Make Defensible AI Incident Decisions

Did an AI system cause the harm, materially contribute to it, amplify it, or fail to prevent it?

And how serious was the actual or potential impact?

Causality and severity are two of the most consequential and difficult questions in AI incident response.

This white paper offers practical guidance for evaluating those questions, preserving relevant evidence, and documenting decisions that can withstand regulatory, legal, and organizational scrutiny.

KEY TAKEAWAYS

• Evaluate direct causation, material contribution, amplification, and failure to prevent harm

• Assess severity using real-world impact, scale, duration, and reversibility

• Understand how litigation and regulatory reviews may approach AI incidents differently

• Build evidence readiness with consistent, time-stamped, and auditable records