Episode 9 — Risk Management Frameworks
Structured frameworks provide organizations with consistent methods for identifying, assessing, and mitigating AI risks. This episode introduces well-known models, including the National Institute of Standards and Technology (NIST) AI Risk Management Framework, ISO 31000 for risk management, and European Union approaches aligned with the AI Act. Core phases include mapping risks in context, measuring likelihood and impact, managing risks through controls and mitigation plans, and governing through policies, oversight, and continuous improvement. Frameworks ensure risks are not handled ad hoc but integrated systematically into organizational processes.
Practical examples demonstrate how risk frameworks operate in real-world contexts. A financial institution may map fairness risks in credit scoring, measure disparities using specific metrics, and manage them through algorithmic adjustments and governance oversight. A healthcare provider may apply continuous monitoring to ensure diagnostic tools maintain accuracy across diverse populations. Learners are also introduced to tools such as risk registers and key risk indicators that provide visibility and accountability. By the end, it is clear that risk frameworks transform abstract concerns about AI into structured, auditable practices that enable trust, resilience, and regulatory readiness. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your certification path.
