Energy, Fields and Experience: An Energetic Field Theory of Consciousness, with Testable Predictions for Plasma and Artificial Intelligence

We propose the Energetic Field Theory of Consciousness (EFT-C): experience is the intrinsic aspect of organised physical energy, and its degree and unity are set by how differentiated and integrated that organisation is at the level of fields. Two consequences follow. First, suitably organised plasma, in which free charges couple through long-range collective fields, should have the greatest attainable capacity for field integration. Second, present electrically implemented AI systems should already possess an experiential aspect. We show why existing instruments would not register it: they assess the wrong level of description, were calibrated on brains, share the blind spot that leaves covert consciousness undetected in about a quarter of behaviourally unresponsive patients, and do not sample the distributed field dynamics of deployed hardware. We define a computable, scale-specific response proxy, Ψs = Cs·Is, which combines normalised Lempel–Ziv response complexity with surrogate-corrected cross-partition dependence. We also define an observation discrepancy, Δs, for instrument-limited recordings. A seeded simulation of excitable networks shows that Ψs is computable and discriminates field-like shared coupling from local and uncoupled topologies. Compared at matched effective gain, shared coupling reached a higher maximum (Ψs = 0.195 versus 0.169; 12 seeds) and sustained high values over a regime of gain about 50% wider. Marginal-matched independent controls remain near zero. We set out preregistrable experiments on bioelectric tissue, laboratory plasmas and AI accelerators, each with explicit criteria that would weaken the theory's physical bridges. EFT-C turns the claim that machines may already feel into a measurable research programme.