arXiv AI By Victor Frimpong

The Governance Inversion Hypothesis: Why More AI Regulation May Produce Less Organisational Control

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arXiv:2606. 26117v1 Announce Type: cross Abstract: This paper introduces the Governance Inversion Hypothesis (GIH) to explain a growing paradox in artificial intelligence (AI) governance: under conditions of increasing regulatory expansion and technological complexity, organisations may become more formally governed while simultaneously experiencing a decline in operational control over AI systems.

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arXiv AI
Jul 24

Regulating autonomous and agentic AI

arXiv:2607. 21345v1 Announce Type: new Abstract: Regulating activities where regulatees use autonomous and agentic AI is challenging.

By Chris Reed, Alex Austria, Anmol Bharuka, Pragnitha Mandava, Khushiya Mujawar, Luka Shakhkulashvili
arXiv AI
2d ago

Architecture Without an Architect? Global Governance of Artificial Intelligence in a Divided World

The essay reviews Matthijs Maas’s framework for global AI governance, highlighting the rapid, border‑less development of AI and the fragmented, non‑binding international responses. It argues that governance cannot rely on a single institutional blueprint but must account for the varied powers of states, international bodies, and private firms. The central challenge is shaping an evolving architecture amid actors with differing incentives and no shared plans.

By Simon Chesterman