Which practice involves simulating real-world adversaries to identify vulnerabilities in AI applications?

• A. Explainability in AI
• B. Red teaming in AI systems
• C. TEVV in AI system development
• D. Chairperson

Answer: (B)

Red teaming involves simulating real-world adversaries to identify vulnerabilities in AI applications. In this practice, a dedicated team acts like attackers, probing the system with realistic scenarios to test data pipelines, prompts, access controls, deployment environments, and safety guardrails. The aim is to uncover weaknesses that might not show up in normal testing, such as susceptibility to prompt injection, data poisoning, model misuse, or privacy leaks, and to evaluate the effectiveness of governance, monitoring, and incident response. The insights from red teaming guide concrete mitigations—strong input validation, robust authentication, adversarial training, enhanced monitoring, and governance updates—so the AI system remains secure and trustworthy. This approach is different from explainability, which focuses on understanding how the model makes decisions.