NCA-GENL Question 221
Select 4A team is deploying a large language model (LLM) for a healthcare application and wants to ensure the model generates trustworthy and unbiased outputs. Which of the following strategies leveraging NVIDIA and other technologies can help improve the AI system's trustworthiness?
- A
Use NVIDIA NeMo Guardrails to enforce responses that align with ethical and domain-specific guidelines.
- B
Train the model on diverse and high-quality datasets to minimize biases.
- C
Deploy the model on NVIDIA GPUs, as they inherently improve the ethical behavior of the model.
- D
Implement explainability techniques, such as SHAP or Integrated Gradients, to provide insights into the model's predictions.
- E
Monitor the model's behavior in production using NVIDIA Triton Inference Server with logging and alerting mechanisms.
Show answer and explanation
Correct answers: A, B, D, E
Explanation
Improving AI trustworthiness requires a combination of strategies, including leveraging NVIDIA tools like NeMo Guardrails for safe and ethical outputs, training on diverse datasets to minimize biases, implementing explainability techniques for transparency, and monitoring production behavior to ensure reliability. While NVIDIA GPUs enhance performance, they do not directly improve trustworthiness, making option 3 incorrect.
- A. Correct.
NVIDIA NeMo Guardrails is specifically designed to ensure that LLMs generate safe, accurate, and ethical responses, making it a key tool for improving trustworthiness.
- B. Correct.
Training on diverse and high-quality datasets helps reduce biases, ensuring that the model's behavior is fair and reliable.
- C. Incorrect.
While NVIDIA GPUs provide performance optimizations, they do not directly influence the ethical behavior of the model.
- D. Correct.
Explainability techniques like SHAP and Integrated Gradients help users understand why a model made a certain decision, enhancing trust and transparency.
- E. Correct.
Monitoring the model in production using tools like NVIDIA Triton Inference Server ensures any issues, such as drift or bias, can be identified and addressed in real time.