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AICat: An AI Cataloguing Approach to Support the EU AI Act

arXiv 2501.04014 ↗First posted 19 Dec 2024cs.DL cs.AI cs.CYcited by 0

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Abstract (arXiv)

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.

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References · 4

  1. 2024Croissant: A Metadata Format for ML-Ready Datasetscited by 79
  2. 2023Use case cards: a use case reporting framework inspired by the European AI Actcited by 14
  3. 2024AI Cards: Towards an Applied Framework for Machine-Readable AI and Risk Documentation Inspired by the EU AI Actcited by 10
  4. 2024Data Privacy Vocabulary (DPV) -- Version 2cited by 7

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