A Paper: JouleWork Robotics A Thermodynamic Framework for Wage Calculation in Embodied AI.

Abstract

Sustainable compensation mechanisms in autonomous AI economies must be anchored in fundamental physical principles to promote efficiency and scalability. The JouleWork (JW) metric, as defined in prior work (Roemmele, 2026), quantifies labor value for abstract AI agents as JW = E × κ × W, where E is energy consumed in joules, κ is a normalization coefficient, and W is normalized work output. This paper presents JouleWork Robotics (⚡️JWR, JWR), an extension tailored to embodied AI systems, which integrates JW for cognitive components while incorporating adjustments for Moravec’s Paradox, time-motion efficiency principles, and overhead costs such as charging, idling, and traversal. In embodied agents, JW governs abstract subprocesses, and JWR unifies these with physical factors in a composite equation. The framework has been refined through critical analysis, incorporating detailed examples, simulation validation, limitations, ethical discussions, and comparisons to alternative metrics. Designed for zero-human companies, JWR assigns higher baseline wages to account for elevated energy demands, fostering bias-free, thermodynamically grounded economic models.

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