[178],"variations":[179,188],"empirical":[181],"measures":[182],"attribute":[186],"such":[187],"structural":[190],"different":[193],"units":[194],"population.":[197],"Our":[198],"effort":[199],"culminates":[200],"Map,":[204],"systematic":[207],"attempt":[208],"organize":[210],"explain":[212],"relationship":[214],"between":[215],"various":[216],"criteria":[217],"found":[218],"literature.":[221],"Finally,":[222],"which":[225,241],"assumptions":[227],"minimally":[229],"needed":[230],"performing":[232],"propose":[237],"Cookbook,":[240],"allows":[242],"one":[243],"assess":[245],"existence":[247],"disparate":[249,252],"impact":[250],"treatment.":[253]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":4}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}