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AI Governance and EthicsmediumMultiple ChoiceObjective-mapped

AI0-001 AI Governance and Ethics Practice Question

A healthcare AI startup is developing a diagnostic tool that uses patient data to predict disease risk. To comply with HIPAA and minimize privacy risks while still training accurate models, which privacy-preserving technique should they prioritize?

⚠ Common exam trap

The AI0-001 exam often tests the misconception that anonymization or pseudonymization are sufficient for HIPAA compliance in AI contexts, but the trap here is that these techniques do not protect against inference attacks or re-identification in high-dimensional data, whereas differential privacy provides a provable mathematical guarantee.

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

Differential privacy is the correct choice because it provides a formal mathematical guarantee that the output of a model does not reveal whether any individual's data was included in the training set. This is essential for HIPAA compliance as it prevents re-identification attacks even when an adversary has auxiliary information. Unlike anonymization or pseudonymization, differential privacy adds calibrated noise to the training process or query results, ensuring strong privacy protection while preserving model utility.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Anonymization

    Why it's wrong here

    Anonymization strips identifiers, but advanced re-identification attacks can still succeed.

  • Pseudonymization

    Why it's wrong here

    Pseudonymization replaces identifiers with pseudonyms, but data can often be re-identified.

  • Differential privacy

    Why this is correct

    Differential privacy provides a mathematical guarantee against re-identification and is suitable for healthcare AI.

  • Data minimization

    Why it's wrong here

    Data minimization reduces the amount of data collected, but may not prevent re-identification of individuals.

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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.