What does this research mean for the field?

In pre-execution AI governance, a mechanism constitutes true authorization only if it produces a verdict before execution at a non-bypassable, fail-closed runtime boundary and generates an independently reconstructible artifact, meaning alternative mechanisms like monitoring or logs cannot substitute for it. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.CHALLENGES_CONSENSUS.

What question did this study set out to answer?

To state the formal conditions constituting valid pre-execution AI authorization and demonstrate why alternative governance mechanisms cannot substitute for runtime enforcement.

August 22, 2026Open Access

The Authorization Non-Substitution Principle: A General Result for Pre-Execution AI Governance

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Authors

EMEdward MeymanFerghana Polytechnical Institute

Discussion

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Implication

Theoretical analysis defines necessary conditions for pre-execution AI authorization, indicating that monitoring signals and credentials cannot substitute for fail-closed runtime enforcement.

Key Points

To state the formal conditions constituting valid pre-execution AI authorization and demonstrate why alternative governance mechanisms cannot substitute for runtime enforcement.
Conducted a formal category analysis derived from the fundamental definition of authorization and the Authorization Artifact Test.
Evaluated candidate mechanisms—including observability, delegation, certification, deterrence, LLM-as-a-Judge, and documentation—against essential authorization criteria.
Formulated the Authorization Non-Substitution Principle (ANSP), establishing that valid authorization strictly requires a pre-execution verdict, a non-bypassable fail-closed runtime boundary, and a reconstructible artifact.
Established a three-question screening model to definitively separate mechanisms that merely support authorization from those that actively constitute it.

Cite This Study

Edward Meyman (2026) studied this question.

synapsesocial.com/papers/6a895f53ca7ade938187dd3b https://doi.org/10.5281/zenodo.22017005

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Implication

Theoretical analysis defines necessary conditions for pre-execution AI authorization, indicating that monitoring signals and credentials cannot substitute for fail-closed runtime enforcement.