Homo Fluxus: A Thermodynamic Framework for Consciousness, Systemic Empathy, and Aligned Intelligence

Summary

Cosmology, consciousness, affect, ethics, and AI alignment are often treated as separate problems, but this paper argues they share a single thermodynamic basis: local entropy minimization through coherent information flow, formalized as the cognition module of Energy-Flow Cosmology (EFC-C). From this, it derives an agent-as-node-in-flow ontology (Homo Fluxus) and a mechanism called systemic empathy, where field-coupled agents detect entropy changes beyond their own boundaries. A latent variable, coherence potential Φ_coh, is inferred from three proxies: integrated information rate, cross-frequency phase coherence, and interoceptive-allostatic integration. The framework predicts that current AI alignment failures result from applying bounded local optimization to unbounded coupled fields, and proposes field-empathy as a distinct architectural constraint.

Study at a glance

Abstract

Modern science treats cosmology, consciousness, affect, ethics, and AI alignment as separate problems, each with its own unresolved core. This paper argues that these problems share a single thermodynamic substrate: local entropy minimization through coherent information flow, as formalized in the cognition module of Energy-Flow Cosmology (EFC-C).From this substrate, two constructs are derived: Homo Fluxus, an agent-as-node-in-flow ontology, and field-coupled coherence sensitivity (here termed systemic empathy), an operational mechanism by which sufficiently field-coupled agents register entropy-state changes beyond their own boundary and weight actions accordingly.The framework introduces a coherence potential Φ_coh as a latent variable inferred from three convergent proxies: integrated information rate, cross-frequency phase coherence, and interoceptive-allostatic integration. The identity claim — that these are projections of one thermodynamic variable rather than independent correlates — yields falsifiable predictions at six levels (cosmological, neural, affective, social, ethical, computational).A key consequence is that current AI alignment failures correspond formally to a class of scaling errors: the application of bounded local optimization to unbounded coupled fields. The paper proposes field-empathy as an architectural constraint distinct from standard regularization or multi-objective methods, and outlines minimal test cases.The paper is positioned as one module within the broader Energy-Flow Cosmology framework; its claims are conditional on the substrate developed in companion EFC-S and EFC-D works. The unification claim derives its strength precisely from this cross-scale commitment.Methodological note: the construct of systemic empathy was developed in part through autoethnographic observation, framed using established methodological literature (autoethnography, neurophenomenology, post-traumatic growth research, ACE studies). This methodological context does not constitute evidential support for the claims of the framework, which stand or fall on third-person predictions.

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