Episode 2 — Grasp AI Definitions, Types, and Core Use Cases That Matter
This episode builds the vocabulary needed to understand later governance topics by separating broad AI concepts from narrower technical categories that often appear on the exam. You will review what artificial intelligence generally means in practice, how machine learning differs from rules-based automation, and why generative systems, predictive systems, recommendation systems, classification models, and decision support tools create different governance concerns. The episode also connects those definitions to real use cases in hiring, fraud detection, customer service, content generation, healthcare, and security operations so you can see how the same technical label can lead to very different risks depending on context. For exam purposes, the key skill is not reciting every model family but recognizing what a system is doing, what kind of output it creates, and how that affects oversight, accountability, and legal obligations. In real organizations, weak definitions cause bad procurement, vague risk reviews, and misleading claims about capability, so clear terminology is a governance control, not just a study topic. 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. And dont forget Cyberauthor.me for the companion study guide and flash cards!
