AIF-C01 Practice Question: Security, Compliance, and Governance for AI Solutions
A machine learning team wants to detect bias in a deployed model's predictions on new data. They use Amazon SageMaker. Which service should they use to generate bias reports after deployment?
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
✓
Amazon SageMaker Clarify
Amazon SageMaker Clarify provides bias detection and explainability for ML models, both during training and after deployment. SageMaker Model Monitor detects data drift but not bias. SageMaker Debugger is for training debugging. SageMaker Role Manager is for managing IAM roles.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Amazon SageMaker Clarify
Why this is correct
Clarify can run bias metrics on predictions after deployment.
- ✗
Amazon SageMaker Debugger
Why it's wrong here
Debugger monitors training jobs, not inference.
- ✗
Amazon SageMaker Model Monitor
Why it's wrong here
Model Monitor detects drift in input data over time, not bias in predictions.
- ✗
Amazon SageMaker Role Manager
Why it's wrong here
Role Manager helps create IAM roles for SageMaker, 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.