AI0-001 AI Models and Data Engineering Practice Question
An organization uses a machine learning model to approve loans. The model shows higher false positive rates for a protected group. Which data engineering step should be taken to mitigate this?
⚠ Common exam trap
A common misconception tested in CompTIA AI is that removing the protected attribute is sufficient to eliminate bias, when in reality proxy features and correlated variables can perpetuate discrimination, making adversarial debiasing a more robust solution.
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 adversarial debiasing technique
Adversarial debiasing is a technique that trains the model to minimize prediction error while simultaneously preventing an adversary from predicting the protected attribute from the model's outputs. This directly reduces disparate impact by forcing the model to learn representations that are uncorrelated with the protected group, thereby lowering false positive rates for that group without simply removing the attribute.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Remove the protected attribute from training data
Why it's wrong here
Simply removing the attribute does not prevent proxy features from encoding the same bias.
- ✓
Use adversarial debiasing technique
Why this is correct
Adversarial debiasing forces the model to be invariant to protected attributes, reducing bias.
- ✗
Increase model complexity
Why it's wrong here
Increasing complexity often exacerbates overfitting and can amplify bias.
- ✗
Add synthetic data to balance groups
Why it's wrong here
Synthetic data can mitigate imbalance but may not address the root cause of disparate false positive rates.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA 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 AI0-001 exam.