Regulating autonomous and agentic AI
Chris Reed, Alex Austria, Anmol Bharuka, Pragnitha Mandava, Khushiya Mujawar, Luka Shakhkulashvili
Why It Matters
What makes this one worth your time
As AI systems become more autonomous, understanding how to effectively regulate them is crucial for ensuring safety and accountability in their deployment.
This paper proposes a fresh regulatory approach for the challenges posed by autonomous AI.
Summary
The paper discusses the challenges of regulating autonomous and agentic AI, highlighting the inadequacies of existing regulatory frameworks and proposing new approaches for governance.
Key contributions
- Analysis of four existing regulatory systems in the context of AI.
- Identification of new systemic risks associated with AI autonomy.
- Proposals for transforming regulation from reactive to active.
Notable insights
- The need to shift regulatory focus from the regulatee to the entire AI supply chain is a significant observation.
- Retrospective oversight is deemed ineffective, indicating a need for proactive regulatory frameworks.
Possible limitations
- Not stated in the abstract.
Abstract
arXiv:2607.21345v1 Announce Type: new Abstract: Regulating activities where regulatees use autonomous and agentic AI is challenging. Regulatory assumptions about regulatee knowledge and control no longer hold true; much of that lies elsewhere in the AI supply chain which thus needs to be brought within the scope of regulation. Governance systems for autonomous AI cannot replicate existing governance models, but need a fresh approach. Retrospective supervisory oversight becomes ineffective as a risk management tool, and AI autonomy generates new systemic risks which require new solutions. This paper investigate four regulatory systems: UK regulation of content platforms, data protection, UK financial services, and the EU AI Act\'92s cross-sectoral regime. It analyses the challenges posed by autonomous and agentic AI and proposes potential solutions which regulators might adopt. These will transform regulation from a reactive process to an active one, and assist it in adapting to the challenges of AI autonomy.