Mapping the Regulatory Learning Space for the EU AI Act
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Abstract (arXiv)
The EU AI Act represents the world's first transnational AI regulation with concrete enforcement measures. It builds on existing EU mechanisms for regulating health and safety of products but extends them to protect fundamental rights and to address AI as a horizontal technology across multiple application sectors. We argue that this will lead to multiple uncertainties in the enforcement of the AI Act, which coupled with the fast-changing nature of AI technology, will require a strong emphasis on comprehensive and rapid regulatory learning for the Act. We define a parametrised regulatory learning space based on the provisions of the Act and describe a layered system of different learning arenas where the population of oversight authorities, value chain participants, and affected stakeholders may interact to apply and learn from technical, organisational and legal implementation measures. We conclude by exploring how existing open data policies and practices in the EU can be adapted to support rapid and effective regulatory learning.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Feb 2025.
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Citing papers per year: 2025: 2; 2026: 1.
3 papers.
- 2025Assessing High-Risk AI Systems under the EU AI Act: From Legal Requirements to Technical Verificationcited by 4
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- 2026AI Act Evaluation Benchmark: An Open, Transparent, and Reproducible Evaluation Dataset for NLP and RAG Systems10 Mar 2026
- 2025Assessing High-Risk AI Systems under the EU AI Act: From Legal Requirements to Technical Verification15 Dec 2025
- 2025Quantifying the Climate Risk of Generative AI: Region-Aware Carbon Accounting with G-TRACE and the AI Sustainability Pyramid6 Nov 2025