Generative AI Leader Google Cloud's Generative AI Offerings Practice Question
A company is using Vertex AI Gemini API to analyze customer feedback. They notice that the model occasionally generates offensive content. They have already set safety settings to block high-probability harmful content. What additional step should they take to further reduce offensive outputs?
⚠ Common exam trap
Candidates often assume fine-tuning (Option D) is the default fix for any output quality issue, but safety filtering is a separate, configurable layer that should be tuned before retraining, and temperature (Option A) is often mistakenly thought to control safety when it only controls randomness.
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
✓
Adjust safety settings to block medium-probability harmful content
The company has already blocked high-probability harmful content, but offensive outputs can still occur at lower probability thresholds. By adjusting safety settings to block medium-probability harmful content, they tighten the filter to catch more borderline cases without requiring model retraining or sacrificing output diversity. This leverages Vertex AI's configurable safety filters, which operate on likelihood categories (e.g., high, medium, low) rather than just binary blocking.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Set the temperature to 0.0
Why it's wrong here
Reduces randomness but not safety.
- ✓
Adjust safety settings to block medium-probability harmful content
Why this is correct
Stricter thresholds block more offensive outputs.
- ✗
Enable context caching
Why it's wrong here
Does not filter outputs.
- ✗
Fine-tune the model on customer feedback data
Why it's wrong here
Fine-tuning may not eliminate offensive content and could introduce bias.
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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.