Defining the scope of AI regulations
Not on the map. Why?
Abstract (arXiv)
The paper argues that the material scope of AI regulations should not rely on the term "artificial intelligence (AI)". The argument is developed by proposing a number of requirements for legal definitions, surveying existing AI definitions, and then discussing the extent to which they meet the proposed requirements. It is shown that existing definitions of AI do not meet the most important requirements for legal definitions. Next, the paper argues that a risk-based approach would be preferable. Rather than using the term AI, policy makers should focus on the specific risks they want to reduce. It is shown that the requirements for legal definitions can be better met by defining the main sources of relevant risks: certain technical approaches (e.g. reinforcement learning), applications (e.g. facial recognition), and capabilities (e.g. the ability to physically interact with the environment). Finally, the paper discusses the extent to which this approach can also be applied to more advanced AI systems.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 26 Aug 2019.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 2; 2024: 1; 2025: 1; 2026: 2.
8 papers.
- 2023Frontier AI Regulation: Managing Emerging Risks to Public Safetycited by 98
- 2021Conformity Assessments and Post-market Monitoring: A Guide to the Role of Auditing in the Proposed European AI Regulationcited by 19
- 2025Unlocking the Black Box: Analysing the EU Artificial Intelligence Act's Framework for Explainability in AIcited by 11
- 2023International Governance of Civilian AI: A Jurisdictional Certification Approachcited by 8
- 2022Closed-Loop View of the Regulation of AI: Equal Impact across Repeated Interactionscited by 3
- 2026Legal Infrastructure for Transformative AI Governancecited by 2
- 2026When Do Data-Driven Systems Exhibit the Capability to Infer?cited by 1
- 2024The Switch, the Ladder, and the Matrix: Models for Classifying AI Systemscited by 0
- 2026When Do Data-Driven Systems Exhibit the Capability to Infer?10 Jun 2026
- 2026Legal Infrastructure for Transformative AI Governance1 Feb 2026
- 2025Unlocking the Black Box: Analysing the EU Artificial Intelligence Act's Framework for Explainability in AI24 Jan 2025
- 2024The Switch, the Ladder, and the Matrix: Models for Classifying AI Systems7 Jul 2024
- 2023International Governance of Civilian AI: A Jurisdictional Certification Approach29 Aug 2023
- 2023Frontier AI Regulation: Managing Emerging Risks to Public Safety6 Jul 2023
- 2022Closed-Loop View of the Regulation of AI: Equal Impact across Repeated Interactions3 Sep 2022
- 2021Conformity Assessments and Post-market Monitoring: A Guide to the Role of Auditing in the Proposed European AI Regulation9 Nov 2021