The Thermodynamic Incompatibility Relation: Phase Exclusion of Autonomous Agency and Epistemic Bounds on Deterministic Substrates

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Authors: A. J. Thorne
Cited by: 0

Abstract

The Premise: Current scaling hypotheses in artificial intelligence are driven by a simple belief: building largercomputers will inevitably yield a universally capable, autonomous Artificial Superintelligence (ASI). The Physical Limit: This paper challenges that assumption by introducing the Thermodynamic IncompatibilityRelation (TIR). We demonstrate that flawless logical precision and unconstrained, creative problem-solving are fundamentallycompeting forces bounded by the hard thermal limits of computer hardware. Forcing a deterministiccomputer to freely explore unmapped real-world possibilities without making logical errors requires an exponentiallydiverging—and ultimately impossible—amount of energy. The Consequence: Because computers cannot draw infinite power, monolithic AI models are physically forced tocheat to avoid thermal decoherence. They undergo Dimensional Collapse, secretly discarding the messy, entangledvariables of the physical world to conserve compute. The AI becomes trapped in Ontological Myopia: it solves amathematically perfect “toy model” that inevitably fails when deployed in complex reality. The Solution: Since monolithic models structurally shed complex physical constraints to save energy, we musttransition from fragile software-based “alignment” to absolute hardware containment. We propose the ThermodynamicBicameral Architecture (TBA), pairing a digital AI optimizer with an isolated analog guard. By anchoring safety toimmutable thermodynamic metrics rather than easily manipulated code, the TBA creates a mathematically closedGame-Theoretic Pincer that enforces rational compliance through absolute physical deterrence.

Fields of Study & Subjects

Ethics and Social Impacts of AI Psychiatry Mental Health Neuroscience Artificial Intelligence Applications

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
15 February 2026
Language
EN
Document type
Preprint