When Systems Turn Inward: The Self-Continuity Gradient

This essay explores a unifying feedback principle behind emotional collapse, organizational rigidity, mass conformity, and failure modes in artificial systems. When coherence becomes impossible, systems may minimize prediction error not by correcting the world but by adjusting or erasing the self. This reflective piece introduces the concept of the “self-continuity gradient,” a mechanism through which stability inverts into self-suppression across biological, social, and computational domains.