Theoretical analysis defines consciousness as minimum information loss via the Wasserstein metric across system partitions, highlighting the geometric foundation of integrated information.
FINDING: Integrated Information Theory (IIT) formalizes consciousness as a quantity Φ (phi), measuring irreducible cause-effect power of a system's state, with a mathematical core in information geometry and system partitioning. | MATH: Φ = minimum information loss (Earth Mover's Distance / Wasserstein metric) over all unidirectional partitions of the system's cause-effect repertoire; IIT 3.0 defines Φ via the *integrated information* of a mechanism M in state s: Φ(M,s) = min over partitions P of [EMD(p(s|M), p(s|M_P))], where p is the probability distribution over past/future states; IIT 4.0 refines this to *intrinsic cause-effect power* using the *system's own* perspective, with Φ^max as the system's integrated information. Key constants: none fixed — Φ is a real number ≥ 0, but the theory posits a *threshold* (Φ > 0) for consciousness, and a *maximal* Φ (Φ^max) for the dominant substrate. | CONNECTION: The Wasserstein metric (Earth Mover's Distance) is a *geodesic distance* on proba Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
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Andrew Stewart Caldin (2026) studied this question.
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