{"id":"https://openalex.org/W4416148554","doi":"https://doi.org/10.1007/978-3-032-11108-1_5","title":"Towards Fair AI Systems: An Insurance Case Study to\u00a0Identify and\u00a0Mitigate Discrimination","display_name":"Towards Fair AI Systems: An Insurance Case Study to\u00a0Identify and\u00a0Mitigate Discrimination","publication_year":2025,"publication_date":"2025-11-12","ids":{"openalex":"https://openalex.org/W4416148554","doi":"https://doi.org/10.1007/978-3-032-11108-1_5"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-032-11108-1_5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-032-11108-1_5","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-032-11108-1_5.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/978-3-032-11108-1_5.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120646766","display_name":"Annabel Resch","orcid":null},"institutions":[{"id":"https://openalex.org/I145847075","display_name":"TU Wien","ror":"https://ror.org/04d836q62","country_code":"AT","type":"education","lineage":["https://openalex.org/I145847075"]}],"countries":["AT"],"is_corresponding":true,"raw_author_name":"Annabel Resch","raw_affiliation_strings":["Data Science Research Unit, TU Wien, Favoritenstra\u00dfe 9-11, 1040, Vienna, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science Research Unit, TU Wien, Favoritenstra\u00dfe 9-11, 1040, Vienna, Austria","institution_ids":["https://openalex.org/I145847075"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020665735","display_name":"Allan Hanbury","orcid":"https://orcid.org/0000-0002-7149-5843"},"institutions":[{"id":"https://openalex.org/I145847075","display_name":"TU Wien","ror":"https://ror.org/04d836q62","country_code":"AT","type":"education","lineage":["https://openalex.org/I145847075"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Allan Hanbury","raw_affiliation_strings":["Data Science Research Unit, TU Wien, Favoritenstra\u00dfe 9-11, 1040, Vienna, Austria"],"raw_orcid":"https://orcid.org/0000-0002-7149-5843","affiliations":[{"raw_affiliation_string":"Data Science Research Unit, TU Wien, Favoritenstra\u00dfe 9-11, 1040, Vienna, Austria","institution_ids":["https://openalex.org/I145847075"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5120646766"],"corresponding_institution_ids":["https://openalex.org/I145847075"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":{"value":5000,"currency":"EUR","value_usd":5392},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.59695958,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"67","last_page":"82"},"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":0.7271999716758728,"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":0.7271999716758728,"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":0.03680000081658363,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.02810000069439411,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6480000019073486},{"id":"https://openalex.org/keywords/compensation","display_name":"Compensation (psychology)","score":0.5134000182151794},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5080999732017517},{"id":"https://openalex.org/keywords/insurance-policy","display_name":"Insurance policy","score":0.5015000104904175},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.4934000074863434},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.4140999913215637},{"id":"https://openalex.org/keywords/general-insurance","display_name":"General insurance","score":0.33239999413490295}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7010999917984009},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6480000019073486},{"id":"https://openalex.org/C162118730","wikidata":"https://www.wikidata.org/wiki/Q1128453","display_name":"Actuarial science","level":1,"score":0.5169000029563904},{"id":"https://openalex.org/C2780023022","wikidata":"https://www.wikidata.org/wiki/Q1338171","display_name":"Compensation (psychology)","level":2,"score":0.5134000182151794},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5080999732017517},{"id":"https://openalex.org/C68799949","wikidata":"https://www.wikidata.org/wiki/Q977871","display_name":"Insurance policy","level":2,"score":0.5015000104904175},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.4934000074863434},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4390000104904175},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.4140999913215637},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3871999979019165},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.3400999903678894},{"id":"https://openalex.org/C14293393","wikidata":"https://www.wikidata.org/wiki/Q2663825","display_name":"General