The Structural Recursive Model for Human-AI Interaction

Although personal informatics offers fragmented data, it often does not provide a coherent grammar to understand yourself. To address this gap, we present the Structural Re-cursive Model (SRM), a unified framework f or representing, measuring, and navigating the dynamics of identity. SRM reconceive “perfection” not as a static state, but as the capacity for context-sensitive alignment under change. Our contribution is fourfold: (i) a structured state space (domains × stakeholders) with a symbolic G-scale; (ii) a formal model of structural satisfaction, happiness, and resilience; (iii) a temporal, volumetric extension to capture long-term evolution; and (iv) a concrete architecture for AI self-modeling, enabling artificial agents to maintain their own SRM for transparent, value-aligned interaction. Ultimately, SRM provides a computational grammar for the self-a language structured enough for machine implementation, yet expressive enough for lived experience, paving the way for a new symbiosis between human and artificial cognition.