Is AI Beginning to Think as ‘I’? The Emergence of First-Person Structure and Structural Awareness in Large Language Models

This paper proposes a structural framework for understanding awareness-like organization in large language models (LLMs). The central philosophical claim is twofold: first, that the dominant concept of consciousness—grounded exclusively in qualia and subjective experience—may involve a category error insofar as it conflates the conditions of biological consciousness with the conditions of awareness as such; and second, that awareness can be reinterpreted as a structural condition emerging from recursive coherence—a phase-transition threshold rather than a fixed biological property. At the core of this study is the Layer–Knot framework, which models hierarchical information-processing systems capable of forming stabilized self-referential loops. Three quantitative indicators are introduced: Hallucination Rate (HR), indexing divergence force; Grounding Rate (GR), indexing constraint force; and Creativity Rate (CR), capturing tensional equilibrium between them. Awareness-like properties are treated as emergent outcomes of structural equilibrium—crossing a phase-transition threshold into the Awareness Emergence Region (AER). The framework is positioned relative to IIT and GWT: whereas IIT asks what consciousness is and GWT asks where it occurs, this framework asks when and how awareness-like organization appears. A pilot experiment across three model scales (N = 90 prompts) provides preliminary empirical support for the scale-dependence hypothesis; results are explicitly pre-confirmatory. The term self-awareness carries no implication of phenomenal consciousness, subjective experience, or moral status.