An organization is reviewing an AI application to determine whether it is still needed. Engineers have been asked to analyze the number of incorrect predictions against the total number of predictions

The correct answer is C. Key performance indicator (KPI). AAISM guidance identifies metrics like error rate versus total predictions as a key performance indicator (KPI) for evaluating AI model effectiveness. KPIs provide measurable values to assess performance against objectives. Model validation is broader and occurs prior to producti

AI Security Operations and Monitoring

Question

An organization is reviewing an AI application to determine whether it is still needed. Engineers have been asked to analyze the number of incorrect predictions against the total number of predictions made. Which of the following is this an example of?

Options

AControl self-assessment (CSA)
BModel validation
CKey performance indicator (KPI)
DExplainable decision-making

How the community answered

(46 responses)

A
9% (4)
B
2% (1)
C
87% (40)
D
2% (1)

Explanation

AAISM guidance identifies metrics like error rate versus total predictions as a key performance indicator (KPI) for evaluating AI model effectiveness. KPIs provide measurable values to assess performance against objectives. Model validation is broader and occurs prior to production use, testing the model against predefined standards. Control self-assessment relates to governance processes, not predictive accuracy. Explainable decision-making refers to interpretability, not error-rate evaluation. Thus, analyzing incorrect predictions against total predictions is a performance measure, making it a KPI.

Topics

#AI Performance Metrics#KPIs#AI Operations Monitoring

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