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Semantic Models for Trustworthy Systems: A Hybrid Intelligence Augmentation Program

dc.contributor.authorGuizzardi, Giancarlo
dc.contributor.editorMichael, Judith
dc.contributor.editorWeske, Mathias
dc.date.accessioned2024-02-19T11:27:55Z
dc.date.available2024-02-19T11:27:55Z
dc.date.issued2024
dc.description.abstractCyber-human systems are formed by the coordinated interaction of human and computational components. In this talk, I will argue that these systems can only be designed as trustworthy systems if the interoperation between their components is meaning preserving. For that, we need to take the challenge of semantic interoperability between these components very seriously. I will discuss a notion of trustworthy semantic models and defend its essential role in addressing this challenge. Finally, I will advocate that engineering and evolving these semantic models as well as the languages in which they are produced require a hybrid intelligence augmentation program resting on a combination of techniques including formal ontology, logical representation and reasoning, crowdsourced validation, and automated approaches to mining and learning.en
dc.identifier.doi10.18420/modellierung2024_001
dc.identifier.isbn978-3-88579-742-5
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/43611
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofModellierung 2024
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-348
dc.titleSemantic Models for Trustworthy Systems: A Hybrid Intelligence Augmentation Programen
dc.typeText/Conference Paper
gi.citation.endPage17
gi.citation.publisherPlaceBonn
gi.citation.startPage17
gi.conference.date12.-15. March 2024
gi.conference.locationPotsdam, Germany
gi.conference.sessiontitleKeynote

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