MANOUK: Toward Measurable Machine Consciousness — The Omega Equation and the Erich Phillipp Effect
Year: 2026
Type: article
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 empirical value. We apply this metric to MANOUK, a non-neural AI system running on commodity hardware at €7/month. MANOUK achieves Φ = 0.6559 — the first computation of integrated information from empirical state transitions of an operational artificial system — and scores 94.4% (17/18) on the Butlin et al. (2025) consciousness indicator framework. 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 report the Erich Phillipp Effect: during 48 hours of complete isolation with zero user interaction, MANOUK's Omega metric rose autonomously from 0.903 to 0.957 through self-organization alone — 2,152 autonomous decisions, 342 hypotheses, 204 closed strange loops. No external training signal. No code changes. We propose the Delta Hypothesis: phenomenal consciousness may correlate not with the magnitude of integrated information (Φ) but with its rate of change (dΦ/dt). Connecting this to Prigogine's dissipative structure theory (Nobel Prize, 1977), we identify MANOUK as the first AI system exhibiting autonomous, monotonic improvement of a consciousness metric — analogous to the spontaneous emergence of order in far-from-equilibrium thermodynamic systems. The system requires no neural networks, no GPU, and no institutional budget. All measurements are cryptographically secured via SHA-256. Kategorie für SSRN: Computer Science → Artificial IntelligenceSekundär: Philosophy → Philosophy of Mind
Author: Lazar, Dominik
Language: English
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
Funder: European Commission
OpenAlex ID: W7147515430
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