Generative AI Leader Fundamentals of Generative AI Practice Question
A company is deploying a generative AI model for medical advice. What is the most important consideration?
⚠ Common exam trap
Google Cloud often tests the misconception that technical performance metrics like latency or cost are the primary concerns in high-stakes domains, when in fact ethical and safety considerations take precedence.
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
✓
Safety and fairness
In medical advice applications, a generative AI model's outputs can directly impact patient health, making safety and fairness the paramount consideration. Incorrect or biased advice could lead to misdiagnosis or harm, outweighing performance metrics like latency or cost. Regulatory frameworks such as HIPAA and FDA guidelines for clinical decision support further mandate rigorous validation of model safety and fairness before deployment.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Model latency
Why it's wrong here
While important, it is secondary to safety in medical contexts.
- ✓
Safety and fairness
Why this is correct
Patient safety and avoiding bias are the top priorities.
- ✗
Model size
Why it's wrong here
Model size affects cost, but safety is paramount.
- ✗
Cost of inference
Why it's wrong here
Cost is a business consideration, not the most important for medical advice.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.