AI Safety as Control of Irreversibility: A Systems Framework for Decision-Energy and Sovereignty Boundaries
Recent AI systems compress the distance between capability growth and capability deployment. Earlier high-risk technologies were slowed by capital intensity, physical bottlenecks, organizational inertia, and specialized supply chains. By contrast, AI capabilities can be copied, invoked, embedded in workflows, and scaled across institutions at low marginal cost. This paper argues that declining deployment friction changes the safety problem at its root. Safety is not only local output correctness or preference alignment, but the control of irreversibility under rising decision density. The paper formalizes this claim through decision-energy density: the rate-weighted capacity of a node to ...
| Authors | Wesley Shu, Peng Wei |
|---|---|
| Primary category | cs.AI |
| Published | 2 May 2026 |
| Last updated at source | 2 May 2026 |
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