Question 20
Domain 2 — AI Operations, Lifecycle, and Control EnvironmentWhen assessing training data quality for an AI system, which dimension ensures that the data adequately covers all target population subgroups and real-world scenarios the model will encounter?
Correct answer: D
Explanation
Representativeness is the dimension that checks whether training data reflects the full target population and the situations the model will face. It ensures the dataset “adequately covers all target population subgroups and real-world scenarios,” so the model can generalize beyond a narrow sample.
Why each option is right or wrong
A. Accuracy
B. Timeliness
C. Consistency
D. Representativeness
Representativeness is the quality dimension that asks whether the training set mirrors the intended deployment population and operating context, including all relevant subgroups and scenario variation. In data-governance terms, this is the criterion used to avoid sampling bias and coverage gaps that would otherwise distort model performance on unseen but expected cases.