{"id":"https://openalex.org/W4380319026","doi":"https://doi.org/10.1145/3593013.3594036","title":"Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-Making","display_name":"Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-Making","publication_year":2023,"publication_date":"2023-06-12","ids":{"openalex":"https://openalex.org/W4380319026","doi":"https://doi.org/10.1145/3593013.3594036"},"language":"en","primary_location":{"id":"doi:10.1145/3593013.3594036","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3593013.3594036","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3593013.3594036","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 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/10.1145/3593013.3594036","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029332467","display_name":"Luke Guerdan","orcid":"https://orcid.org/0009-0009-3566-9429"},"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":true,"raw_author_name":"Luke Guerdan","raw_affiliation_strings":["Carnegie Mellon University, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057845767","display_name":"Amanda Coston","orcid":"https://orcid.org/0000-0001-9282-9921"},"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":"Amanda Coston","raw_affiliation_strings":["Carnegie Mellon University, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001070941","display_name":"Zhiwei Steven Wu","orcid":"https://orcid.org/0000-0002-8125-8227"},"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":"Zhiwei Steven Wu","raw_affiliation_strings":["Carnegie Mellon University, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022664382","display_name":"Kenneth Holstein","orcid":"https://orcid.org/0000-0001-6730-922X"},"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":"Kenneth Holstein","raw_affiliation_strings":["Carnegie Mellon University, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5029332467"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":4.3692,"has_fulltext":true,"cited_by_count":17,"citation_normalized_percentile":{"value":0.95348165,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"688","last_page":"704"},"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":0.9959999918937683,"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":0.9959999918937683,"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":0.9900000095367432,"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/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9588000178337097,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/proxy","display_name":"Proxy (statistics)","score":0.6865594983100891},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.683233916759491},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6499273777008057},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.5568366646766663},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.5321668386459351},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4802727699279785},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45801037549972534},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4461112916469574},{"id":"https://openalex.org/keywords/causal-structure","display_name":"Causal structure","score":0.4433867037296295},{"id":"https://openalex.org/keywords/causal-model","display_name":"Causal model","score":0.4265914857387543},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.33705392479896545},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15545722842216492},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1227845847606659}],"concepts":[{"id":"https://openalex.org/C2780148112","wikidata":"https://www.wikidata.org/wiki/Q1432581","display_name":"Proxy (statistics)","level":2,"score":0.6865594983100891},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.683233916759491},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6499273777008057},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.5568366646766663},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.5321668386459351},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4802727699279785},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45801037549972534},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4461112916469574},{"id":"https://openalex.org/C163504300","wikidata":"https://www.wikidata.org/wiki/Q2364925","display_name":"Causal structure","level":2,"score":0.4433867037296295},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.4265914857387543},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.33705392479896545},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15545722842216492},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1227845847606659},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3593013.3594036","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3593013.3594036","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3593013.3594036","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 ACM Conference on Fairness, Accountability, and Transparency","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3593013.3594036","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3593013.3594036","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3593013.3594036","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 ACM Conference on Fairness, Accountability, and Transparency","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.699999988079071}],"awards":[{"id":"https://openalex.org/G2584449986","display_name":"Graduate Research Fellowship Program (GRFP)","funder_award_id":"1745016","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4587571719","display_name":null,"funder_award_id":"CASMI","funder_id":"https://openalex.org/F4320309475","funder_display_name":"Northwestern University"},{"id":"https://openalex.org/G4640338107","display_name":null,"funder_award_id":"Technology","funder_id":"https://openalex.org/F4320309475","funder_display_name":"Northwestern