{"id":"https://openalex.org/W2965211237","doi":"https://doi.org/10.1145/3292500.3332281","title":"Explainable AI in Industry","display_name":"Explainable AI in Industry","publication_year":2019,"publication_date":"2019-07-25","ids":{"openalex":"https://openalex.org/W2965211237","doi":"https://doi.org/10.1145/3292500.3332281","mag":"2965211237"},"language":"en","primary_location":{"id":"doi:10.1145/3292500.3332281","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3332281","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & 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/A5084589814","display_name":"Krishna Gade","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Krishna Gade","raw_affiliation_strings":["Fiddler Labs, Mountain View, CA, USA"],"affiliations":[{"raw_affiliation_string":"Fiddler Labs, Mountain View, CA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071195197","display_name":"Sahin Cem Geyik","orcid":null},"institutions":[{"id":"https://openalex.org/I1316064682","display_name":"LinkedIn (United States)","ror":"https://ror.org/02fyxhe35","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I1316064682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sahin Cem Geyik","raw_affiliation_strings":["LinkedIn, Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"LinkedIn, Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002843568","display_name":"Krishnaram Kenthapadi","orcid":"https://orcid.org/0000-0003-1237-087X"},"institutions":[{"id":"https://openalex.org/I1316064682","display_name":"LinkedIn (United States)","ror":"https://ror.org/02fyxhe35","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I1316064682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Krishnaram Kenthapadi","raw_affiliation_strings":["LinkedIn, Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"LinkedIn, Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043464710","display_name":"Varun Mithal","orcid":"https://orcid.org/0000-0003-2662-6936"},"institutions":[{"id":"https://openalex.org/I1316064682","display_name":"LinkedIn (United States)","ror":"https://ror.org/02fyxhe35","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I1316064682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Varun Mithal","raw_affiliation_strings":["LinkedIn, Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"LinkedIn, Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069391199","display_name":"Ankur Taly","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ankur Taly","raw_affiliation_strings":["Fiddler Labs, Mountain View, CA, USA"],"affiliations":[{"raw_affiliation_string":"Fiddler Labs, Mountain View, CA, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5084589814"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.5264,"has_fulltext":false,"cited_by_count":132,"citation_normalized_percentile":{"value":0.98059093,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3203","last_page":"3204"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9987999796867371,"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"}},"topics":[{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9987999796867371,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9320999979972839,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9253000020980835,"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/interpretability","display_name":"Interpretability","score":0.869507908821106},{"id":"https://openalex.org/keywords/transparency","display_name":"Transparency (behavior)","score":0.7251659035682678},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.518497109413147},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5102097988128662},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.4720343351364136},{"id":"https://openalex.org/keywords/openness-to-experience","display_name":"Openness to experience","score":0.4375913739204407},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3717110753059387},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.3349645137786865},{"id":"https://openalex.org/keywords/knowledge-management","display_name":"Knowledge management","score":0.32678231596946716},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.2803163528442383},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.1978936493396759},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.18553176522254944},{"id":"https://openalex.org/keywords/economic-growth","display_name":"Economic growth","score":0.10699179768562317}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.869507908821106},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.7251659035682678},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.518497109413147},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5102097988128662},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.4720343351364136},{"id":"https://openalex.org/C84976871","wikidata":"https://www.wikidata.org/wiki/Q2015673","display_name":"Openness to experience","level":2,"score":0.4375913739204407},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3717110753059387},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.3349645137786865},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.32678231596946716},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2803163528442383},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.1978936493396759},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.18553176522254944},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.10699179768562317},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3292500.3332281","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3332281","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1996796871","https://openalex.org/W2046945713","https://openalex.org/W2149033360","https://openalex.org/W2282821441","https://openalex.org/W2420245003","https://openalex.org/W2594633041","https://openalex.org/W2724999822","https://openalex.org/W2788403449","https://openalex.org/W2809925683","https://openalex.org/W2888487581","https://openalex.org/W2903566196","https://openalex.org/W2932771740","https://openalex.org/W2941829268","https://openalex.org/W2942444880","https://openalex.org/W2944675392","https://openalex.org/W2951885001","https://openalex.org/W2962790223","https://openalex.org/W3043146651","https://openalex.org/W3093393055"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W4390569940","https://openalex.org/W2888392564","https://openalex.org/W4361193272","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W2806259446","https://openalex.org/W2963326959","https://openalex.org/W4361225185","https://openalex.org/W2999650543"],"abstract_inverted_index":{"Artificial":[0],"Intelligence":[1],"is":[2,75],"increasingly":[3],"playing":[4],"an":[5],"integral":[6],"role":[7,43],"in":[8,20,48,60,86],"determining":[9],"our":[10],"day-to-day":[11],"experiences.":[12],"Moreover,":[13],"with":[14,104],"proliferation":[15],"of":[16,37,83,113],"AI":[17,38,46,84],"based":[18],"solutions":[19],"areas":[21],"such":[22,94,108],"as":[23,95,109],"hiring,":[24],"lending,":[25],"criminal":[26],"justice,":[27],"healthcare,":[28],"and":[29,34,63,69,81,92,97,100,116],"education,":[30],"the":[31],"resulting":[32],"personal":[33],"professional":[35],"implications":[36,107],"are":[39],"far-reaching.":[40],"The":[41],"dominant":[42],"played":[44],"by":[45],"models":[47],"these":[49,61],"domains":[50,89],"has":[51],"led":[52],"to":[53],"a":[54,64,76],"growing":[55],"concern":[56],"regarding":[57],"potential":[58],"bias":[59],"models,":[62],"demand":[65],"for":[66,78],"model":[67,73],"transparency":[68],"interpretability.":[70],"In":[71],"addition,":[72],"explainability":[74],"prerequisite":[77],"building":[79],"trust":[80],"adoption":[82],"systems":[85],"high":[87],"stakes":[88],"requiring":[90],"reliability":[91],"safety":[93],"healthcare":[96],"automated":[98],"transportation,":[99],"critical":[101],"industrial":[102],"applications":[103],"significant":[105],"economic":[106],"predictive":[110],"maintenance,":[111],"exploration":[112],"natural":[114],"resources,":[115],"climate":[117],"change":[118],"modeling.":[119]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":22},{"year":2023,"cited_by_count":30},{"year":2022,"cited_by_count":34},{"year":2021,"cited_by_count":15},{"year":2020,"cited_by_count":10}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}