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Mitigating Generative AI Hallucinations

dc.contributor.authorDe Chiara, Alessandro
dc.contributor.authorManna, Ester
dc.contributor.authorSingh, Shubhranshu
dc.date.accessioned2025-12-09T11:00:42Z
dc.date.available2025-12-09T11:00:42Z
dc.date.issued2025
dc.description.abstractWe theoretically investigate whether AI developers or AI operators should be liable for the harm the AI systems may cause when they hallucinate. We find that the optimal liability framework may vary over time, with the evolution of the AI technology, and that making the AI operators liable can be desirable only if it induces monitoring of the AI systems. We also highlight non-trivial relationships between welfare and reputational concerns, human supervision ability, and the accuracy of the technology. Our results have implications for regulatory design and business strategies.
dc.format.extent44 p.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/2445/224749
dc.language.isoeng
dc.relation.ispartofUB Economics – Working Papers, 2025 E25/492
dc.relation.ispartofseries[WP E-Eco25/492]
dc.rightscc-by-nc-nd, (c) De Chiara et al., 2025
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceUB Economics – Working Papers [ERE]
dc.subject.classificationIntel·ligència artificial
dc.subject.classificationTeoria d'operadors
dc.subject.classificationDisseny de sistemes
dc.subject.otherArtificial intelligence
dc.subject.otherOperator theory
dc.subject.otherSystem design
dc.titleMitigating Generative AI Hallucinations
dc.typeinfo:eu-repo/semantics/workingPaper

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