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

Morten Magnusson

Figshare April 25, 2026 DOI: 10.6084/m9.figshare.32099389.v1 (opens in new tab)

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AI-extracted from the abstract
Characteristics Theoretical or philosophical paper Peer reviewed
Keywords Context archaeology Regularization linguistics Ambiguity Latent variable Variable mathematics Unification Maximization Artificial intelligence Theoretical computer science Forgetting Bounded function Predictability Scaling Mutual information
Key points Argues that cosmology, consciousness, affect, ethics, and AI alignment share a thermodynamic substrate of local entropy minimization through coherent information flow, and that AI alignment failures correspond to scaling errors from bounded local optimization applied to unbounded coupled fields.

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.