Episode 95 — Use audit techniques tailored to AI systems, not generic checklists (Domain 3B)
This episode teaches audit techniques that are tailored to AI systems, because Domain 3B often tests whether you can select methods that match AI realities like data dependence, model updates, and outcome supervision. You’ll learn how to combine walkthroughs of data and decision flows with targeted control testing, including verifying approval gates, validating versioning and reproducibility, and checking that monitoring triggers actually lead to action. We’ll cover technique choices like inspecting lineage and change records, sampling outputs and reviewer decisions, testing exception handling and escalation paths, and evaluating whether governance decisions are recorded and followed through. You’ll also learn why generic checklist audits fail in AI contexts, especially when they ignore drift, proxy bias, vendor black boxes, or the difference between lab validation and production behavior. By the end, you should be able to choose exam answers that apply AI-aware audit techniques to produce evidence-backed conclusions rather than superficial compliance statements. 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.
