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Ensuring trustworthy AI for sensitive infrastructure using Knowledge Representation

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dc.contributor.authorMejri, Oumayma
dc.contributor.authorWaedt, Karl
dc.contributor.authorYatagha, Romarick
dc.contributor.authorEdeh, Natasha
dc.contributor.authorSebastiao, Claudia Lemos
dc.contributor.editorKlein, Maike
dc.contributor.editorKrupka, Daniel
dc.contributor.editorWinter, Cornelia
dc.contributor.editorGergeleit, Martin
dc.contributor.editorMartin, Ludger
dc.date.accessioned2024-10-21T18:24:17Z
dc.date.available2024-10-21T18:24:17Z
dc.date.issued2024
dc.description.abstractArtificial intelligence (AI) has become increasingly integrated into various aspects of society, from healthcare and finance to law enforcement and hiring processes. More recently, sensitive infrastructure such as nuclear plants is engaging AI in aspects of safety. However, these systems are not immune to biases and ethical concerns. This paper explores the role of knowledge representation in addressing ethics and fairness in AI, examining how biased or incomplete representations can lead to unfair outcomes and unreliable decision-making. It proposes strategies to mitigate these risks.en
dc.identifier.doi10.18420/inf2024_167
dc.identifier.isbn978-3-88579-746-3
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/45144
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofINFORMATIK 2024
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-352
dc.subjectArtificial Intelligence
dc.subjectBias in AI
dc.subjectKnowledge Representation
dc.subjectTrustworthy AI
dc.subjectSensitive Infrastructure
dc.subjectData Bias
dc.subjectExplainable AI
dc.subjectAlgorithmic Fairness
dc.titleEnsuring trustworthy AI for sensitive infrastructure using Knowledge Representationen
dc.typeText/Conference Paper
gi.citation.endPage1938
gi.citation.publisherPlaceBonn
gi.citation.startPage1929
gi.conference.date24.-26. September 2024
gi.conference.locationWiesbaden
gi.conference.sessiontitle9th IACS WS'24

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