Episode 33 — Explain AI Types and Capabilities Leaders Must Understand to Govern Risk
This episode explains essential AI concepts that security leaders must understand to govern risk and make defensible decisions, reflecting exam expectations around emerging technology oversight and high-level risk-benefit analysis. You will define machine learning, deep learning, and generative models in practical terms, then distinguish training from inference so you can reason about where data flows, where errors can occur, and where controls must be applied. We examine how AI systems are commonly used in business and security contexts, including summarization, triage assistance, and pattern detection, while emphasizing limitations such as hallucinations, bias, and model drift that can create operational and security failures. Scenarios include a proposal to use AI for sensitive decision-making and how to evaluate whether oversight, validation, and monitoring are sufficient, plus troubleshooting considerations for unclear data ownership, uncontrolled adoption, and overconfidence in outputs that are not verified. 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.
