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AI Concepts and FoundationshardMultiple ChoiceObjective-mapped

AI0-001 AI Concepts and Foundations Practice Question

A company develops an AI model that recommends job candidates. The model inadvertently discriminates against a protected group. Which approach is most effective for mitigating this bias?

⚠ Common exam trap

CompTIA often tests the misconception that removing a protected attribute from training data is sufficient to eliminate bias, but the trap is that models can still discriminate through correlated proxy features, making fairness-aware algorithms necessary.

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 fairness-aware machine learning algorithm

Fairness-aware machine learning algorithms explicitly incorporate fairness constraints or objectives during model training, directly addressing and mitigating bias against protected groups. Unlike simple removal of protected attributes, these algorithms can detect and correct for proxy discrimination and disparate impact, ensuring the model's recommendations are equitable by design.

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 protected attribute from the training data

    Why it's wrong here

    Other correlated features may still encode bias; removal is insufficient.

  • Use a fairness-aware machine learning algorithm

    Why this is correct

    Fairness-aware algorithms incorporate constraints to reduce disparate impact.

  • Analyze model predictions after deployment

    Why it's wrong here

    Post-hoc analysis only identifies bias; it does not prevent it.

  • Collect more training data from the protected group

    Why it's wrong here

    More data does not inherently reduce bias if the underlying patterns are biased.

About these practice questions

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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.