INCIDENT BOUNDARY DIAGNOSTIC INSTRUMENT (IBDI): A Tri-Layer Diagnostic Framework for AI Incidents as Governance-Substrate Events

The Incident Boundary Diagnostic Instrument (IBDI) is a three-layer diagnostic framework for analyzing and training on AI incidents in regulated and high-stakes domains. IBDI integrates Boundary Intelligence (technical boundary and telemetry analysis), Emotional Indicators of Compromise (EIOC) (interaction-layer emotional and behavioral signals), and APR-Lite (governance controls for domain detection, friction, and finality) into a single scenario-based simulator and scoring engine. Each incident scenario is represented by a shared schema and evaluated through three coordinated diagnostic passes, producing both layer-specific scores and a unified remediation profile. Using the Nippon Life v. OpenAI disability-claim lawsuit as a worked example, this paper demonstrates how a single AI-mediated event can be decomposed into a boundary-visibility failure, an emotional-procedural escalation signature, and a substrate-layer governance gap. IBDI is published as timestamped prior art to support future jurisprudence, technical standards, and tool development in AI governance.