A practical exploration of the convergence of Case-Based Reasoning and Explainable Artificial Intelligence

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dc.contributor.authorPradeep, Preejaen
dc.contributor.authorCaro-Martínez, Martaen
dc.contributor.authorWijekoon, Anjanaen
dc.contributor.funderCHIST-ERAen
dc.contributor.funderIrish Research Councilen
dc.contributor.funderScience Foundation Irelanden
dc.contributor.funderEuropean Regional Development Funden
dc.contributor.funderEngineering and Physical Sciences Research Councilen
dc.contributor.funderAgencia Estatal de Investigaciónen
dc.contributor.funderMinisterio de Ciencia e Innovaciónen
dc.date.accessioned2024-09-03T14:07:33Z
dc.date.available2024-09-03T14:07:33Z
dc.date.issued2024-07-14en
dc.description.abstractAs Artificial Intelligence (AI) systems become increasingly complex, ensuring their decisions are transparent and understandable to users has become paramount. This paper explores the integration of Case-Based Reasoning (CBR) with Explainable Artificial Intelligence (XAI) through a real-world example, which presents an innovative CBR-driven XAI platform. This study investigates how CBR, a method that solves new problems based on the solutions of similar past problems, can be harnessed to enhance the explainability of AI systems. Though the literature has few works on the synergy between CBR and XAI, exploring the principles for developing a CBR-driven XAI platform is necessary. This exploration outlines the key features and functionalities, examines the alignment of CBR principles with XAI goals to make AI reasoning more transparent to users, and discusses methodological strategies for integrating CBR into XAI frameworks. Through a case study of our CBR-driven XAI platform, iSee: Intelligent Sharing of Explanation Experience, we demonstrate the practical application of these principles, highlighting the enhancement of system transparency and user trust. The platform elucidates the decision-making processes of AI models and adapts to provide explanations tailored to diverse user needs. Our findings emphasize the importance of interdisciplinary approaches in AI research and the significant role CBR can play in advancing the goals of XAI.en
dc.description.sponsorshipEuropean Union (iSee project, a CHIST-ERA project financed by the European Union, which received funding for Ireland from the Irish Research Council under grant number CHIST-ERA-2019- iSee); Science Foundation Ireland (Grant number 12/RC/2289-P2 at Insight the SFI Research Centre for Data Analytics at UCC, which is co-funded under the European Regional Development Fund); Ministerio de Ciencia e Innovación, Agencia Estatal de Investigación Spain (MCIN/AEI and European Union ‘‘Next Generation EU/PRTR’’ under grant number PCI2020-120720-2); Engineering and Physical Sciences Research Council, UK (EPSRC under grant number EP/V061755/1)en
dc.description.statusPeer revieweden
dc.description.versionPublished Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationPradeep, P., Caro-Martínez, M. and Wijekoon, A. (2024) ‘A practical exploration of the convergence of Case-Based Reasoning and Explainable Artificial Intelligence’, Expert Systems with Applications, 255, 124733. Available at: https://doi.org/10.1016/j.eswa.2024.124733.en
dc.identifier.doihttps://doi.org/10.1016/j.eswa.2024.124733.en
dc.identifier.endpage12en
dc.identifier.issn0957-4174en
dc.identifier.issuedDen
dc.identifier.journaltitleExpert Systems with Applicationsen
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/16250
dc.identifier.volume255en
dc.language.isoenen
dc.publisherElsevieren
dc.relation.ispartofExpert Systems with Applicationsen
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2289/IE/INSIGHT - Irelands Big Data and Analytics Research Centre/en
dc.relation.projectinfo:eu-repo/grantAgreement/UKRI/EPSRC/EP/V061755/1/GB/iSee: Intelligent Sharing of Explanation Experience by Users for Users/en
dc.rights© 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/)en
dc.rights.urihttp://creativecommons.org/licenses/bync-nd/4.0/en
dc.subjectCase-Based Reasoningen
dc.subjectCBR-driven XAIen
dc.subjectExplainable Artificial Intelligenceen
dc.subjectHuman-understandable explanationsen
dc.subjectTrustworthy AIen
dc.titleA practical exploration of the convergence of Case-Based Reasoning and Explainable Artificial Intelligenceen
dc.typeArticle (peer-reviewed)en
oaire.citation.volume255en
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