AI0-001 AI Security, Ethics and Governance Practice Question
A financial services firm deploys an AI system to screen loan applications. The model was trained on historical data that reflected biased lending practices. After deployment, a regulatory body investigates and finds that the model denies loans at a disproportionately higher rate to a protected demographic group. The firm must address this issue while maintaining compliance with fair lending laws. The Chief AI Officer proposes four possible actions. Which action is the most appropriate first step?
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 using a debiased dataset and implement fairness-aware algorithms, then validate with fairness metrics
The most appropriate first step because it directly addresses the root cause of biased predictions by retraining the model on a debiased dataset and implementing fairness-aware algorithms. This proactive approach aligns with regulatory expectations to correct systemic bias. Option B (documenting) is reactive and does not fix the underlying issue. Option C (rule-based manual review) is inefficient, costly, and may still produce inconsistent decisions. Option D (disclosing to applicants) could be part of a remediation plan but is premature without first correcting the model.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Retrain the model using a debiased dataset and implement fairness-aware algorithms, then validate with fairness metrics
Why this is correct
This directly addresses the biased model and demonstrates a commitment to fairness.
- ✗
Document the model's predictions and submit a report to the regulator explaining the historical dataset bias
Why it's wrong here
Documentation is important but does not remediate the bias; the regulator expects corrective action.
- ✗
Immediately deploy a rule-based system to manually review all denial decisions from the AI system
Why it's wrong here
This is a temporary measure but does not solve the bias in the model itself.
- ✗
Disclose the bias findings to all rejected applicants and offer them priority reconsideration
Why it's wrong here
Transparency is good, but without actually fixing the model, the same bias will continue.
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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.