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March 14, 20260 citationsOpen Access

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

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NTNarnaiezzsshaa Truong

Key Points

  • To present a tri-layer framework for diagnosing AI incidents in high-stakes environments.
  • Developed the Incident Boundary Diagnostic Instrument (IBDI) framework.
  • Integrated Boundary Intelligence, Emotional Indicators of Compromise, and APR-Lite.
  • Used a scenario-based simulator to score AI incidents.
  • Identified governance gaps in AI through boundary-visibility failure.
  • Highlighted emotional-procedural escalations in AI incidents.
  • Demonstrated the use of IBDI in a real-case scenario of Nippon Life v. OpenAI.

Abstract

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.

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Cite This Study

Narnaiezzsshaa Truong (2026) studied this question.

synapsesocial.com/papers/69b4b9eb18185d8a3980212ahttps://doi.org/10.5281/zenodo.18975425
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