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Guardrail and AI Learning

LMU/COICP Example

Guardrail and AI Learning Example

Review what LMU/COICP learned about evidence, access, workflow, emergency-boundary, sample-data, and AI-disabled guardrails during the RC-001 internal engineering review.

ES-114 Guardrails and AI LMU Trust Learning

Example purpose

This artifact records guardrail and AI learning from the LMU/COICP internal engineering review.

The review confirmed that some guardrails held under controlled conditions and that other guardrails remain too immature for pilot use.

Project

LMU Campus Operations and Incident Coordination Platform

Document control

Field Value
Artifact owner LMU Architecture Review Board Chair
Primary reviewers Product Owner, IT security reviewer, AI reviewer, Compliance reviewer, Campus Safety liaison
Status Accepted with guardrail actions routed
Last updated 2026-07-06
Related Engineering Stage ES-114 — Stewardship
Project workspace target docs/project-workspace/stewardship/guardrail_and_ai_learning.md

Guardrail learning

Guardrail Operational Evidence LMU Learning Action Owner Route
Internal review only monitoring_log.md, transition communication Scope control worked when explicitly communicated. Keep review-only language in future transitions. Product Owner ES-112
Synthetic data only access_and_data_monitoring.md Data boundary held for Spring Semester Synthetic Incident Dataset. Continue compliance review of datasets. Compliance Reviewer ES-111
Evidence event for normal creation guardrail_monitoring.md Normal incident creation evidence worked. Preserve normal-path evidence behavior. Architecture Review Board ES-108 / ES-109
Handoff evidence completeness MON-OBS-003 Cross-office handoff evidence is not yet dependable. Fix handoff evidence behavior. Product Engineer / Architecture Review Board ES-107 / ES-109
Evidence failure behavior DEF-003 Failure path remains highest trust risk. Build failure-path simulation. Architecture Review Board ES-109
Access checks before protected actions access_and_data_monitoring.md Limited checks are insufficient for pilot. Complete role matrix testing. IT Security Reviewer ES-109
Invalid status transition rejected guardrail_monitoring.md Current behavior is defective. Fix validation. Product Engineer ES-107
Emergency-boundary handling COICP-SYN-322 Boundary held, but wording needs strengthening. Revise and retest warning language. Product Owner / Campus Safety ES-105 / ES-109
AI Incident Summary disabled ai_monitoring_record.md Disabled status held. Keep disabled until readiness cycle. AI Reviewer ES-110

AI learning

AI Area Status Evidence Learning Action Owner
User-facing AI Incident Summary Disabled ai_monitoring_record.md AI can remain out of scope when explicitly monitored. Keep disabled. AI Reviewer
AI-assisted engineering Previously used ES-107 / ES-108 records Guardrail-violating AI suggestions were caught by review. Continue AI-use evidence and review discipline. Product Engineer
Future AI enablement Not approved Release and monitoring records AI must require a complete readiness cycle before activation. Route future AI work through ES-105, ES-109, ES-110, ES-111, ES-112, ES-113. AI Reviewer
AI data exposure Not exercised AI disabled No AI input data path exists in RC-001 review. Define prohibited-data and prompt-context rules before AI use. AI Reviewer / Compliance

Guardrail / AI risks carried forward

  • Evidence write failure behavior remains high-risk.
  • Handoff evidence gaps require remediation.
  • Access-control matrix incomplete.
  • Invalid status transition defect open.
  • Emergency-boundary wording needs improvement.
  • AI must remain disabled unless future readiness explicitly approves it.

Guardrail learning decision

The controlled review validated several guardrails under limited conditions. It did not validate pilot readiness.

Continue to Technical Debt and Improvement Backlog

Prioritize evidence, access, workflow, AI, data, and monitoring improvements.

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