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AIF-C01 Practice Question: A healthcare startup is deploying an AI system to…
A healthcare startup is deploying an AI system to assist in diagnosing skin conditions from images. They want to follow the NIST AI Risk Management Framework. Which THREE practices should they implement?
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
✓
Use Amazon SageMaker to continuously monitor model performance and retrain as needed
The NIST AI RMF emphasizes governance, transparency, and risk management. Documenting model cards, establishing human oversight, and continuous monitoring align with these principles.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use Amazon SageMaker to continuously monitor model performance and retrain as needed
Why this is correct
Continuous monitoring is part of risk management to detect and address issues over time.
- ✓
Document the model's intended use, performance, and limitations in a model card
Why this is correct
Model cards support transparency and documentation, key aspects of the NIST RMF.
- ✓
Establish a human-in-the-loop process for uncertain diagnoses
Why this is correct
Human oversight is recommended for high-risk applications like medical diagnosis.
- ✗
Archive all training data in Amazon S3 Glacier for long-term retention
Why it's wrong here
Archiving in Glacier is a data storage practice, not directly related to risk management.
- ✗
Deploy the model on AWS Lambda for serverless inference
Why it's wrong here
Serverless deployment is an infrastructure choice, not a risk management practice.
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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.