CfP special issue of Semantic Web journal on "The role of ontologies & knowledge in XAI"

Explainable AI (XAI) has been identified as a key factor for developing trustworthy AI systems. The reasons for equipping intelligent systems with explanation capabilities are not limited to user rights and acceptance. Explainability is also needed for designers and developers to enhance system robustness and enable diagnostics to prevent bias, unfairness, and discrimination, as well as to increase trust by all users in why and how decisions are made. XAI focuses on developing new approaches for explanations of black-box models by achieving good explainability without sacrificing system performance. This special issue will feature contributions dedicated to the role played by knowledge bases, ontologies, and knowledge graphs in XAI, in particular with regard to building trustworthy and explainable decision support systems.

We welcome four main types of submissions: (i) full research papers, (ii) reports on tools and systems, (iii) application reports, and (iv) survey articles. The description of the submission types is posted at http://www.semantic-web-journal.net/authors#types. While there is no upper limit, paper length must be justified by content. All manuscripts will be reviewed based on the SWJ open and transparent review policy and will be made available online during the review process.