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AI Governance and EthicseasyMultiple ChoiceObjective-mapped

AI0-001 AI Governance and Ethics Practice Question

An AI ethics board is reviewing a model that recommends criminal sentencing lengths. They want to ensure that the model's false positive rates for different demographic groups are equal. Which fairness metric should they use?

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

Equalized odds

Equalized odds requires that the model's true positive rates and false positive rates are equal across groups. Demographic parity only requires equal selection rates. Individual fairness ensures similar individuals are treated similarly but does not define group rates. Calibration ensures predicted probabilities match actual outcomes for each group but does not enforce equal error rates.

Answer analysis

Option-by-option breakdown

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

  • Calibration

    Why it's wrong here

    Calibration ensures that predicted probabilities correspond to actual outcomes per group, but does not address false positive rate equality.

  • Individual fairness

    Why it's wrong here

    Individual fairness requires similar individuals to receive similar predictions, but does not consider group-level error rates.

  • Equalized odds

    Why this is correct

    Equalized odds requires both false positive rates and true positive rates to be equal across groups.

  • Demographic parity

    Why it's wrong here

    Demographic parity requires equal outcome rates across groups, not equal error rates.

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.

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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.