Question 878 of 997
Responsible AI and Data GovernancemediumMultiple SelectObjective-mapped

Generative AI Leader Responsible AI and Data Governance Practice Question

This Generative AI Leader practice question tests your understanding of responsible ai and data governance. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

A company is developing a generative AI application that will be used by customers in the EU. To comply with GDPR, which TWO measures are REQUIRED? (Choose 2)

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

Provide users the ability to request deletion of their personal data

Option A is correct because GDPR grants data subjects the 'right to erasure' (Article 17), requiring organizations to delete personal data upon request without undue delay. For a generative AI application, this means the company must be able to remove specific training data or user inputs from the model's memory or logs, which is technically challenging but legally mandatory.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Answer analysis

Option-by-option breakdown

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

  • Provide users the ability to request deletion of their personal data

    Why this is correct

    Right to erasure is a core GDPR right.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Implement end-to-end encryption for all data in transit and at rest

    Why it's wrong here

    Security is a requirement but encryption details are not explicitly mandated; it is a means to comply with security principle.

  • Publish a Model Card for the AI model

    Why it's wrong here

    Model Cards are not a GDPR requirement.

  • Ensure all data is stored in a data center within the EU

    Why it's wrong here

    Data residency may be required for certain data but not universally under GDPR.

  • Obtain explicit consent from users before processing their personal data

    Why this is correct

    Consent is a legal basis under GDPR.

    Related concept

    Read the scenario before looking for a memorised answer.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Google often tests the distinction between GDPR's explicit legal requirements (like consent and erasure) and common security or transparency practices (like encryption or Model Cards) that are recommended but not mandated, leading candidates to over-select options that seem 'good' but are not legally required.

Detailed technical explanation

How to think about this question

The right to erasure (Article 17) is particularly complex for generative AI models because personal data may be embedded in model weights through training, making complete deletion non-trivial. Techniques like machine unlearning or differential privacy can help, but GDPR does not prescribe specific methods; the burden is on the controller to demonstrate compliance. In practice, companies often implement data retention policies and input logging controls to isolate user data from the model's persistent state.

KKey Concepts to Remember

  • Read the scenario before looking for a memorised answer.
  • Find the constraint that changes the correct option.
  • Eliminate answers that are true in general but not in this case.

TExam Day Tips

  • Watch for words such as best, first, most likely and least administrative effort.
  • Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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FAQ

Questions learners often ask

What does this Generative AI Leader question test?

Responsible AI and Data Governance — This question tests Responsible AI and Data Governance — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Provide users the ability to request deletion of their personal data — Option A is correct because GDPR grants data subjects the 'right to erasure' (Article 17), requiring organizations to delete personal data upon request without undue delay. For a generative AI application, this means the company must be able to remove specific training data or user inputs from the model's memory or logs, which is technically challenging but legally mandatory.

What should I do if I get this Generative AI Leader question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jul 4, 2026

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This Generative AI Leader practice question is part of Courseiva's free Google Cloud 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 Generative AI Leader exam.