From Alpine Meadows to Planetary Commons: Arrow's Escape on the Threshold of AI Governance

Abstract: This paper advances a computational account of governance failure, arguing that the persistence of principal-agent pathologies across radically different political systems reflects not merely moral or structural inadequacy but the intractability of civilizational governance for biological cognition operating in human time. Drawing on Arrow's Impossibility Theorem, Ostrom's commons governance principles, and the epistemological implications of recent advances in artificial intelligence, the paper argues that AI-mediated dynamic preference tracking represents a practical escape from Arrow's constraints at civilizational scale. Ostrom's scalar boundary denotes a precise specification of the problem AI governance must solve. Risks of AI deployed as power amplifier rather than legitimate infrastructure are identified. A considered interpretation is offered of what genuine preference aggregation, freed from manufactured consent and false needs, might reveal about human wants. The is the third in a series following Nossal (2022) and Nossal (2026).