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AI Security, Ethics and GovernancemediumMultiple ChoiceObjective-mapped

AI0-001 AI Security, Ethics and Governance Practice Question

You are an AI governance officer at a bank that uses a machine learning model to predict credit risk. The model was developed by an external vendor and uses a proprietary algorithm. The bank's compliance team has determined that the model must be explainable to meet regulatory requirements. However, the vendor claims the model is a 'black box' and cannot provide explanations. You need to ensure compliance while maintaining the model's performance. What is the best course of action?

⚠ Common exam trap

It's easy for candidates to assume that a 'black box' model cannot be explained at all, leading them to choose replacement with a simpler model (Option C), when in fact model-agnostic techniques like SHAP or LIME can provide explanations without altering the model itself.

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 a model-agnostic explanation technique like SHAP

D is correct because model-agnostic explanation techniques like SHAP (SHapley Additive exPlanations) can provide post-hoc interpretability for any black-box model without requiring access to its internal structure or proprietary algorithm. This allows the bank to meet regulatory explainability requirements while preserving the vendor's proprietary model and its predictive performance.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Ignore the requirement as the model is proprietary

    Why it's wrong here

    Regulatory compliance is mandatory; ignoring is not an option.

  • Ask the vendor to develop a custom explanation module

    Why it's wrong here

    Vendor already indicated impossibility; custom module may not be feasible.

  • Replace the model with a simpler, interpretable model

    Why it's wrong here

    Simpler models may have lower performance, impacting business.

  • Use a model-agnostic explanation technique like SHAP

    Why this is correct

    SHAP provides explanations for any model, satisfying regulatory needs.

About these practice questions

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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.