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Ethical Considerations of AIhardMultiple ChoiceObjective-mapped

AI Associate Ethical Considerations of AI Practice Question

A financial services firm uses Einstein Next Best Action to offer credit products. The model recommends high-interest loans more often to minority groups. The AI Associate must mitigate this. What is the most effective approach?

⚠ Common exam trap

It's easy for candidates to confuse explainability (SHAP values) with mitigation, thinking that understanding why bias occurs is sufficient to fix it, when in fact only direct adjustments to the model's output can change the biased recommendations.

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

Apply post-processing fairness adjustments to the recommendations.

Post-processing fairness adjustments directly modify the model's output to enforce demographic parity or equal opportunity, reducing biased recommendations without retraining the model. This approach is practical when the firm cannot easily change the underlying training data or model architecture, and it allows the AI Associate to intervene at the decision point to ensure fair lending practices.

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 model and use a rule-based system.

    Why it's wrong here

    Rule-based systems can also be biased and less effective.

  • Use SHAP values to explain predictions.

    Why it's wrong here

    Explanation does not change biased outcomes.

  • Apply post-processing fairness adjustments to the recommendations.

    Why this is correct

    This can equalize outcomes without full retraining.

  • Add a disclaimer that recommendations may be biased.

    Why it's wrong here

    Disclaimers do not mitigate harm.

Quick reference

RAID Level Comparison

RAID LevelMin DisksFault ToleranceReadWriteUsable Capacity
RAID 02NoneExcellentExcellent100%
RAID 121 diskGoodModerate50%
RAID 531 diskGoodModerate67–94%
RAID 642 disksGoodLower50–88%
RAID 1041 disk per mirrorExcellentGood50%

RAID is not a backup strategy — it protects against disk failure but not against accidental deletion, ransomware, or site-level events.

About these practice questions

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This AI Associate practice question is part of Courseiva's free Salesforce 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 AI Associate exam.