Generative AI Leader Fundamentals of Generative AI Practice Question
A company is using Vertex AI to generate personalized marketing emails. The model sometimes produces biased content. What is the most effective way to detect and mitigate bias?
⚠ Common exam trap
Google Cloud often tests the misconception that bias mitigation is solely a data quantity problem, leading candidates to choose 'add more diverse training data' without recognizing the need for diagnostic tools like Explainable AI to first detect and understand the bias.
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
✓
Use Vertex AI Explainable AI to analyze predictions and detect bias in training data
Vertex AI Explainable AI provides feature attributions and model explanations that help identify which input features (e.g., demographic attributes, phrasing patterns) contribute most to biased outputs. By analyzing these attributions against training data, you can pinpoint and mitigate bias at the source, rather than relying on post-hoc manual review or model swapping.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Add more diverse training data
Why it's wrong here
May not address existing biases without analysis.
- ✗
Manually review all generated emails before sending
Why it's wrong here
Not scalable for large volumes.
- ✗
Switch to a different generative model
Why it's wrong here
Other models may also have bias.
- ✓
Use Vertex AI Explainable AI to analyze predictions and detect bias in training data
Why this is correct
Explainable AI helps identify bias sources.
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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.