Jinho Lee

We argue that AI governance, in its current form, is structurally incomplete—not due to a lack of ethical frameworks or alignment strategies, but because it omits a measurable variable: the state of consciousness. This is not a philosophical gap. It is an operational failure. For decades, consciousness has been treated as unmeasurable, and therefore excluded from system design. As a result, AI systems are governed as if human cognitive states were static, context-free, and irrelevant. This assumption is no longer tenable. The first scientific transformation driven by AI is already reshaping human cognition at scale—without any measurable interface to detect, model, or regulate its impact. We propose a reframing: governance must become state-dependent. The Consciousness Civilization Framework (CCF) introduces: (1) a state-space model of consciousness (OE–RE–EE), (2) quantifiable indices (VCE, CRI, CFI), and (3) an experimental interface pathway (CAIS / Sal-Meter) for detecting consciousness-like signals through molecular–electrochemical systems. This framework does not claim a complete solution to the hard problem of consciousness. It asserts something more urgent: full measurement is not required to begin governance. Partial, operationally reliable signals—if measurable and reproducible—are sufficient to transform AI systems from state-blind to state-aware. The necessary scientific pathway is not hypothetical. It is already formalized, documented, and open for validation. This paper positions CCF not as a theory, but as an entry point to a research program—one that invites direct participation in the experimental grounding of consciousness measurement and its integration into AI governance. The alternative is clear: to continue scaling AI capability while remaining unable to measure the human-state transformations through which its deepest cognitive, relational, and civilizational impacts become visible.