The Third Enclosure Movement: Rethinking AI Regulation through a Taxonomy of Restricted Knowledge
Abstract
This paper examines how law and policy can respond to multi-layered enclosures emerging in AI governance. It introduces two conceptual tools: the Third Enclosure Movement, situating AI within historical logics of exclusion, and a Taxonomy of Restricted Knowledge, distinguishing legal, technical, epistemic, and state-enforced enclosures. A comparative analysis of the UK, EU, US, and China, alongside case studies in healthcare, agritech, and consumer AI, suggests no single strategy suffices. While abolitionist critiques expose structural injustices in intellectual property, treaty lock-in under TRIPS and entrenched domestic frameworks make wholesale abolition infeasible. The paper argues instead for treaty-compliant partial-commons reforms within existing legal architectures, including compulsory licensing under TRIPS (arts 30–31), disclosure and audit obligations under the EU AI Act (arts 16–29), interoperability duties under the Digital Markets Act (arts 6(4)–(9)), and open-licensing conditions for publicly funded AI outputs. It reframes AI governance as the defence of shared epistemic agency and proposes a legally realistic middle path that constrains recursive enclosure while sustaining democratic legitimacy in the age of AI.
Keywords
- Enclosure
- AI regulation
- Knowledge governance
- Liability
- Auditability
- Commons
- Restricted knowledge