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AIF-C01 Practice Question: Developing an AI system that transcribes medical…
A company is developing an AI system that transcribes medical consultations. To ensure privacy and security, they need to implement controls that protect patient health information (PHI). Which AWS service can help anonymize data before it is used for model training?
⚠ Common exam trap
AIF-C01 often tests whether candidates confuse general-purpose AI services (Rekognition, Comprehend) with the medical-specialized variant (Comprehend Medical), so picking plain Comprehend or Rekognition misses the PHI-specific capability.
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 Comprehend Medical
Amazon Comprehend Medical is a HIPAA-eligible NLP service purpose-built for extracting and detecting PHI from unstructured medical text such as clinical notes and transcriptions. It includes a DetectPHI API that identifies 18+ PHI categories (names, dates, IDs, contact info) so they can be redacted or anonymized before the data is used for model training.
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 Ground Truth
Why it's wrong here
Ground Truth labels and annotates datasets for supervised training; it does not detect and remove PHI from text. It would be correct when building labelled training sets, whereas anonymisation of medical transcripts requires a text-oriented detection and redaction service.
- ✗
AWS Lake Formation
Why it's wrong here
Lake Formation governs access, catalogues and permissions over data lakes; it controls who may query data rather than transforming or masking PHI within it. It suits centralised fine-grained access management, not the de-identification of consultation transcripts prior to model training.
- ✗
Amazon Rekognition
Why it's wrong here
Rekognition performs image and video analysis such as facial detection and moderation; it does not redact text or mask PHI in transcripts. It would be the right choice for identifying objects or faces in media, not for anonymising clinical text before training.
- ✓
Amazon Comprehend Medical
Why this is correct
Amazon Comprehend Medical uses natural language processing to detect and redact protected health information such as names, dates and medical record numbers within clinical text, satisfying the requirement to anonymise PHI before it reaches model training.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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.