Consciousness as Critical Phase Transition: A Philosophical-Computational Framework

We propose a philosophical-computational framework — PROSENTIR — in whichconsciousness is neither a binary property nor an irreducible mystery, butan emergent phenomenon arising at a critical phase transition in complexneural-like systems. Building on a constructive epistemological stance thatrejects radical skepticism on pragmatic grounds, we argue that subjectiveexperience can be operationalized through three measurable signatures: (i) critical slowing down, quantified by the relaxation time τ viaautocorrelation area integration; (ii) maximal susceptibility χ at thetransition point κc; and (iii) inter-module information integration Φ, estimated through the non-parametric Kraskov mutual information estimator. We implement and validate τ and χ in a modular, hierarchical neural networkwith asymmetric dynamics, confirming that these signatures co-emerge at asingle critical coupling κc. The Kraskov-based Φ is formalized as theprimary target of PROSENTIR Phase 2. Our framework connects the hard problemof consciousness to the theory of phase transitions in statistical physics, resolves the Molyneux problem through sensorimotor integration, and proposesa pragmatic criterion for machine consciousness grounded in autonomousinference rather than behavioral mimicry.