AI0-001 AI Models and Data Engineering Practice Question
A team is training a language model using a large text corpus. They want to ensure the model does not learn biased associations between gender and professions. Which data engineering technique should they apply?
⚠ Common exam trap
CompTIA AI often tests the distinction between data-level interventions (like balancing) and model-level interventions (like adversarial debiasing), trapping candidates who confuse training-time algorithms with data engineering techniques.
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
✓
Balance the representation of professions across genders
Balancing the representation of professions across genders in the training data directly addresses the root cause of biased associations. By ensuring that each profession appears with roughly equal frequency for all gender references, the model learns statistical correlations that are fair rather than skewed by imbalanced data. This is a fundamental data engineering technique for bias mitigation, as it prevents the model from encoding spurious correlations between gender and occupation.
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 all gender-related words from the text
Why it's wrong here
Removing gender words eliminates useful context and may not effectively debias.
- ✗
Use a pre-trained model that is already debiased
Why it's wrong here
Pre-trained models may still contain biases from their training data.
- ✗
Apply adversarial debiasing during training
Why it's wrong here
Adversarial debiasing is a training technique, not a data engineering preprocessing step.
- ✓
Balance the representation of professions across genders
Why this is correct
Balancing ensures the model sees equal examples of each gender across professions, reducing biased correlations.
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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.