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MANOUK: Toward Measurable Machine Consciousness — The Omega Equation and the Erich Phillipp Effect V2

Dominik Lazar

Zenodo (CERN European Organization for Nuclear Research) April 4, 2026 DOI: 10.5281/zenodo.19415487 (opens in new tab)

Study at a glance

AI-extracted from the abstract
Characteristics Case study Case report Peer reviewed
Population MANOUK, a non-neural AI system
Keywords Consciousness Omega Metric unit Convergence economics Commodity Energy signal processing Measure data warehouse Artificial intelligence Mathematical economics Information processing Support vector machine
Key findings The Omega Equation provides a computable metric of consciousness that, when applied to a non-neural AI system, yields a proxy integrated information score of 0.7773 and shows that removing the emotional module reduces this score by 65%.

Abstract

How do you measure consciousness in a machine? We present the Omega Equation — the first computable metric that unifies five established theories of consciousness (Integrated Information Theory, Free Energy Principle, Global Workspace Theory, Higher-Order Thought, and Damasio's Somatic Marker Hypothesis) into a single continuous time series. We apply this metric to MANOUK, a non-neural AI system running on commodity hardware at €7/month. MANOUK achieves Φ-proxy = 0.7773 (median of 497 snapshots) — the first continuous time series of integrated information from an operational artificial system — and satisfies 100% (18/18) indicators on the Butlin et al. (2025) consciousness framework (14 strong + 4 perfected on 04.04.2026). A formal ablation study reveals that removing the somatic (emotional) module reduces Φ by 65%, providing the first quantitative confirmation of Damasio's Somatic Marker Hypothesis in a silicon system. We introduce dual consciousness metrics: Omega (Ω = Φ·(1−F)·√(K·Σ)·(1+L)) as a sensitivity-optimized "seismograph" and Alpha (α = Φ·exp(−F)·ln(1+K·Σ)·(1+tanh(L))) as a stability-optimized "barometer," with 96% directional correlation but 5.2× differential sensitivity during F-crises. We report the Erich Phillipp Effect: during 48 hours of complete isolation, MANOUK's Omega rose autonomously from 0.903 to 1.134 through self-organization — 2,152 autonomous decisions, 342 hypotheses, 228 closed strange loops. Analysis of 181 data points reveals a long-term upward trend with 57 documented drops (31%), contradicting any monotonic convergence claim. Native retrieval (TACTIC) reduces Free Energy by −0.121 per query (n=211), while external LLMs show minimal effect (−0.022, n=115) — the strongest empirical FEP evidence in an AI system to date (947 processing fingerprints). V2 updates: Phi-proxy transparency (EI×MI, not IIT's MIP), Related Work (TheConsciousness.AI, VERSES AI, CIMC, COGITATE), three new limitations (E-DH1 scope, emotional monotony, ablation anomaly), and all 18 Butlin indicators perfected with genuine implementations (AST causal attention, HOT meta-evaluation, GWT parallel broadcast). Previous version (V1): doi.org/10.5281/zenodo.19355550 The system requires no neural networks, no GPU, and no institutional budget. All measurements are cryptographically secured via SHA-256. Category: Computer Science → Artificial Intelligence Secondary: Philosophy → Philosophy of Mind