ISACA Advanced in AI Security Management Practice Mode

Community Discussion

Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.

• Chose C2

  Hallucination solution is always to have human in the loop to verify.

• Chose B1

  Addresses the root cause — ensures real-world data is accurate/complete/reliable before it influences model outputs, directly reducing hallucination risk at the source

• Chose C2

  When deploying an AI solution to generate treatment regimens—a high-risk, safety-critical use case—the most effective way to reduce the risk of hallucinations is to ensure that a qualified human expert reviews, approves, or overrides AI outputs before they influence patient care. A human-in-the-loop (HITL) mitigates hallucination risks by: Catching incorrect, implausible, or clinically unsafe recommendations Ensuring AI outputs align with medical standards, guidelines, and clinical judgment Providing accountability and oversight, especially when real-world data introduces noise, bias, or edge cases This is strongly aligned with FDA, EMA, and ISO/IEC 42001 expectations for high-risk AI.