Generative AI Leader Practice Question: Business Strategies for Generative AI Solutions
A company's generative AI model is producing biased outputs. What is the most effective mitigation strategy?
⚠ Common exam trap
Google Cloud often tests the misconception that prompt engineering or model scaling alone can fix bias, when in fact only retraining or fine-tuning with balanced data addresses the underlying weight distribution.
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
✓
Fine-tune the model using a balanced, representative dataset and implement output filtering
Fine-tuning on a balanced, representative dataset directly addresses the root cause of biased outputs by correcting the model's learned associations, while output filtering provides a safety net to catch residual bias. This combination is more effective than superficial fixes because it modifies the model's internal weights rather than just masking outputs.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use a larger model with more parameters to improve overall accuracy
Why it's wrong here
Larger models can still be biased; parameter count does not address bias directly.
- ✓
Fine-tune the model using a balanced, representative dataset and implement output filtering
Why this is correct
Balanced data reduces bias during training, and filters catch biased outputs in production.
- ✗
Use prompt engineering to instruct the model to avoid biased language
Why it's wrong here
Prompt engineering can reduce but not eliminate bias if the model's training data is skewed.
- ✗
Increase the diversity of input samples by random sampling
Why it's wrong here
Random sampling does not guarantee balanced representation of all groups.
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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.