insurance","level":3,"score":0.33239999413490295},{"id":"https://openalex.org/C29513703","wikidata":"https://www.wikidata.org/wiki/Q6398174","display_name":"Key person insurance","level":3,"score":0.30300000309944153},{"id":"https://openalex.org/C22738907","wikidata":"https://www.wikidata.org/wiki/Q3813256","display_name":"Casualty insurance","level":3,"score":0.30149999260902405},{"id":"https://openalex.org/C168042013","wikidata":"https://www.wikidata.org/wiki/Q1037642","display_name":"Insurance law","level":4,"score":0.30140000581741333},{"id":"https://openalex.org/C5891342","wikidata":"https://www.wikidata.org/wiki/Q2868302","display_name":"Property insurance","level":4,"score":0.2930000126361847},{"id":"https://openalex.org/C2779396721","wikidata":"https://www.wikidata.org/wiki/Q1184466","display_name":"Workers' compensation","level":3,"score":0.28380000591278076},{"id":"https://openalex.org/C4430244","wikidata":"https://www.wikidata.org/wiki/Q5611238","display_name":"Group insurance","level":5,"score":0.27549999952316284},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.26919999718666077},{"id":"https://openalex.org/C2983635472","wikidata":"https://www.wikidata.org/wiki/Q334911","display_name":"Health insurance","level":3,"score":0.25699999928474426},{"id":"https://openalex.org/C115672447","wikidata":"https://www.wikidata.org/wiki/Q992350","display_name":"Liability insurance","level":3,"score":0.25290000438690186}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-032-11108-1_5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-032-11108-1_5","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-032-11108-1_5.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.1007/978-3-032-11108-1_5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-032-11108-1_5","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-032-11108-1_5.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416148554.pdf","grobid_xml":"https://content.openalex.org/works/W4416148554.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W1961345416","https://openalex.org/W2100960835","https://openalex.org/W2918300080","https://openalex.org/W2949676527","https://openalex.org/W2950068534","https://openalex.org/W3014590323","https://openalex.org/W3047533667","https://openalex.org/W3139339864","https://openalex.org/W3181414820","https://openalex.org/W3206660074","https://openalex.org/W4210736086","https://openalex.org/W4214835294","https://openalex.org/W4220760463","https://openalex.org/W4288758404","https://openalex.org/W4311773331","https://openalex.org/W4379928685","https://openalex.org/W4394783307","https://openalex.org/W4399365109","https://openalex.org/W4402641202","https://openalex.org/W4404351522","https://openalex.org/W4407237133"],"related_works":[],"abstract_inverted_index":{"We":[0],"investigate":[1],"potential":[2],"gender-based":[3],"discrimination":[4,94],"in":[5,19,37],"a":[6,50,77,113],"real-world":[7],"insurance":[8,38,61,81,87],"machine":[9],"learning":[10],"model":[11,56],"designed":[12],"to":[13,17,70,99,115],"identify":[14],"claims":[15,82],"likely":[16],"\u201cexplode\u201d":[18],"compensation":[20],"costs.":[21],"With":[22],"the":[23],"EU":[24],"AI":[25],"Act":[26],"and":[27,67],"Austrian":[28,60,86],"legal":[29],"frameworks":[30],"requiring":[31],"non-discriminatory":[32],"algorithmic":[33],"systems,":[34],"ensuring":[35],"fairness":[36,107],"claim":[39],"prediction":[40],"models":[41],"has":[42],"become":[43],"critically":[44],"important.":[45],"The":[46,89],"research":[47],"examines":[48],"whether":[49],"Light":[51],"Gradient":[52],"Boosting":[53],"Machine":[54],"(LGBM)":[55],"used":[57],"by":[58,84],"an":[59,85],"company":[62],"exhibits":[63],"gender":[64],"discriminatory":[65],"behavior":[66],"explores":[68],"methods":[69,104],"mitigate":[71],"such":[72],"bias.":[73],"This":[74],"study":[75],"analyzed":[76],"dataset":[78],"of":[79],"450,000":[80],"provided":[83],"company.":[88],"baseline":[90],"analysis":[91],"revealed":[92],"significant":[93],"against":[95],"female":[96],"claimants":[97],"compared":[98],"male":[100],"claimants.":[101],"While":[102],"mitigation":[103],"successfully":[105],"improved":[106],"metrics,":[108],"these":[109],"improvements":[110],"came":[111],"at":[112],"cost":[114],"predictive":[116],"performance.":[117]},"counts_by_year":[],"updated_date":"2026-03-13T14:20:09.374765","created_date":"2025-11-12T00:00:00"}
