Responsible generative AI practices: Practice Questions — Trustworthy AI (NVIDIA-Certified Associate: Generative AI LLM)

Practice Questions on Responsible Generative AI Practices

These multiple-choice questions are designed to help candidates prepare for the Trustworthy AI section of the NVIDIA-Certified Associate: Generative AI LLM exam, focusing specifically on responsible generative AI practices.

1. Which of the following is a key principle of responsible generative AI development?

   • A. Maximizing output speed regardless of content quality
   • B. Ensuring transparency and explainability of AI-generated content
   • C. Prioritizing model complexity over user safety
   • D. Ignoring user feedback to maintain model integrity

   Correct Answer: B

   Explanation: Transparency and explainability help users understand how AI generates content, which is essential for trust and accountability in responsible AI.

2. What is an effective practice to reduce harmful biases in generative AI models?

   • A. Training exclusively on unfiltered internet data
   • B. Ignoring ethical guidelines to improve creativity
   • C. Incorporating diverse and representative datasets during training
   • D. Allowing unrestricted content generation without moderation

   Correct Answer: C

   Explanation: Using diverse and representative datasets helps mitigate bias and promotes fairness in AI-generated outputs.

3. Which approach best supports safe deployment of generative AI applications?

   • A. Deploying models without monitoring to speed up release
   • B. Implementing continuous monitoring and user feedback loops
   • C. Disabling content filters to enhance creativity
   • D. Avoiding updates to prevent model drift

   Correct Answer: B

   Explanation: Continuous monitoring and incorporating user feedback help detect and address unsafe or inappropriate outputs promptly.

4. Why is it important to align generative AI models with user values and societal norms?

   • A. To limit the model’s usefulness
   • B. To ensure outputs are ethical, relevant, and socially acceptable
   • C. To reduce model accuracy
   • D. To increase computational cost

   Correct Answer: B

   Explanation: Alignment ensures AI-generated content respects ethical standards and societal expectations, fostering trust and acceptance.

5. Which of the following is a responsible practice when handling user data in generative AI systems?

   • A. Collecting data without user consent
   • B. Anonymizing data and securing user privacy
   • C. Sharing user data freely with third parties
   • D. Ignoring data protection regulations

   Correct Answer: B

   Explanation: Protecting user privacy through anonymization and compliance with data protection laws is essential for responsible AI use.

6. What role do content moderation mechanisms play in responsible generative AI?

   • A. They restrict all user creativity
   • B. They help prevent generation of harmful or inappropriate content
   • C. They slow down the AI response time unnecessarily
   • D. They are optional and rarely needed

   Correct Answer: B

   Explanation: Content moderation is critical to ensure AI outputs do not cause harm or spread misinformation.

7. How can developers ensure generative AI models remain trustworthy over time?

   • A. By never updating the model after deployment
   • B. By regularly auditing model outputs and retraining with updated data
   • C. By ignoring user complaints
   • D. By disabling logging and monitoring systems

   Correct Answer: B

   Explanation: Ongoing audits and retraining help maintain model accuracy, fairness, and safety as contexts evolve.

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