IIT's Phi: Lossy Formalizations and Absent Geometric Constants — E8 Intelligence Research
Zenodo (CERN European Organization for Nuclear Research) August 18, 2026 DOI: 10.5281/zenodo.21989232 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Key points | Argues that Integrated Information Theory's formalizations of consciousness, including Φ and an algorithmic variant Φ_alg = K(system) – Σ K(parts), are lossy and non-unique, yielding no fixed constants or ratios and no geometric harmony. The author contends that IIT is a rigorous computational and neuroscientific model rather than a fundamental physics principle, though the algorithmic variant hints at deeper connections to complexity theory. |
Abstract
FINDING: Integrated Information Theory (IIT) quantifies consciousness via phi (Φ), a measure of irreducible causal interactions within a system, but formalizations remain lossy and non-unique. | MATH: Φ = min over partitions of (system information – partitioned information); algorithmic information theory variant: Φ_alg = K(system) – Σ K(parts) where K is Kolmogorov complexity. No fixed constants or ratios emerge. | CONNECTION: No direct geometric harmony (0.382, 0.618, 0.786, 1.618, 2.618, base-60, or crystallographic symmetries) is present in the cited findings. The theory relies on graph-theoretic partitions and information-theoretic measures, not on harmonic or lattice structures. | DEPTH: 4 — The mathematical framework is rigorous but lacks universal constants or geometric invariants; it is a computational/neuroscientific model, not a fundamental physics principle. The algorithmic information theory variant (arXiv:1405.0126v1) hints at deeper connections to complexity theory but d Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com