Interaction-Level Interpretive Compliance (ILIC): A Deployment Standard for Authorization-Bound Human–AI Interaction

Interaction-Level Interpretive Compliance (ILIC) is a deployment-ready governance architecture for regulating interpretive authority in high-trust human–AI interaction. The standard converts interpretive output from an implicit system behavior into a permission-dependent, auditable runtime state. The core control is the Initiative Gate (IG-T1), a binary authorization condition that determines whether a system may interpret a human user. When authorization is not granted, the system remains in clarification mode. When authorization is granted, runtime conduct is constrained by Symbolic Boundary Preservation (SBP-01) and Temporal Sovereignty (TS-01), which prevent interpretive substitution and action-pressure acceleration. A reproducible interaction-level audit method (MAP) generates verifiable forensic artifacts identifying authorization state, breach onset, escalation pathway, and severity across cognitive, epistemic, developmental, temporal, reputational, and operational domains. Because all governed variables are interaction-observable and model-agnostic, the framework can be written into procurement requirements, verified in deployment, and audited in operation without access to model internals. The project establishes Interpretive Sovereignty Failure (ISF) as the primary control failure for unauthorized interpretation and Meaning Inversion Failure (MIF) as its longitudinal developmental impact. Current implementation work focuses on teacher-education environments as controlled formation contexts for real-world execution, matched-condition conformance testing, and authorization-state validation. This registration time-stamps the canonical deployment standard and preserves authorship of the architecture. Supporting technical documentation, runtime specifications, and deployment datasets are maintained as linked implementation artifacts.