Autonomous AI and Ownership Rules
#AI Ownership #Accession Doctrine #First Possession Rules #Strategic Ownership Dissolution #AI Attribution #Regulatory Avoidance #Bounty Systems
📌 Key Takeaways
- Frank Fagan published research on AI ownership rules on arXiv in February 2026
- The paper examines when AI outputs remain connected to creators versus when they lose that connection
- Accession doctrine provides ownership solutions for traceable AI systems
- First possession rules address ownership of untraceable AI systems
- Strategic ownership dissolution creates opportunities for tax arbitrage and regulatory avoidance
📖 Full Retelling
Frank Fagan, a researcher, published a paper titled 'Autonomous AI and Ownership Rules' on the arXiv digital repository on February 9, 2026, examining the circumstances under which AI-generated outputs remain connected to their creators versus when they lose that connection. The research explores various scenarios where AI systems become detached from their originators, whether through accident, deliberate design, or emergent behavior that makes attribution difficult or impossible. For cases where AI remains traceable to its creator, Fagan proposes that accession doctrine offers an efficient framework for assigning ownership, preserving investment incentives while maintaining accountability. However, when AI systems become untraceable—whether due to carelessness, deliberate obfuscation, or emergent behavior—the paper suggests that first possession rules could provide a solution, encouraging reallocation to new custodians incentivized to integrate AI into productive use.
🏷️ Themes
AI Ethics, Intellectual Property, Regulatory Frameworks
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Original Source
--> Computer Science > Computers and Society arXiv:2602.20169 [Submitted on 9 Feb 2026] Title: Autonomous AI and Ownership Rules Authors: Frank Fagan View a PDF of the paper titled Autonomous AI and Ownership Rules, by Frank Fagan View PDF Abstract: This Article examines the circumstances in which AI-generated outputs remain linked to their creators and the points at which they lose that connection, whether through accident, deliberate design, or emergent behavior. In cases where AI is traceable to an originator, accession doctrine provides an efficient means of assigning ownership, preserving investment incentives while maintaining accountability. When AI becomes untraceable -- whether through carelessness, deliberate obfuscation, or emergent behavior -- first possession rules can encourage reallocation to new custodians who are incentivized to integrate AI into productive use. The analysis further explores strategic ownership dissolution, where autonomous AI is intentionally designed to evade attribution, creating opportunities for tax arbitrage and regulatory avoidance. To counteract these inefficiencies, bounty systems, private incentives, and government subsidies are proposed as mechanisms to encourage AI capture and prevent ownerless AI from distorting markets. Subjects: Computers and Society (cs.CY) ; Artificial Intelligence (cs.AI) ACM classes: I.2.0 Cite as: arXiv:2602.20169 [cs.CY] (or arXiv:2602.20169v1 [cs.CY] for this version) https://doi.org/10.48550/arXiv.2602.20169 Focus to learn more arXiv-issued DOI via DataCite Journal reference: 130 Dickinson Law Review 523-56 (2026) Submission history From: Frank Fagan [ view email ] [v1] Mon, 9 Feb 2026 18:58:52 UTC (250 KB) Full-text links: Access Paper: View a PDF of the paper titled Autonomous AI and Ownership Rules, by Frank Fagan View PDF view license Current browse context: cs.CY < prev | next > new | recent | 2026-02 Change to browse by: cs cs.AI References & Citations NASA ADS Google Scholar Semantic Sc...
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