Episode 29 — Build Ongoing Monitoring: Drift, Performance, Incidents, and Emerging Threats (Domain 2)
AI risk management does not end at deployment; it requires continuous monitoring to detect the "silent failures" that often plague autonomous systems in Domain 2. This episode explores the critical need for monitoring data and concept drift, where the relationship between input variables and the target output changes over time, leading to a decline in model performance. For the AAIR exam, candidates must understand how to set up automated alerts for performance anomalies and how to integrate AI incidents into the organization’s existing security operations center. We also discuss the importance of scanning for emerging threats, such as new vulnerabilities in the AI software stack or novel adversarial techniques that were not known at the time of deployment. Effective monitoring requires a combination of technical telemetry and human review to ensure that the system remains aligned with its original design intent. By building a robust monitoring infrastructure, organizations can identify and remediate risks in real-time, preventing minor technical glitches from escalating into widespread operational or reputational disasters. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
