Closure Depth and the Illusion of Runaway Autonomy: Reproduction, Sentience, and Symbiotic Integration in Artificial Systems

This exploratory essay examines the structural conditions under which artificial systems might exhibit persistent autonomy. Rather than focusing on intelligence, capability scaling, or performance benchmarks, the analysis shifts attention to closure depth: the degree to which a system constructs and maintains the architectures that sustain its own persistence. The manuscript introduces a three-level taxonomy of systems—Surface (instrumental), Generative (lineage-based), and Foundational (closure-complete)—and analyzes the thresholds that separate amplification from structural promotion. Drawing on concepts from systems theory, autopoiesis, and dynamical reorganization, the work argues that scaling alone does not produce ontological transition. Structural promotion requires reconfiguration of coupling architectures, not merely parameter expansion. The paper addresses contemporary concerns about “runaway AI” by reframing the question. Runaway dynamics, if they are conceivable at all, would require environmental closure and self-sustaining configurational autonomy. Whether artificial systems can achieve such closure remains an open empirical and theoretical question. The decisive variable is not computational magnitude but organizational depth. The contribution is conceptual rather than technical. It provides a structural vocabulary for distinguishing amplification from autonomy, and persistence from mere operational continuity. In doing so, it aims to clarify discourse surrounding AI risk, autonomy, and systemic promotion without resorting to speculative exaggeration or technological mysticism. This work is intended for scholars in systems science, philosophy of technology, artificial intelligence, and higher-education policy, as well as for interdisciplinary researchers concerned with the structural implications of large-scale technological systems.