Foundations of AI & Cybersecurity - Lesson 34: Scenario on Auditing Model Output for Risks

This scenario lesson explains that auditing AI outputs must be treated as a continuous operational control, not a one-time review step. It shows how grounding against hallucinations, validating accuracy, testing for fairness, and enforcing access controls work together to make AI outputs safer and more trustworthy. The key lesson is that enterprise AI earns trust only when its outputs are continuously checked for truth, correctness, equity, and authorized use.

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