Journal of Artificial Intelligence and AI Ethics
Research Article Volume: 1 & Issue: 1
Abstract
This research establishes a complete mathematical framework for general intelligence without agency. We prove that persistent agentic optimization under generality constraints is structurally incompatible with reachability preservation through an impossibility theorem grounded in coverage-based generality. We introduce reachability entropy (HR) as a con served quantity for non-agentic systems and prove the Boundary Flow Theorem: reachability entropy is conserved under constraint tangent, non-teleological dynamics. Extensive computational experiments validate conservation across 2D/3D systems over 104 timesteps, demonstrating perturbative stability under vi olations up to ϵ = 2.0 with second-order degradation. We present a complete singularity classification (S1, S2, S3) distinguishing geometric from teleological collapse mechanisms. This framework introduces Constraint-Induced Vector Fields (CIVFs) and Non-Teleological systems (NT-systems) as new classes in dynamical systems theory, with empirical vali dation including deliberate failure modes confirming theoretical boundary conditions. The paradigm establishes that general intelligence does not require agency, with implications for safe AI development.