Argumentation and logic programming for explainable and ethical AI

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dc.contributor.authorCALEGARI, Roberta
dc.contributor.authorOMICINI, Andrea
dc.contributor.authorSARTOR, Giovanni
dc.date.accessioned2024-02-29T10:37:18Z
dc.date.available2024-02-29T10:37:18Z
dc.date.issued2020
dc.descriptionPublished online: 15 November 2020en
dc.description.abstractIn this paper we sketch a vision of explainability of intelligent systems as a logic approach suitable to be injected into and exploited by the system actors once integrated with sub-symbolic techniques. In particular, we show how argumentation could be combined with different extensions of logic programming – namely, abduction, inductive logic programming, and probabilistic logic programming – to address the issues of explainable AI as well as some ethical concerns about AI.en
dc.description.sponsorshipRoberta Calegari and Giovanni Sartor have been supported by the H2020 ERC Project “CompuLaw” (G.A. 833647). Andrea Omicini has been partially supported by the H2020 Project “AI4EU” (G.A. 825619).en
dc.format.mimetypeapplication/pdfen
dc.identifier.citationCEUR workshop proceedings, 2020, Vol. 2742, pp. 55-68en
dc.identifier.endpage68en
dc.identifier.issn1613-0073
dc.identifier.startpage55en
dc.identifier.urihttps://hdl.handle.net/1814/76643
dc.identifier.volume2742en
dc.language.isoenen
dc.orcid.uploadtrue*
dc.publisherRheinisch-Westfaelische Technische Hochschule Aachenen
dc.relationComputable Law
dc.relationA European AI On Demand Platform and Ecosystem
dc.relation.ispartofCEUR workshop proceedingsen
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.rights.licenseAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleArgumentation and logic programming for explainable and ethical AIen
dc.typeArticleen
dspace.entity.typePublication
person.identifier.orcid0000-0003-2210-0398
person.identifier.other29040
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