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AI0-001 AI Governance and Ethics Practice Question

A company is forming an AI ethics board to oversee the development of a high-stakes AI system for bail decision recommendations. Which THREE responsibilities should the board primarily undertake?

⚠ Common exam trap

AI0-001 often tests the boundary between governance and engineering — candidates pick 'write production code' or 'market the system' because they sound like responsibilities, but ethics boards set policy and review outcomes, not build or sell.

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

✓

Review model outputs for disparate impact across demographic groups

Option A is correct because an AI ethics board overseeing a bail recommendation system must audit model outputs for disparate impact across demographic groups, since bail decisions are legally and ethically sensitive and bias can violate anti-discrimination requirements. Option C is correct because the board should establish human-in-the-loop requirements for high-risk decisions, ensuring that consequential bail recommendations are reviewed by a qualified human rather than fully automated. Option D is correct because the board must define fairness criteria and acceptable bias thresholds, giving the organization measurable standards for evaluating whether the system's outputs are equitable. Option B is not a primary ethics-board responsibility because marketing the system to clients is a commercial function, not ethical oversight. Option E is not appropriate because writing production code is an engineering task, and the board should provide governance, review, and policy direction rather than implementation work.

Answer analysis

Option-by-option breakdown

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

  • ✓

    Review model outputs for disparate impact across demographic groups

    Why this is correct

    Reviewing outputs for disparate impact directly addresses the fairness constraint inherent in bail recommendations, where historical arrest data can encode racial bias. The board examines error rates and outcome distributions across demographic groups, catching discriminatory patterns that accuracy metrics alone conceal. This satisfies the stem's high-stakes oversight requirement by providing ongoing, evidence-based scrutiny of deployed model behaviour.

  • ✗

    Market the AI system to potential clients

    Why it's wrong here

    Marketing falls outside ethics-board oversight, which covers risk assessment, bias auditing and accountability for the bail model. It is tempting because boards do sometimes advise on stakeholder communication, but commercial promotion conflicts with independent ethical scrutiny of a high-stakes system.

  • ✓

    Establish human-in-the-loop requirements for high-risk decisions

    Why this is correct

    Establishing human-in-the-loop requirements directly addresses the high-stakes bail context, where automated recommendations could wrongly affect liberty. The board ensures a qualified human reviews and can override each high-risk recommendation before it influences a decision, satisfying the stem's oversight constraint for consequential AI outcomes.

  • ✓

    Define fairness criteria and acceptable bias thresholds

    Why this is correct

    Defining fairness criteria and acceptable bias thresholds directly addresses the bail scenario's legal and ethical exposure, where disparate impact on protected groups carries liability. The board must translate abstract equity goals into measurable metrics, such as demographic parity or equalised odds, so the system's outputs can be audited against concrete tolerances before deployment.

  • ✗

    Write the production code for the AI model

    Why it's wrong here

    Writing production code is an engineering task, not governance; board members must remain independent of implementation to review it objectively. It is tempting because technical expertise helps the board evaluate feasibility, but that input comes through review and advice, while the board's remit covers oversight, policy and accountability.

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JA

Written and reviewed by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

Last reviewed September 2026 · checked against the official CompTIA exam blueprint

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.