A Deterministic Architecture for Pre-Execution Governance

Le résumé fourni par la source

Artificial intelligence systems require reliable pre-execution mechanisms to ensure contextualintegrity, traceability, and internal coherence before actions are carried out. Terms such asclarity and awareness are frequently used in governance discourse, yet they are rarelyformalized in operational terms.This paper introduces PREEXEC™, a deterministic pre-execution architecture that quantifiesClarity as a structural coherence state and Awareness as a composite of State, Intent, andContext Awareness. Normalized sub-scores, deterministic thresholds, and a versioned audittrail (AuditChain) enable reproducible release decisions, traceability, and systems-levelmonitoring.The architecture builds on established concepts from context-aware computing, intentionmodeling, systems-theoretic safety, and AI risk management, providing a practical foundationfor higher-order governance layers.

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