Which of the following is a key risk indicator (KRI) for an AI system used for threat detection?
A.
Number of training epochs
B.
Training time of the model
C.
Number of layers in the neural network
D.
Number of system overrides by cyber analysts
The Answer Is:
D
This question includes an explanation.
Explanation:
AAISM materials emphasize that in operational AI systems, key risk indicators (KRIs) must reflect risks to performance and reliability rather than technical design factors alone. In the case of threat detection, the most relevant KRI is the frequency of system overrides by human analysts, as this indicates a lack of trust, frequent false positives, or poor detection accuracy. Training epochs, model depth, and training time are technical metrics but do not directly measure operational risk. Analyst overrides represent a practical measure of system effectiveness and risk.
[References:, AAISM Study Guide – AI Risk Management (Operational KRIs for AI Systems), ISACA AI Security Management – Monitoring AI Effectiveness, ]
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