Episode 54 — Build Fallbacks and Fail-Safes: What Happens When AI Must Stop (Domain 3)
Every mission-critical AI system must have a robust "Plan B" to ensure business continuity if the model fails or behaves unpredictably. This episode explores the design of fallbacks, such as reverting to a traditional rule-based system, and fail-safes, which are automated triggers that halt a process before harm can occur. For the AAIR certification, understanding how to define these trigger points—such as a specific error rate threshold or a loss of connectivity to a critical data source—is essential. We discuss the importance of "graceful degradation," where the system loses some functionality but continues to operate in a safe, limited capacity. Examples include an autonomous vehicle coming to a controlled stop if its sensors are blinded or a financial trading algorithm pausing if market volatility exceeds its programmed limits. By building these emergency protocols, risk professionals ensure that an AI failure does not lead to a total system collapse, protecting both the organization and its customers from catastrophic outcomes. 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.
