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Explainable AI in education: fostering human oversight and shared responsibility

2025Text Open access
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dc.contributor.authorBellas, Francisco
dc.contributor.authorOoege, Jeroen
dc.contributor.authorRoddeck, Lezel
dc.contributor.authorRashheed, Hasan Abu
dc.contributor.authorSkenduli, Marjana Prifti
dc.contributor.authorMasdoum, Florent
dc.contributor.authorZainuddin, Nurkhamimi bin
dc.contributor.authorGori, Jessica Niewint
dc.contributor.authorCostello, Eamon
dc.contributor.authorKralj, Lidija
dc.contributor.authorDcosta, Deepti Teresa
dc.contributor.authorKatsamori, Dora
dc.contributor.authorNeethling, Darren
dc.contributor.authorMaat, Sarah ter
dc.contributor.authorSaurabh, Roy
dc.contributor.authorAlasgarova, Rena
dc.contributor.authorRadaelli, Elena
dc.contributor.authorStamatescu, Ana
dc.contributor.authorBlazic, Arjana
dc.contributor.authorAttwell, Graham
dc.contributor.authorTamoliūnė, Giedrė
dc.contributor.authorTziampazi, Theodora
dc.contributor.authorKreinsen, Moritz
dc.contributor.authorAlves Lopes, António
dc.contributor.authorDieguez, Jose Vinas
dc.contributor.authorObae, Cristina
dc.date.accessioned2025-04-30T09:09:59Z
dc.date.available2025-04-30T09:09:59Z
dc.date.issued2025
dc.description.abstractExplainable artificial intelligence (XAI) is a sub-field of artificial intelligence (AI), which aims to provide explanations about the reasons why an AI-based system takes a decision or provides an output (TechDispatch, 2023). The search for meaningful explanations is not new in the field of AI, but it has been mainly a technical issue for developers who were looking for reliability in the results obtained by their AI systems, so they could be accepted by end users of specific areas (Ali et al, 2023). The great advance of AI technology in the last years has turned these systems into general-purpose digital tools, and new considerations have arisen in this realm. In terms of ethical AI, the Ethics guidelines for trustworthy AI published in 2019 by the High-Level Expert Group on AI of the European Commission established seven key requirements for trustworthy AI: (1) human agency and oversight, (2) technical robustness and safety, (3) privacy and data governance, (4) transparency, (5) diversity, non-discrimination and fairness, (6) societal and environmental wellbeing, and (7) accountability.por
dc.identifier.urihttp://hdl.handle.net/10400.26/57757
dc.language.isoeng
dc.peerreviewedyes
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectArtificial intelligence
dc.subjectEducation
dc.subjectDigital education
dc.subjectEuropean Union
dc.titleExplainable AI in education: fostering human oversight and shared responsibilityeng
dc.typetext
dspace.entity.typePublication
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85

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