hardMultiple Choice
Generative AI Leader Practice Question: A multinational corporation deploys a generative…
A multinational corporation deploys a generative AI chatbot for customer support in the EU. They must ensure compliance with GDPR regarding user data used for fine-tuning. Which data governance practice is REQUIRED?
⚠ Common exam trap
A common trap is conflating privacy-enhancing best practices (anonymization, regional storage, model unlearning) with strict GDPR legal requirements. Candidates should identify the mandatory lawful-basis requirement — explicit consent for using personal data in fine-tuning — rather than selecting a best-practice 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
✓
Obtain explicit consent from users for their data to be used in fine-tuning
Under GDPR, using personal data for fine-tuning a generative AI model is a new processing purpose and requires its own lawful basis. Where consent is used, it must be freely given, specific, informed and unambiguous, and explicit consent is required for special-category or unexpected secondary uses. Option B identifies the mandatory legal requirement: obtaining explicit consent from users for their data to be used in fine-tuning. Option C addresses a data subject right that may apply once data is already processed, but it is not the primary upfront governance practice required for using personal data in fine-tuning.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Store user data only in the EU region to comply with data residency requirements
Why it's wrong here
Data residency is important but does not address the right to erasure or consent for fine-tuning.
- ✓
Obtain explicit consent from users for their data to be used in fine-tuning
Why this is correct
Consent is required, but it does not address the right to erasure after fine-tuning has occurred.
- ✗
Implement a mechanism to delete specific user data from the fine-tuning dataset upon user request
Why it's wrong here
GDPR's right to erasure requires the ability to delete personal data; this includes data used in training sets.
- ✗
Anonymize all user data before using it for fine-tuning
Why it's wrong here
Anonymization reduces privacy risk but does not fulfill the right to erasure under GDPR if data is not fully anonymized.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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