AI0-001 AI Governance and Ethics Practice Question
A healthcare AI system uses patient data to predict disease risk. To comply with HIPAA and reduce the risk of re-identification, which technique should be applied to the training data before model development?
⚠ Common exam trap
A common misconception is that pseudonymisation (Option A) is equivalent to de-identification under HIPAA, when in fact it is a reversible process that fails against linkage attacks, making differential privacy the only mathematically rigorous option.
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
✓
Differential privacy with a carefully chosen epsilon
Differential privacy (Option C) is the correct technique because it adds calibrated noise to the training data or model outputs, providing a mathematical guarantee against re-identification even if an attacker has auxiliary information. This directly addresses HIPAA's requirement to protect patient privacy while preserving statistical utility for disease risk prediction.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Pseudonymisation by replacing patient names with random IDs
Why it's wrong here
Pseudonymisation is reversible and can be combined with other data to re-identify individuals; it does not satisfy HIPAA's de-identification requirements.
- ✗
Data augmentation to create synthetic samples
Why it's wrong here
Synthetic data can still leak information from the original data and does not provide formal privacy guarantees.
- ✓
Differential privacy with a carefully chosen epsilon
Why this is correct
Differential privacy adds controlled noise to protect individual records, meeting HIPAA's de-identification standards with formal guarantees.
- ✗
Data minimisation by removing all features except age and gender
Why it's wrong here
Removing features may still allow re-identification and does not provide formal privacy guarantees required by HIPAA.
About these practice questions
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA 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 AI0-001 exam.