Episode 8 — AI Regulation in Practice
AI regulation increasingly applies a risk-tiered framework, where obligations scale with the potential for harm. This episode explains how regulators classify systems into prohibited, high-risk, limited-risk, and minimal-risk categories. Prohibited systems, such as manipulative social scoring, are banned outright. High-risk systems, including those in healthcare, finance, or infrastructure, face stringent requirements such as conformity assessments, transparency obligations, and ongoing monitoring. Limited-risk systems, like chatbots, may require disclosure notices, while minimal-risk systems, such as spam filters, face little oversight. Learners gain clarity on how risk classification informs compliance strategies.
Examples illustrate regulation in action: financial credit scoring models categorized as high-risk must undergo fairness and robustness testing, while customer service bots may only require user disclosures. The episode highlights differences across jurisdictions, with the European Union AI Act serving as a prominent model and the United States favoring sector-specific guidance. Learners also examine the impact of regulation on organizations of different sizes, from startups struggling with resource demands to enterprises managing global compliance programs. By understanding these frameworks, learners see regulation not only as a constraint but as a mechanism to promote trust, prevent harm, and encourage responsible adoption of AI technologies. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your certification path.
