{"id":"https://openalex.org/W4407245204","doi":"https://doi.org/10.48550/arxiv.2502.04058","title":"Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses","display_name":"Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses","publication_year":2025,"publication_date":"2025-02-06","ids":{"openalex":"https://openalex.org/W4407245204","doi":"https://doi.org/10.48550/arxiv.2502.04058"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2502.04058","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2502.04058","pdf_url":"https://arxiv.org/pdf/2502.04058","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2502.04058","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111034088","display_name":"Kiet Q. H. Vo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vo, Kiet Q. H.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051223998","display_name":"Siu Lun Chau","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chau, Siu Lun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015018035","display_name":"Masahiro Kato","orcid":"https://orcid.org/0000-0002-4855-5537"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kato, Masahiro","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100328549","display_name":"Yixin Wang","orcid":"https://orcid.org/0000-0003-4324-2408"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yixin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5116188209","display_name":"Krikamol Muandet","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Muandet, Krikamol","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/T11810","display_name":"Complex Systems and Decision Making","score":0.16619999706745148,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11810","display_name":"Complex Systems and Decision Making","score":0.16619999706745148,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/process-management","display_name":"Process management","score":0.41586506366729736},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3940768539905548},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.35803014039993286},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.3445563018321991},{"id":"https://openalex.org/keywords/knowledge-management","display_name":"Knowledge management","score":0.3318985402584076}],"concepts":[{"id":"https://openalex.org/C195094911","wikidata":"https://www.wikidata.org/wiki/Q14167904","display_name":"Process management","level":1,"score":0.41586506366729736},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3940768539905548},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.35803014039993286},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3445563018321991},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.3318985402584076}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2502.04058","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2502.04058","pdf_url":"https://arxiv.org/pdf/2502.04058","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2502.04058","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2502.04058","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:arXiv.org:2502.04058","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2502.04058","pdf_url":"https://arxiv.org/pdf/2502.04058","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2569205066","display_name":"Toward Automated Uncertainty Quantification in Causal Inference","funder_award_id":"2310831","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3335687950","display_name":"ACED: Tail-aware Generative Modeling for Inverse Discovery of Molecules","funder_award_id":"2435696","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G396568656","display_name":"Collaborative Research: ATD: Hawkes Process-Based Causal Relationship Discovery For Complex Threat Detection and Forecasting","funder_award_id":"2428059","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4406361865","display_name":"CAREER: Bringing Structure to the Unstructured: Robust Causal and Statistical Modeling of High-dimensional Unstructured Data","funder_award_id":"2440954","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8101864701","display_name":null,"funder_award_id":"N00014-23-1-2590","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G8876996369","display_name":null,"funder_award_id":"N00014","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320333858","display_name":"Michigan Institute for Data Science, University of Michigan","ror":null},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4407245204.pdf","grobid_xml":"https://content.openalex.org/works/W4407245204.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"We":[0],"study":[1],"explanation":[2,118,181],"design":[3],"in":[4,17,93,156,166],"algorithmic":[5,33],"decision":[6,23],"making":[7],"with":[8,135],"strategic":[9,99],"agents,":[10,100],"individuals":[11],"who":[12],"may":[13],"modify":[14],"their":[15,81,104,197],"inputs":[16],"response":[18],"to":[19,36,71,125,195],"explanations":[20,92,127,145],"of":[21],"a":[22,94,122,136,170,206],"maker's":[24],"(DM's)":[25],"predictive":[26,110,178,199],"model.":[27],"As":[28],"the":[29,46,73,153,177,193],"demand":[30],"for":[31,149,210],"transparent":[32],"systems":[34],"continues":[35],"grow,":[37],"most":[38],"prior":[39],"work":[40],"assumes":[41],"full":[42],"model":[43,61,74,179,215],"disclosure":[44,67],"as":[45,54],"default":[47],"solution.":[48],"In":[49,112],"practice,":[50,167],"however,":[51],"DMs":[52,89],"such":[53],"financial":[55],"institutions":[56],"typically":[57],"disclose":[58],"only":[59],"partial":[60,66,214],"information":[62,157],"via":[63],"explanations.":[64],"Such":[65],"can":[68,90,163],"lead":[69],"agents":[70,130],"misinterpret":[72],"and":[75,120,180,186,212],"take":[76],"actions":[77],"that":[78,96,142,174,190],"unknowingly":[79],"harm":[80],"utility.":[82],"A":[83],"key":[84],"open":[85],"question":[86],"is":[87],"how":[88,161],"communicate":[91],"way":[95],"avoids":[97],"harming":[98],"while":[101,201],"still":[102],"supporting":[103],"own":[105],"decision-making":[106],"goals,":[107],"e.g.,":[108],"minimising":[109],"error.":[111],"this":[113],"work,":[114],"we":[115,140,168],"analyse":[116],"well-known":[117],"methods,":[119],"establish":[121],"necessary":[123],"condition":[124],"prevent":[126],"from":[128],"misleading":[129],"into":[131],"self-harming":[132],"actions.":[133],"Moreover,":[134],"conditional":[137],"homogeneity":[138],"assumption,":[139],"prove":[141],"action":[143],"recommendation-based":[144],"(ARexes)":[146],"are":[147],"sufficient":[148],"non-harmful":[150],"responses,":[151],"mirroring":[152],"revelation":[154],"principle":[155],"design.":[158],"To":[159],"demonstrate":[160],"ARexes":[162,191],"be":[164],"operationalised":[165],"propose":[169],"simple":[171],"learning":[172],"procedure":[173],"jointly":[175],"optimises":[176],"policy.":[182],"Experiments":[183],"on":[184],"synthetic":[185],"real-world":[187],"tasks":[188],"show":[189],"allow":[192],"DM":[194],"optimise":[196],"model's":[198],"performance":[200],"preserving":[202],"agents'":[203],"utility,":[204],"offering":[205],"more":[207],"refined":[208],"strategy":[209],"safe":[211],"effective":[213],"disclosure.":[216]},"counts_by_year":[],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-02-08T00:00:00"}