Episode 94 — Choose audit criteria for AI using policy, risk, and outcomes (Domain 3A)

This episode explains how to choose audit criteria for AI by using policy, risk, and outcomes, because AAIA expects you to build criteria that can be proven with evidence, not just referenced as “best practice.” You’ll learn how internal policies and procedures become criteria when they include roles, required steps, thresholds, approvals, and recordkeeping expectations. We’ll cover how risk appetite and decision impact shape criteria depth, such as stricter criteria for high-impact decisions that require stronger validation, monitoring, and human review triggers. Outcomes-based criteria will focus on what the organization must demonstrate in production, including stable performance, controlled drift response, fairness monitoring where applicable, and effective complaint and incident handling. You’ll also learn how to handle ambiguous criteria by looking for documented interpretations, approved standards mappings, and consistent enforcement across teams, rather than inventing requirements on the fly. By the end, you should be able to pick exam answers that define criteria in a way that is measurable, defensible, and aligned to the scenario’s real risk. 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.
Episode 94 — Choose audit criteria for AI using policy, risk, and outcomes (Domain 3A)
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