On the Multiple Roles of Ontologies in Explainable AI

Roberto Confalonieri*, Giancarlo Guizzardi

*Corresponding author for this work

Research output: Working paperPreprintAcademic

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Abstract

This paper discusses the different roles that explicit knowledge, in particular ontologies, can play in Explainable AI and in the development of human-centric explainable systems and intelligible explanations. We consider three main perspectives in which ontologies can contribute significantly, namely reference modelling, common-sense reasoning, and knowledge refinement and complexity management. We overview some of the existing approaches in the literature, and we position them according to these three proposed perspectives. The paper concludes by discussing what challenges still need to be addressed to enable ontology-based approaches to explanation and to evaluate their human-understandability and effectiveness.
Original languageEnglish
PublisherArXiv.org
Number of pages14
DOIs
Publication statusPublished - 8 Nov 2023

Keywords

  • cs.AI
  • I.2.6

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