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AIF-C01 Practice Question: A healthcare organization is deploying an AI…
A healthcare organization is deploying an AI system to assist in diagnosing diseases from medical images. They need to ensure the system is robust, safe, and subject to human oversight. Which TWO actions align with responsible AI guidelines? (Select TWO.)
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
✓
Monitor model performance over time to detect data drift
Monitoring for data drift and integrating human review for high-risk decisions are key practices for robustness, safety, and controllability. The other options are either insufficient or irrelevant.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Monitor model performance over time to detect data drift
Why this is correct
Data drift can degrade model accuracy; monitoring ensures robustness and triggers retraining when needed.
- ✗
Deploy the model directly to production without testing
Why it's wrong here
Skipping testing violates safety and veracity principles.
- ✓
Use Amazon Augmented AI (A2I) to set up human review for uncertain predictions
Why this is correct
A2I enables human-in-the-loop, ensuring that high-stakes decisions are reviewed by humans, promoting safety and controllability.
- ✗
Permanently disable human review to speed up diagnoses
Why it's wrong here
Removing human oversight increases risk and violates safety and controllability principles, especially in healthcare.
- ✗
Use only one source of training data
Why it's wrong here
Limited data sources can introduce representation bias; diverse data is recommended for robustness.
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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.