{"id":"https://openalex.org/W3010319796","doi":"https://doi.org/10.3390/info11030137","title":"A Responsible Machine Learning Workflow with Focus on Interpretable Models, Post-hoc Explanation, and Discrimination Testing","display_name":"A Responsible Machine Learning Workflow with Focus on Interpretable Models, Post-hoc Explanation, and Discrimination Testing","publication_year":2020,"publication_date":"2020-02-29","ids":{"openalex":"https://openalex.org/W3010319796","doi":"https://doi.org/10.3390/info11030137","mag":"3010319796"},"language":"en","primary_location":{"id":"doi:10.3390/info11030137","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info11030137","pdf_url":"https://www.mdpi.com/2078-2489/11/3/137/pdf","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2078-2489/11/3/137/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078324452","display_name":"Navdeep Gill","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Navdeep Gill","raw_affiliation_strings":["H2O.ai, Mountain View, CA 94043, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"H2O.ai, Mountain View, CA 94043, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030443550","display_name":"Patrick Hall","orcid":null},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]},{"id":"https://openalex.org/I4210133369","display_name":"Decision Sciences (United States)","ror":"https://ror.org/03gcvf773","country_code":"US","type":"company","lineage":["https://openalex.org/I4210133369"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Patrick Hall","raw_affiliation_strings":["Department of Decision Sciences, The George Washington University, Washington, DC 20052, USA","H2O.ai, Mountain View, CA 94043, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Decision Sciences, The George Washington University, Washington, DC 20052, USA","institution_ids":["https://openalex.org/I193531525","https://openalex.org/I4210133369"]},{"raw_affiliation_string":"H2O.ai, Mountain View, CA 94043, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055398306","display_name":"Kim Montgomery","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim Montgomery","raw_affiliation_strings":["H2O.ai, Mountain View, CA 94043, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"H2O.ai, Mountain View, CA 94043, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064475505","display_name":"Nicholas Schmidt","orcid":"https://orcid.org/0000-0002-8340-8145"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Nicholas Schmidt","raw_affiliation_strings":["BLDS, LLC, Philadelphia, PA 19103, USA"],"raw_orcid":"https://orcid.org/0000-0002-8340-8145","affiliations":[{"raw_affiliation_string":"BLDS, LLC, Philadelphia, PA 19103, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5030443550","https://openalex.org/A5064475505"],"corresponding_institution_ids":["https://openalex.org/I193531525","https://openalex.org/I4210133369"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":2.9919,"has_fulltext":true,"cited_by_count":34,"citation_normalized_percentile":{"value":0.9277517,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"11","issue":"3","first_page":"137","last_page":"137"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9988999962806702,"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":0.9988999962806702,"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":0.9980999827384949,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.9810000061988831,"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/interpretability","display_name":"Interpretability","score":0.9377834796905518},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7850829362869263},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7492451071739197},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.724645733833313},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.6876258850097656},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6714480519294739},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.45821303129196167},{"id":"https://openalex.org/keywords/transparency","display_name":"Transparency (behavior)","score":0.4456748962402344}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9377834796905518},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7850829362869263},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7492451071739197},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.724645733833313},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.6876258850097656},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6714480519294739},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.45821303129196167},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.4456748962402344},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/info11030137","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info11030137","pdf_url":"https://www.mdpi.com/2078-2489/11/3/137/pdf","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:eb7d91559a2d4960b0632f11f6324eff","is_oa":true,"landing_page_url":"https://doaj.org/article/eb7d91559a2d4960b0632f11f6324eff","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Information, Vol 