{"id":"https://openalex.org/W7136391360","doi":"https://doi.org/10.48550/arxiv.2603.12935","title":"Can Fairness Be Prompted? Prompt-Based Debiasing Strategies in High-Stakes Recommendations","display_name":"Can Fairness Be Prompted? Prompt-Based Debiasing Strategies in High-Stakes Recommendations","publication_year":2026,"publication_date":"2026-03-13","ids":{"openalex":"https://openalex.org/W7136391360","doi":"https://doi.org/10.48550/arxiv.2603.12935"},"language":"en","primary_location":{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/64642b1c-c8a6-4ce5-835b-0b70e8ad0a06","is_oa":true,"landing_page_url":"https://researchprofiles.ku.dk/da/publications/64642b1c-c8a6-4ce5-835b-0b70e8ad0a06","pdf_url":"https://curis.ku.dk/ws/files/543384386/Can_Fairness_Be_Prompted.pdf","source":{"id":"https://openalex.org/S4306401983","display_name":"Research at the University of Copenhagen (University of Copenhagen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I124055696","host_organization_name":"University of Copenhagen","host_organization_lineage":["https://openalex.org/I124055696"],"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":"Rotar , M , Rampisela , T V & Maistro , M 2026 ' Can Fairness Be Prompted? Prompt-Based Debiasing Strategies in High-Stakes Recommendations ' arXiv preprint . https://doi.org/10.48550/arXiv.2603.12935","raw_type":"workingPaper"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://curis.ku.dk/ws/files/543384386/Can_Fairness_Be_Prompted.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129590220","display_name":"Mihaela Rotar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rotar, Mihaela","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129418509","display_name":"Theresia Veronika Rampisela","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rampisela, Theresia Veronika","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129623372","display_name":"Maria Maistro","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maistro, Maria","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.2782999873161316,"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":0.2782999873161316,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.1460999995470047,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.07670000195503235,"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/debiasing","display_name":"Debiasing","score":0.9993000030517578},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.2802000045776367},{"id":"https://openalex.org/keywords/cognitive-bias","display_name":"Cognitive bias","score":0.22349999845027924},{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.2214999943971634}],"concepts":[{"id":"https://openalex.org/C2779458634","wikidata":"https://www.wikidata.org/wiki/Q24963715","display_name":"Debiasing","level":2,"score":0.9993000030517578},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6743999719619751},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.4083999991416931},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.35199999809265137},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.3158999979496002},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2802000045776367},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2761000096797943},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.22439999878406525},{"id":"https://openalex.org/C189216375","wikidata":"https://www.wikidata.org/wiki/Q1127759","display_name":"Cognitive bias","level":3,"score":0.22349999845027924},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.2214999943971634}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/64642b1c-c8a6-4ce5-835b-0b70e8ad0a06","is_oa":true,"landing_page_url":"https://researchprofiles.ku.dk/da/publications/64642b1c-c8a6-4ce5-835b-0b70e8ad0a06","pdf_url":"https://curis.ku.dk/ws/files/543384386/Can_Fairness_Be_Prompted.pdf","source":{"id":"https://openalex.org/S4306401983","display_name":"Research at the University of Copenhagen (University of Copenhagen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I124055696","host_organization_name":"University of Copenhagen","host_organization_lineage":["https://openalex.org/I124055696"],"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":"Rotar , M , Rampisela , T V & Maistro , M 2026 ' Can Fairness Be Prompted? Prompt-Based Debiasing Strategies in High-Stakes Recommendations ' arXiv preprint . https://doi.org/10.48550/arXiv.2603.12935","raw_type":"workingPaper"},{"id":"doi:10.48550/arxiv.2603.12935","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12935","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/64642b1c-c8a6-4ce5-835b-0b70e8ad0a06","is_oa":true,"landing_page_url":"https://researchprofiles.ku.dk/da/publications/64642b1c-c8a6-4ce5-835b-0b70e8ad0a06","pdf_url":"https://curis.ku.dk/ws/files/543384386/Can_Fairness_Be_Prompted.pdf","source":{"id":"https://openalex.org/S4306401983","display_name":"Research at the University of Copenhagen (University of Copenhagen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I124055696","host_organization_name":"University of Copenhagen","host_organization_lineage":["https://openalex.org/I124055696"],"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":"Rotar , M , Rampisela , T V & Maistro , M 2026 ' Can Fairness Be Prompted? Prompt-Based Debiasing Strategies in High-Stakes Recommendations ' arXiv preprint . https://doi.org/10.48550/arXiv.2603.12935","raw_type":"workingPaper"},"sustainable_development_goals":[{"display_name":"Gender equality","id":"https://metadata.un.org/sdg/5","score":0.6038364768028259}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7136391360.pdf","grobid_xml":"https://content.openalex.org/works/W7136391360.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"can":[4,62,128],"infer":[5],"sensitive":[6,109],"attributes":[7],"such":[8],"as":[9,64],"gender":[10],"or":[11],"age":[12],"from":[13],"indirect":[14],"cues":[15],"like":[16],"names":[17],"and":[18,38,57,67,112],"pronouns,":[19],"potentially":[20],"biasing":[21],"recommendations.":[22],"While":[23],"several":[24],"debiasing":[25,69,89,119],"methods":[26],"exist,":[27],"they":[28],"require":[29],"access":[30],"to":[31,125,133],"the":[32,84],"LLMs'":[33],"weights,":[34],"are":[35],"computationally":[36],"costly,":[37],"cannot":[39],"be":[40,126],"used":[41],"by":[42,131],"lay":[43],"users.":[44,99],"To":[45,79],"address":[46],"this":[47,82],"gap,":[48],"we":[49],"investigate":[50],"implicit":[51],"biases":[52],"in":[53,91,145],"LLM":[54,124],"Recommenders":[55],"(LLMRecs)":[56],"explore":[58],"whether":[59],"prompt-based":[60,88],"strategies":[61,76],"serve":[63],"a":[65],"lightweight":[66],"easy-to-use":[68],"approach.":[70],"We":[71],"contribute":[72],"three":[73],"bias-aware":[74],"prompting":[75],"for":[77,98],"LLMRecs.":[78],"our":[80,117],"knowledge,":[81],"is":[83],"first":[85],"study":[86],"on":[87,95],"approaches":[90],"LLMRecs":[92],"that":[93,116],"focuses":[94],"group":[96],"fairness":[97,130],"Our":[100],"experiments":[101],"with":[102],"3":[103],"LLMs,":[104],"4":[105],"prompt":[106],"templates,":[107],"9":[108],"attribute":[110],"values,":[111],"2":[113],"datasets":[114],"show":[115],"proposed":[118],"approach,":[120],"which":[121],"instructs":[122],"an":[123],"fair,":[127],"improve":[129],"up":[132],"74%":[134],"while":[135],"retaining":[136],"comparable":[137],"effectiveness,":[138],"but":[139],"might":[140],"overpromote":[141],"specific":[142],"demographic":[143],"groups":[144],"some":[146],"cases.":[147]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-17T00:00:00"}
