What question did this study set out to answer?

The goal is to integrate emotional-layer governance into the AI Risk Management Framework for better detection of risks.

February 2, 2026Open Access

EIOC-NIST AI RMF Integration: Mapping Emotional-Layer Governance to the AI Risk Management Framework

Key Points

The goal is to integrate emotional-layer governance into the AI Risk Management Framework for better detection of risks.
Developed the Emotional Indicators of Compromise (EIOC) framework.
Mapped EIOC primitives to each function of the NIST AI RMF.
Outlined protocols for operator posture and escalation.
Identified gaps in the current AI RMF regarding emotional risks.
Demonstrated how EIOC fills these gaps with structured detection mechanisms.
Provided a comprehensive mapping to enhance AI governance.

Abstract

The NIST AI Risk Management Framework (AI RMF) establishes a comprehensive governance structure for responsible AI deployment through four core functions: Govern, Map, Measure, and Manage. While the AI RMF acknowledges human-layer risks—including manipulation, autonomy erosion, and emotional harm—it does not specify mechanisms for detecting or mitigating these risks at the emotional layer. The Emotional Indicators of Compromise (EIOC) framework provides the missing instrumentation: a structured set of emotional-layer detection primitives, operator posture protocols, and a tiered escalation model that operationalize the human-layer commitments embedded in the AI RMF. This document maps EIOC primitives and tools to each RMF function, demonstrating how EIOC completes the AI governance stack.

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