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Ethical Considerations of AImediumMultiple ChoiceObjective-mapped

AI Associate Ethical Considerations of AI Practice Question

An AI model for predicting employee performance is found to have a higher false positive rate for women than for men. What is the best course of action?

⚠ Common exam trap

Salesforce often tests the misconception that adjusting thresholds or adding manual review can fix bias, when in fact these are superficial patches that do not address the root cause in the model's training data or architecture.

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

Investigate the cause and retrain the model to reduce bias

A higher false positive rate for women indicates the model has learned biased patterns from the training data, likely due to imbalanced or skewed historical data. Investigating the cause—such as examining feature correlations, data distribution, and model architecture—allows for targeted retraining (e.g., reweighting, adversarial debiasing, or fairness constraints) to reduce bias without sacrificing overall performance. This aligns with ethical AI principles and regulatory expectations, ensuring the model is fair across demographic groups.

Answer analysis

Option-by-option breakdown

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

  • Investigate the cause and retrain the model to reduce bias

    Why this is correct

    Retraining with fairness constraints mitigates bias.

  • Lower the decision threshold for women to equalize false positive rates

    Why it's wrong here

    Adjusting thresholds without addressing model bias is not a true fix.

  • Proceed with deployment because the overall accuracy is acceptable

    Why it's wrong here

    High overall accuracy can mask disparate impact.

  • Use the model but require manual review for all female candidates

    Why it's wrong here

    Manual review is inefficient and may introduce human bias.

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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.