Episode 68 — Control Model Use in Decisioning: Credit, Hiring, Healthcare, and Safety Cases (Domain 1)
When AI is used to make decisions that significantly impact people's lives—such as in credit, hiring, or healthcare—the risk management requirements become significantly more stringent. This episode focuses on the governance of "high-stakes" automated decision-making and the necessity of rigorous fairness and explainability controls in these domains. For the AAIR certification, you must understand the legal implications of automated decisions under regulations like GDPR, which grants individuals the right to an explanation. We discuss the importance of human-in-the-loop oversight to validate the model’s reasoning and ensure that its outputs do not reflect systemic bias. Practical examples include the audit of a hiring algorithm to ensure it does not inadvertently filter out candidates based on protected characteristics. By implementing these high-level controls, organizations ensure that their use of AI for decisioning is not only accurate but also ethically defensible and legally compliant. 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.
