hardMultiple ChoiceObjective-mapped
AIF-C01 Practice Question: A company uses Amazon SageMaker to host a model…
A company uses Amazon SageMaker to host a model for fraud detection. The model must be re-evaluated for bias on a monthly basis. Which SageMaker feature can be used to detect bias in a trained model?
⚠ Common exam trap
Candidates often confuse SageMaker Model Monitor (which monitors data drift) with bias detection, but Model Monitor does not evaluate model fairness or bias metrics.
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
✓
SageMaker Clarify
SageMaker Clarify is the correct choice because it is specifically designed to detect bias in machine learning models and data. It provides built-in capabilities to evaluate bias metrics (e.g., difference in positive proportions, disparate impact) both before training (pre-training bias) and after training (post-training bias), making it suitable for the monthly re-evaluation requirement.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
SageMaker Debugger
Why it's wrong here
Debugger profiles training jobs, not bias detection.
- ✗
SageMaker Model Monitor
Why it's wrong here
Model Monitor detects data drift, not bias.
- ✓
SageMaker Clarify
Why this is correct
Clarify provides bias detection and explainability.
- ✗
SageMaker Autopilot
Why it's wrong here
Autopilot automates model building, not bias detection.
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JA
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.