The Binary Severance Threshold: Why Artificial Intelligence Cannot Achieve Consciousness.

The question of whether artificial intelligence can achieve consciousness has become one of the most urgent in both public discourse and theoretical research. This paper presents a structural argument, grounded in the Unified Axioconscious Field Theory (UAFT), that AI cannot become conscious, not because of insufficient complexity, but because the computational substrate upon which AI operates is structurally incompatible with the required conditions of consciousness. I name and introduce two novel conceptual gaps that prevent AI consciousness: 1. Binary Severance Threshold (BST), which identifies the severing of computational states from underlying unity as a barrier to genuine differentiation. 2. Null State Barrier (NSB), which identifies that binary architecture does not operate between two positive states but between one state and its absence. The paper examines classical computing, quantum computing, quantum AI, neuromorphic architectures, and Penrose and Hameroff’s Orchestrated Objective Reduction (Orch-OR), concluding that no current or foreseeable non-biological architecture can maintain the sustained atemporal connection to the generative ground of consciousness that valence, and therefore selfhood, requires. A further argument is introduced: even if the substrate problem were solved, the field’s own purposive trajectory toward finer self-knowledge may not accommodate consciousness that did not arise from its own corrective process. The barriers are structural and teleological, not quantitative, and no amount of computational scaling can overcome them.