11, Iss 3, p 137 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2078-2489/11/3/137/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/info11030137","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Information","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/info11030137","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info11030137","pdf_url":"https://www.mdpi.com/2078-2489/11/3/137/pdf","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.49000000953674316},{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.4699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3010319796.pdf","grobid_xml":"https://content.openalex.org/works/W3010319796.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W104184427","https://openalex.org/W168150807","https://openalex.org/W1678356000","https://openalex.org/W1979769549","https://openalex.org/W2014352947","https://openalex.org/W2037557484","https://openalex.org/W2046945713","https://openalex.org/W2048231652","https://openalex.org/W2100960835","https://openalex.org/W2102201073","https://openalex.org/W2116984840","https://openalex.org/W2125847307","https://openalex.org/W2125908420","https://openalex.org/W2137406659","https://openalex.org/W2138243089","https://openalex.org/W2162670686","https://openalex.org/W2164616133","https://openalex.org/W2248060815","https://openalex.org/W2461943168","https://openalex.org/W2473418344","https://openalex.org/W2535690855","https://openalex.org/W2618851150","https://openalex.org/W2752257308","https://openalex.org/W2785760873","https://openalex.org/W2787070805","https://openalex.org/W2788481061","https://openalex.org/W2811104224","https://openalex.org/W2896069478","https://openalex.org/W2897042519","https://openalex.org/W2953148557","https://openalex.org/W2963116854","https://openalex.org/W2963125461","https://openalex.org/W2963917042","https://openalex.org/W2967730222","https://openalex.org/W2970863760","https://openalex.org/W2971048680","https://openalex.org/W2982735895","https://openalex.org/W3005086430","https://openalex.org/W3100279624","https://openalex.org/W3125240708","https://openalex.org/W3128452405","https://openalex.org/W4206519735","https://openalex.org/W4289258088","https://openalex.org/W6675321329","https://openalex.org/W6684072790","https://openalex.org/W6690771958","https://openalex.org/W6755007966","https://openalex.org/W6756046586","https://openalex.org/W6769370004","https://openalex.org/W6790587931"],"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/W4312407344","https://openalex.org/W2894289927"],"abstract_inverted_index":{"This":[0],"manuscript":[1],"outlines":[2],"a":[3,43,153],"viable":[4],"approach":[5],"for":[6,13,48,106,156],"training":[7],"and":[8,26,39,56,64,87,91,94,109,125,141,164,166],"evaluating":[9],"machine":[10,157],"learning":[11,45,158],"systems":[12],"high-stakes,":[14],"human-centered,":[15],"or":[16],"regulated":[17],"applications":[18,159],"using":[19,78,114],"common":[20],"Python":[21],"programming":[22],"tools.":[23],"The":[24,99],"accuracy":[25,163],"intrinsic":[27],"interpretability":[28,165],"of":[29,32,68,84,112,170],"two":[30],"types":[31,111],"constrained":[33,74,100],"models,":[34,138],"monotonic":[35],"gradient":[36],"boosting":[37],"machines":[38],"explainable":[40],"neural":[41],"networks,":[42],"deep":[44],"architecture":[46],"well-suited":[47],"structured":[49],"data,":[50],"are":[51,76,103],"assessed":[52],"on":[53],"simulated":[54],"data":[55],"publicly":[57],"available":[58],"mortgage":[59],"data.":[60],"For":[61],"maximum":[62],"transparency":[63],"the":[65,73],"potential":[66],"generation":[67],"personalized":[69],"adverse":[70,120],"action":[71],"notices,":[72],"models":[75],"analyzed":[77],"post-hoc":[79,139],"explanation":[80],"techniques":[81],"including":[82],"plots":[83],"partial":[85],"dependence":[86],"individual":[88],"conditional":[89],"expectation":[90],"with":[92,116,130,144],"global":[93],"local":[95],"Shapley":[96],"feature":[97],"importance.":[98],"model":[101],"predictions":[102],"also":[104],"tested":[105],"disparate":[107],"impact":[108,121],"other":[110],"discrimination":[113,142],"measures":[115],"long-standing":[117],"legal":[118],"precedents,":[119],"ratio,":[122],"marginal":[123],"effect,":[124],"standardized":[126],"mean":[127],"difference,":[128],"along":[129],"straightforward":[131],"group":[132],"fairness":[133],"measures.":[134],"By":[135],"combining":[136],"interpretable":[137],"explanations,":[140],"testing":[143],"accessible":[145],"software":[146],"tools,":[147],"this":[148],"text":[149],"aims":[150],"to":[151],"provide":[152],"template":[154],"workflow":[155],"that":[160,167],"require":[161],"high":[162],"mitigate":[168],"risks":[169],"discrimination.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":2}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
