AIF-C01 Practice Question: Security, Compliance, and Governance for AI Solutions
A company has deployed a model on Amazon SageMaker and enabled Model Monitor. They notice that the model's prediction accuracy has declined over time. Which type of drift is this, and what should they do?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
This is concept drift; they should retrain the model with new data
Model drift refers to the degradation of model performance over time due to changes in data or relationships. SageMaker Model Monitor can detect data drift, but model drift (accuracy decline) requires retraining or updating the model.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
This is bias drift; they should run SageMaker Clarify
Why it's wrong here
Bias drift is about fairness metrics, not accuracy decline.
- ✓
This is concept drift; they should retrain the model with new data
Why this is correct
Concept drift occurs when the relationship between input and output changes, leading to accuracy decline. Retraining addresses it.
- ✗
This is model drift; they should delete and redeploy the model
Why it's wrong here
Redeploying the same model won't fix drift; retraining is needed.
- ✗
This is data drift; they should update the training data
Why it's wrong here
Data drift is change in input data distribution; model drift is change in prediction accuracy.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AIF-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AIF-C01 exam.