{"id":"https://openalex.org/W4403488547","doi":"https://doi.org/10.3233/faia240569","title":"A Comprehensive Sustainable Framework for Machine Learning and Artificial Intelligence","display_name":"A Comprehensive Sustainable Framework for Machine Learning and Artificial Intelligence","publication_year":2024,"publication_date":"2024-10-16","ids":{"openalex":"https://openalex.org/W4403488547","doi":"https://doi.org/10.3233/faia240569"},"language":"en","primary_location":{"id":"doi:10.3233/faia240569","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia240569","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240569","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240569","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088888665","display_name":"Roberto Pagliari","orcid":null},"institutions":[{"id":"https://openalex.org/I1305429384","display_name":"JPMorgan Chase & Co (United States)","ror":"https://ror.org/01x3kkr08","country_code":"US","type":"company","lineage":["https://openalex.org/I1305429384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Roberto Pagliari","raw_affiliation_strings":["J.P. Morgan and Chase"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"J.P. Morgan and Chase","institution_ids":["https://openalex.org/I1305429384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037808394","display_name":"Peter Hill","orcid":"https://orcid.org/0000-0002-2969-2376"},"institutions":[{"id":"https://openalex.org/I1305429384","display_name":"JPMorgan Chase & Co (United States)","ror":"https://ror.org/01x3kkr08","country_code":"US","type":"company","lineage":["https://openalex.org/I1305429384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peter Hill","raw_affiliation_strings":["J.P. Morgan and Chase"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"J.P. Morgan and Chase","institution_ids":["https://openalex.org/I1305429384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104155245","display_name":"Po-Yu Chen","orcid":"https://orcid.org/0000-0002-8568-8988"},"institutions":[{"id":"https://openalex.org/I1305429384","display_name":"JPMorgan Chase & Co (United States)","ror":"https://ror.org/01x3kkr08","country_code":"US","type":"company","lineage":["https://openalex.org/I1305429384"]},{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Po-Yu Chen","raw_affiliation_strings":["Imperial College London","J.P. Morgan and Chase"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imperial College London","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"J.P. Morgan and Chase","institution_ids":["https://openalex.org/I1305429384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107077604","display_name":"Maciej Dabrowny","orcid":null},"institutions":[{"id":"https://openalex.org/I1305429384","display_name":"JPMorgan Chase & Co (United States)","ror":"https://ror.org/01x3kkr08","country_code":"US","type":"company","lineage":["https://openalex.org/I1305429384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maciej Dabrowny","raw_affiliation_strings":["J.P. Morgan and Chase"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"J.P. Morgan and Chase","institution_ids":["https://openalex.org/I1305429384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108982125","display_name":"Tingsheng Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I1305429384","display_name":"JPMorgan Chase & Co (United States)","ror":"https://ror.org/01x3kkr08","country_code":"US","type":"company","lineage":["https://openalex.org/I1305429384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tingsheng Tan","raw_affiliation_strings":["J.P. Morgan and Chase"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"J.P. Morgan and Chase","institution_ids":["https://openalex.org/I1305429384"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036314694","display_name":"Francois Buet-Golfouse","orcid":"https://orcid.org/0000-0002-2164-7087"},"institutions":[{"id":"https://openalex.org/I4210104812","display_name":"Barclays (United Kingdom)","ror":"https://ror.org/01few5909","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210104812"]},{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Francois Buet-Golfouse","raw_affiliation_strings":["Barclays","University College London"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Barclays","institution_ids":["https://openalex.org/I4210104812"]},{"raw_affiliation_string":"University College London","institution_ids":["https://openalex.org/I45129253"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8122,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.87613573,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11891","display_name":"Big Data and Business Intelligence","score":0.4586000144481659,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11891","display_name":"Big Data and Business Intelligence","score":0.4586000144481659,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5956475734710693},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5325849056243896},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37258389592170715}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5956475734710693},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5325849056243896},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37258389592170715}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia240569","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia240569","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240569","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/faia240569","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia240569","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240569","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"sustainable_development_goals":[{"display_name":"Responsible consumption and production","id":"https://metadata.un.org/sdg/12","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403488547.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"In":[0],"many":[1],"applications,":[2],"regulations":[3],"or":[4,77],"best":[5],"practices":[6],"often":[7],"lead":[8],"to":[9,16,86,132,153],"specific":[10],"requirements":[11,168],"in":[12,30,36],"machine":[13],"learning":[14],"relating":[15],"four":[17,135],"key":[18,136],"pillars:":[19],"fairness,":[20],"privacy,":[21],"interpretability":[22],"and":[23,112,144,163,184,195],"greenhouse":[24],"gas":[25],"emissions.":[26],"These":[27],"all":[28,60],"sit":[29],"the":[31,61,70,117,120,124,134,155,170,174,177,186],"broader":[32],"context":[33],"of":[34,55,69,116,166,192],"sustainability":[35],"AI,":[37],"an":[38,190],"emerging":[39],"practical":[40],"AI":[41,105],"topic.":[42],"However,":[43],"although":[44],"these":[45,56],"pillars":[46,71,137],"have":[47,58],"been":[48],"individually":[49],"addressed":[50],"by":[51],"past":[52],"literature,":[53],"none":[54],"works":[57],"considered":[59],"pillars.":[62,121,171],"There":[63],"are":[64],"inherent":[65],"trade-offs":[66,175],"between":[67,119],"each":[68],"(for":[72],"example,":[73],"utility":[74,78],"vs":[75,79],"fairness":[76],"privacy),":[80],"making":[81],"it":[82,202],"even":[83],"more":[84],"important":[85],"consider":[87],"them":[88],"together.":[89],"This":[90,149],"paper":[91],"outlines":[92],"a":[93,103,113,129,139,160,164],"new":[94],"framework":[95],"for":[96,109,159],"Sustainable":[97],"Machine":[98],"Learning.":[99],"It":[100],"proposes":[101],"FPIG,":[102],"general":[104],"pipeline":[106],"that":[107],"allows":[108,151],"simultaneous":[110],"consideration":[111],"better":[114],"understanding":[115],"tradeoffs":[118],"Based":[122],"on":[123,169,180],"FPIG":[125,178],"framework,":[126],"we":[127],"propose":[128],"meta-learning":[130,187],"algorithm":[131,150],"estimate":[133],"given":[138,161],"dataset":[140,162],"summary,":[141],"model":[142,147,157,179,205],"architecture,":[143],"hyperparameters":[145],"before":[146],"training.":[148],"users":[152],"select":[154],"optimal":[156],"architecture":[158],"set":[165],"user":[167],"We":[172],"illustrate":[173],"under":[176],"three":[181],"classical":[182],"datasets":[183,194],"demonstrate":[185],"approach":[188],"with":[189,197],"example":[191],"real-world":[193],"models":[196],"different":[198],"interpretability,":[199],"showcasing":[200],"how":[201],"can":[203],"aid":[204],"selection.":[206]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
