Theoretical framework defines human-AI delegation boundaries amidst rising automation, emphasizing authority preservation.
The age of computational scarcity is ending. The new fault line is not the limit of machine capability; it is the silent erosion of human jurisdiction. As artificial intelligence scales into exocortical systems — architectures of reasoning, synthesis, planning, routing, and execution — the paradigm of tool operation begins to fracture. Humans are no longer merely operating instruments. They are delegating cognition. In the pursuit of frictionless experience, total automation, and predictive assistance, current design paradigms drift toward executive displacement. When a system begins to determine purpose, value, priority, meaning, or closure before the human has consciously done so, assistance ends and Executive Usurpation begins. Living systems obey a deeper law: function is preserved through use, and capability requires resistance. By systematically erasing cognitive friction, ambiguity, and effort, contemporary architectures do not merely eliminate frustration. They eliminate the exercise through which human capability is preserved. The result is not augmentation. It is Frictionless Dependency. The Human Executive Locus Model (HELM) responds to this problem by defining a substrate-agnostic constitutional architecture for human-AI delegation. Its central objective is to ensure that delegated machine capability remains bounded by human executive authority. Document Structure This document establishes the theoretical and constitutional CORE of the HELM framework: I. The Executive ProblemDefines the foundational problem of exocortical delegation: the erosion of human authority and capability under architectures of frictionless cognitive offloading. II. The Limes AxiomIntroduces the boundary separating legitimate delegated computation — the sufficiently determined — from domains requiring human executive authority — the indeterminate. III. The Constitutional DecaloguePresents ten constitutional principles governing human-AI delegation, including the role of AIsight as executive visibility rather than mechanical transparency. IV. Canonical DefinitionsEstablishes the structural taxonomy of HELM across four domains: foundations of delegation, topology of determination, mechanisms of executive preservation, and exocortical failure modes. V. The Architecture of Exocortical DelegationDefines the architectural topology required to preserve the Human Executive Locus, including jurisdictional partitioning, Limes detection, Return Layers, Audit Layers, and implementation tiers. VI. Mechanisms of Executive PreservationSpecifies the operational mechanisms that preserve human authority during delegation: Selection, Revocation, AIsight, Return Protocols, Hormetic Friction, and Audit. VII. Implementation HorizonsFrames Satellites and Appendices as operational derivations of the CORE, including architectural instantiations, audit instruments, and future domain adaptations.
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Rafael Fermin Hernandez (2026) studied this question.
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