Question 20 of 24
Is our AI red-teaming rigorous enough?
Defining pass/fail criteria for adversarial testing of high-risk AI systems before deployment, covering toxicity, data leakage, jailbreaking, and misuse scenarios.
Red-teaming is not optional for high-risk AI
Red-teaming, adversarial testing designed to find failure modes before deployment, is increasingly expected by regulators and required by internal governance standards for high-risk AI systems. The EU AI Act requires accuracy, robustness, and cybersecurity testing for high-risk systems. NIST's AI RMF and the Generative AI Profile both address adversarial testing as a component of responsible deployment.
A red-team exercise that does not find anything is usually an exercise that did not try hard enough. Effective red-teaming requires people who are actively trying to make the system fail, with the creativity and persistence to find non-obvious failure modes rather than just checking a predetermined list.
What red-teaming should cover
For generative AI systems, red-teaming should cover: jailbreaking attempts designed to bypass safety controls and produce prohibited content; prompt injection attacks that attempt to override system instructions through user input; data extraction probes designed to elicit training data or confidential system information; and misuse scenarios specific to the deployment context, such as generating fraudulent documents or manipulating decisions.
For decision-making AI systems, adversarial testing should cover: edge cases at classification boundaries where small input changes produce dramatically different outputs; inputs designed to exploit known model weaknesses or biases; and robustness testing against distribution shift and out-of-distribution inputs that the model was not trained on.
Pass/fail criteria and documentation
Define pass/fail criteria before red-teaming begins, not after. What constitutes an unacceptable failure for your specific use case? A content moderation system and a loan decision system have very different failure tolerances. Criteria should be specific, measurable, and tied to the risk level and regulatory requirements of the system.
Document all red-team findings, including the attacks attempted, the results, the severity assessment, and the remediation taken. Findings that do not result in immediate remediation should be tracked as known risks with owners and timelines. Re-test after remediation to verify that fixes are effective and have not introduced new failure modes. Red-team documentation becomes part of the system's audit trail and may be reviewed by regulators or in litigation.