IIT's Phi Contradiction: Lossy Integration vs. Memory Persistence — E8 Intelligence Research
Year: 2026
Type: preprint
Abstract: FINDING: Integrated Information Theory (IIT) formalizes consciousness as a quantity Φ (phi) measuring irreducible system integration, but current formalizations depend on lossy integration, contradicting memory persistence. MATH: - Φ = integrated information, defined via effective information across a system's bipartition: \[ \Phi(X) = \min_{\text{bipartition}} \left( H(X) - \sum_i H(X_i) \right) \] where \(H\) is Shannon entropy over system states. - Alternative algorithmic information theory approach: \[ \Phi_{\text{alg}} = K(X) - \sum_i K(X_i) \] with \(K\) Kolmogorov complexity. - Key critique: lossy integration (e.g., mutual information) implies continuous memory damage; a lossless measure requires algorithmic information. CONNECTION: - No explicit geometric ratios (0.382, 0.618, etc.) or crystallographic symmetries appear in these findings. - However, the concept of irreducible integration resonates with lattice structures (e.g., root systems i Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
Author: Caldin, Andrew Stewart
Language: English
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7171562923
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