AI Incident Response: Best Practices

AI incidents are inevitable. Having a response plan ensures you can detect, contain, and remediate issues quickly.

Types of AI Incidents

Hallucinations: Fabricated facts that mislead users
Safety bypasses: Jailbreaks or policy violations
PII leaks: Personal information in outputs
Bias incidents: Discriminatory outputs
System failures: Outages or degraded performance

Response Process

1. Detect: Monitoring alerts on anomalies
2. Assess: Severity, scope, and impact
3. Contain: Guardrails, rollback, or disable
4. Investigate: Root cause analysis
5. Remediate: Fix and prevent recurrence
6. Document: Audit trail for compliance

Monitoring for Detection

Real-time classification of outputs
Alerts on high-risk detections
Anomaly detection for drift
Integration with incident management tools

What is an AI incident?

An AI incident is any event where an AI system causes harm, fails unexpectedly, or violates policies. This includes hallucinations that mislead users, safety bypasses, PII leaks, biased outputs, or system failures.

How should I respond?

Follow incident response best practices: 1) Detect and alert quickly, 2) Assess severity and impact, 3) Contain the issue (guardrails, rollback), 4) Investigate root cause, 5) Remediate and prevent recurrence, 6) Document for compliance.