Episode 55 — Control Retraining and Updates: Governance Gates and Regression Testing (Domain 3)
The lifecycle of an AI model is iterative, but retraining a model on new data introduces the risk of "regression," where previously corrected errors reappear or new biases are introduced. This episode details the governance gates that must be passed before a retrained model is allowed back into production. For the AAIR exam, candidates must understand the importance of regression testing, which verifies that the model still performs correctly on older, critical test cases while also handling new data effectively. We discuss the risks of "automated retraining" without human review, which can lead to rapid and uncontrolled performance shifts. Best practices involve maintaining a "champion-challenger" model where the new version is tested in parallel with the current version before being fully deployed. By applying these controls, organizations can ensure that model updates lead to genuine improvement rather than introducing new vulnerabilities or eroding the stability of the existing production environment. 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.