University"},{"id":"https://openalex.org/G4863571209","display_name":null,"funder_award_id":"DGE-1745016","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6242458504","display_name":null,"funder_award_id":"1939606","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6894402473","display_name":null,"funder_award_id":"Fellowship","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7042311845","display_name":null,"funder_award_id":"939606","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"},{"id":"https://openalex.org/F4320309475","display_name":"Northwestern University","ror":"https://ror.org/000e0be47"},{"id":"https://openalex.org/F4320310207","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4380319026.pdf","grobid_xml":"https://content.openalex.org/works/W4380319026.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W2049910836","https://openalex.org/W2090727755","https://openalex.org/W2167460663","https://openalex.org/W2203167467","https://openalex.org/W2237502368","https://openalex.org/W2371804352","https://openalex.org/W2745133928","https://openalex.org/W2901895173","https://openalex.org/W2904715593","https://openalex.org/W2909212904","https://openalex.org/W2970837303","https://openalex.org/W2979893369","https://openalex.org/W2983137008","https://openalex.org/W2995006168","https://openalex.org/W2999637955","https://openalex.org/W3000875740","https://openalex.org/W3001062618","https://openalex.org/W3032816739","https://openalex.org/W3032942076","https://openalex.org/W3037843601","https://openalex.org/W3038505124","https://openalex.org/W3082042211","https://openalex.org/W3091315987","https://openalex.org/W3095542981","https://openalex.org/W3099742594","https://openalex.org/W3101792976","https://openalex.org/W3103751997","https://openalex.org/W3112374793","https://openalex.org/W3124833072","https://openalex.org/W3128485057","https://openalex.org/W3133874049","https://openalex.org/W3134631405","https://openalex.org/W3156106752","https://openalex.org/W3156669901","https://openalex.org/W3159250634","https://openalex.org/W3160122248","https://openalex.org/W3163411042","https://openalex.org/W3163443091","https://openalex.org/W3187543315","https://openalex.org/W3199781855","https://openalex.org/W3214627773","https://openalex.org/W4221104163","https://openalex.org/W4225001143","https://openalex.org/W4225006216","https://openalex.org/W4225087473","https://openalex.org/W4244528936","https://openalex.org/W4283168161","https://openalex.org/W4288058298"],"related_works":["https://openalex.org/W4390042219","https://openalex.org/W2161504683","https://openalex.org/W2526255754","https://openalex.org/W2131643694","https://openalex.org/W2477954850","https://openalex.org/W2740541622","https://openalex.org/W2784306284","https://openalex.org/W2093587551","https://openalex.org/W2766599768","https://openalex.org/W4372273223"],"abstract_inverted_index":{"A":[0],"growing":[1],"literature":[2],"on":[3,36,103],"human-AI":[4,139,162,211],"decision-making":[5,140,163],"investigates":[6],"strategies":[7,186],"for":[8,106,187],"combining":[9],"human":[10,48,206],"judgment":[11],"with":[12],"statistical":[13,117],"models":[14,89],"to":[15,26,113,147,173,200,224,233],"improve":[16],"decision-making.":[17],"Research":[18],"in":[19,62,97,138,160,178,193,239],"this":[20,41,120],"area":[21],"often":[22],"evaluates":[23],"proposed":[24],"improvements":[25],"models,":[27],"interfaces,":[28],"or":[29,83],"workflows":[30],"by":[31,230],"demonstrating":[32],"improved":[33],"predictive":[34,88],"performance":[35],"\u201cground":[37],"truth\u2019\u2019":[38],"labels.":[39],"However,":[40],"practice":[42],"overlooks":[43],"a":[44,63,144,216],"key":[45],"difference":[46],"between":[47,151],"judgments":[49],"and":[50,154,182],"model":[51],"predictions.":[52],"Whereas":[53],"humans":[54],"commonly":[55],"reason":[56],"about":[57],"broader":[58],"phenomena":[59,109],"of":[60,80,116,126,135,158,204,219],"interest":[61],"decision":[64],"\u2013":[65,87],"including":[66],"latent":[67],"constructs":[68],"that":[69,93,130,209,214],"are":[70,94,157],"not":[71],"directly":[72],"observable,":[73],"such":[74],"as":[75],"disease":[76],"status,":[77],"the":[78,133,149,202],"\u201ctoxicity\u201d":[79],"online":[81],"comments,":[82],"future":[84,240],"\u201cjob":[85],"performance\u201d":[86],"target":[90,127,225,236],"proxy":[91,136],"labels":[92,137],"readily":[95],"available":[96],"existing":[98],"datasets.":[99],"Predictive":[100],"models\u2019":[101],"reliance":[102],"simplistic":[104],"proxies":[105],"these":[107,190],"nuanced":[108],"makes":[110],"them":[111],"vulnerable":[112],"various":[114],"sources":[115,125],"bias.":[118,227],"In":[119],"paper,":[121],"we":[122,183],"identify":[123],"five":[124],"variable":[128,226,237],"bias":[129,153,238],"can":[131,170],"impact":[132],"validity":[134],"tasks.":[141,164],"We":[142,165,195,228],"develop":[143],"causal":[145],"framework":[146,169,199],"disentangle":[148],"relationship":[150],"each":[152],"clarify":[155],"which":[156],"concern":[159],"specific":[161],"demonstrate":[166],"how":[167],"our":[168,198],"be":[171],"used":[172],"articulate":[174],"implicit":[175],"assumptions":[176,191],"made":[177],"prior":[179,205],"modeling":[180],"work,":[181],"recommend":[184],"evaluation":[185],"verifying":[188],"whether":[189],"hold":[192],"practice.":[194],"then":[196],"leverage":[197],"re-examine":[201],"designs":[203],"subjects":[207],"experiments":[208],"investigate":[210],"decision-making,":[212],"finding":[213],"only":[215],"small":[217],"fraction":[218],"studies":[220],"examine":[221],"factors":[222],"related":[223],"conclude":[229],"discussing":[231],"opportunities":[232],"better":[234],"address":[235],"research.":[241]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
