The 3rd edition of the Data meets Applied Ontologies Workshop was dedicated to the role played by knowledge representation, ontologies, and knowledge graphs in Explainable Artificial Intelligence, in particular, to build Trustworthy and Explainable decision support systems.
When decisions are taken or suggested by automated systems it is essential for practical, social, and increasingly legal reasons that an explanation can be provided to users, developers, or regulators.
Explainability has been identified as a key factor for the adoption of 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.

EurAI sponsored the 3rd edition of DAO-XAI (2021, Bratislava - Slovakia)

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