AI0-001 AI Governance and Ethics Practice Question
A data scientist is evaluating a binary classifier for a hiring tool. They compute demographic parity and find that the selection rate for Group A is 0.2 and for Group B is 0.4. Which action would MOST directly address this disparity?
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
✓
Retrain the model with a fairness constraint that enforces demographic parity
Demographic parity requires equal selection rates. Retraining with a fairness constraint that enforces demographic parity directly adjusts the model to achieve equal rates. Rebalancing the dataset (if the disparity stems from imbalanced labels) might help, but it does not guarantee parity. Modifying thresholds can also achieve parity, but post-processing without retraining may degrade other metrics; retraining with constraint is more direct.
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 different evaluation metric such as equalized odds
Why it's wrong here
Changing metrics does not fix the disparity; it only changes what is measured.
- ✗
Remove the sensitive attribute from the training data
Why it's wrong here
Removing the attribute may reduce direct discrimination but can still lead to disparate impact via proxy features.
- ✗
Collect more data for Group A to increase its representation
Why it's wrong here
Collecting more data may help, but it does not guarantee equal selection rates without changing the model.
- ✓
Retrain the model with a fairness constraint that enforces demographic parity
Why this is correct
Enforcing demographic parity during training directly addresses the disparate selection rates.
Quick reference
RAID Level Comparison
| RAID Level | Min Disks | Fault Tolerance | Read | Write | Usable Capacity |
|---|---|---|---|---|---|
| RAID 0 | 2 | None | Excellent | Excellent | 100% |
| RAID 1 | 2 | 1 disk | Good | Moderate | 50% |
| RAID 5 | 3 | 1 disk | Good | Moderate | 67–94% |
| RAID 6 | 4 | 2 disks | Good | Lower | 50–88% |
| RAID 10 | 4 | 1 disk per mirror | Excellent | Good | 50% |
RAID is not a backup strategy — it protects against disk failure but not against accidental deletion, ransomware, or site-level events.
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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.