{"id":"https://openalex.org/W4415428864","doi":"https://doi.org/10.3233/faia250781","title":"Measuring Explanation Quality \u2013 A Path Forward","display_name":"Measuring Explanation Quality \u2013 A Path Forward","publication_year":2025,"publication_date":"2025-10-21","ids":{"openalex":"https://openalex.org/W4415428864","doi":"https://doi.org/10.3233/faia250781"},"language":"en","primary_location":{"id":"doi:10.3233/faia250781","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia250781","pdf_url":null,"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://doi.org/10.3233/faia250781","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001095396","display_name":"Nava Tintarev","orcid":"https://orcid.org/0000-0003-1663-1627"},"institutions":[{"id":"https://openalex.org/I34352273","display_name":"Maastricht University","ror":"https://ror.org/02jz4aj89","country_code":"NL","type":"education","lineage":["https://openalex.org/I34352273"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Nava Tintarev","raw_affiliation_strings":["Department of Advanced Computing Sciences, Maastricht University, the Netherlands"],"affiliations":[{"raw_affiliation_string":"Department of Advanced Computing Sciences, Maastricht University, the Netherlands","institution_ids":["https://openalex.org/I34352273"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5001095396"],"corresponding_institution_ids":["https://openalex.org/I34352273"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.50900491,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T10215","display_name":"Semantic Web and Ontologies","score":0.439300000667572,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.439300000667572,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.4253999888896942,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/constructive","display_name":"Constructive","score":0.673799991607666},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.6590999960899353},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6118000149726868},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5820000171661377},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4672999978065491},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4555000066757202},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.42910000681877136}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7404000163078308},{"id":"https://openalex.org/C2778701210","wikidata":"https://www.wikidata.org/wiki/Q28130034","display_name":"Constructive","level":3,"score":0.673799991607666},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.6590999960899353},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6118000149726868},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5820000171661377},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5730000138282776},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5012999773025513},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4672999978065491},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4555000066757202},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.42910000681877136},{"id":"https://openalex.org/C58328972","wikidata":"https://www.wikidata.org/wiki/Q184609","display_name":"Expert system","level":2,"score":0.3774999976158142},{"id":"https://openalex.org/C173366509","wikidata":"https://www.wikidata.org/wiki/Q206829","display_name":"Reductionism","level":2,"score":0.3553999960422516},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.34049999713897705},{"id":"https://openalex.org/C2779351106","wikidata":"https://www.wikidata.org/wiki/Q24965456","display_name":"Decision quality","level":3,"score":0.3147999942302704},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.310699999332428},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2953999936580658},{"id":"https://openalex.org/C105002631","wikidata":"https://www.wikidata.org/wiki/Q4833645","display_name":"Subject-matter expert","level":3,"score":0.27570000290870667},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.27309998869895935},{"id":"https://openalex.org/C45983554","wikidata":"https://www.wikidata.org/wiki/Q3412851","display_name":"Information quality","level":3,"score":0.2712000012397766},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.2646999955177307}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3233/faia250781","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia250781","pdf_url":null,"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"},{"id":"pmh:oai:cris.maastrichtuniversity.nl:openaire/7ce5c7d3-1ed3-4fef-8cb0-c6e3ebf84b72","is_oa":false,"landing_page_url":"https://cris.maastrichtuniversity.nl/en/publications/7ce5c7d3-1ed3-4fef-8cb0-c6e3ebf84b72","pdf_url":null,"source":{"id":"https://openalex.org/S4306402616","display_name":"Research Publications (Maastricht University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I34352273","host_organization_name":"Maastricht University","host_organization_lineage":["https://openalex.org/I34352273"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Tintarev, N 2025, Measuring Explanation Quality - A Path Forward. in I Lynce, N Murano, M Vallati, S Villata, F Chesani, M Milano, A Omicini & M Dastani (eds), ECAI 2025 - 28th European Conference on Artificial Intelligence, including 14th Conference on Prestigious Applications of Intelligent Systems, PAIS 2025 - Proceedings. vol. 413, IOS Press, Frontiers in Artificial Intelligence and Applications, vol. 413, pp. 22-29, 28th European Conference on Artificial Intelligence, ECAI 2025, including 14th Conference on Prestigious Applications of Intelligent Systems, PAIS 2025, Bologna, Italy, 25/10/25. https://doi.org/10.3233/FAIA250781","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.3233/faia250781","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia250781","pdf_url":null,"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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0,17,126],"this":[1,84,132],"paper,":[2],"I":[3,20,80,143],"describe":[4],"lessons":[5],"learned":[6],"in":[7,68],"nearly":[8],"20":[9],"years":[10],"of":[11,56,100,151],"evaluating":[12,148],"explanation":[13,26,57],"interfaces":[14],"with":[15],"people.":[16],"my":[18],"work,":[19],"have":[21],"observed":[22],"that":[23,83],"tailoring":[24],"the":[25,28,98,119,149],"to":[27,118],"user":[29],"(e.g.,":[30,39,47,59],"a":[31,35,128,135],"domain":[32],"expert":[33],"or":[34,42,45,62],"layperson)":[36],"and":[37,77,92,112,134,138],"task":[38],"decision":[40],"support":[41],"model":[43],"improvement),":[44],"context":[46],"under":[48],"time":[49],"pressure)":[50],"is":[51,85],"necessary":[52],"for":[53,88,121,147],"meaningful":[54],"assessment":[55],"quality":[58,150],"correct":[60],"decisions":[61],"better":[63],"understanding).":[64],"Learning":[65],"from":[66,110],"trends":[67],"empirical":[69],"research":[70],"methods":[71],"(natural":[72],"language":[73],"processing,":[74],"information":[75],"retrieval,":[76],"machine":[78,93],"learning),":[79],"further":[81],"argue":[82],"an":[86],"issue":[87],"both":[89],"human-computer":[90],"interaction":[91],"learning.":[94],"Real-world":[95],"factors":[96],"influencing":[97],"performance":[99],"systems":[101],"are":[102,124],"at":[103,113],"best":[104],"implicitly":[105],"encoded":[106],"when":[107],"inferring":[108],"probabilities":[109],"observations,":[111],"worst,":[114],"no":[115],"longer":[116],"applicable":[117],"settings":[120],"which":[122],"they":[123],"used.":[125],"seeking":[127],"balanced":[129],"approach":[130],"between":[131],"reality":[133],"pragmatic,":[136],"data-driven":[137],"(by":[139],"necessity)":[140],"reductionist":[141],"approach,":[142],"make":[144],"constructive":[145],"suggestions":[146],"explainable":[152],"artificial":[153],"intelligence.":[154]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-24T00:00:00"}
