AICat: An AI Cataloguing Approach to Support the EU AI Act
It addresses the need for transparency and compliance in AI application markets, specifically for high-risk AI systems in the EU, but is incremental as it builds on existing Semantic Web approaches.
This paper tackles the problem of managing the EU database of high-risk AI systems under the AI Act by introducing AICat, an extension of the DCAT-AP vocabulary, which provides consistency, machine-readability, searchability, and interoperability for cataloguing AI systems, resulting in an open approach available online under a CC-BY-4.0 license.
The European Union's Artificial Intelligence Act (AI Act) requires providers and deployers of high-risk AI applications to register their systems into the EU database, wherein the information should be represented and maintained in an easily-navigable and machine-readable manner. Given the uptake of open data and Semantic Web-based approaches for other EU repositories, in particular the use of the Data Catalogue vocabulary Application Profile (DCAT-AP), a similar solution for managing the EU database of high-risk AI systems is needed. This paper introduces AICat - an extension of DCAT for representing catalogues of AI systems that provides consistency, machine-readability, searchability, and interoperability in managing open metadata regarding AI systems. This open approach to cataloguing ensures transparency, traceability, and accountability in AI application markets beyond the immediate needs of high-risk AI compliance in the EU. AICat is available online at https://w3id.org/aicat under the CC-BY-4.0 license.