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AI0-001 AI Governance and Ethics Practice Question

A health-tech firm is preparing a model card for a clinical decision support tool that flags patients at risk of sepsis. The compliance team asks which element of the model card is MOST directly relevant to documenting the system's intended use and out-of-scope applications. Which section should the team prioritize?

⚠ Common exam trap

The trap here is assuming that strong performance metrics or ethical review notes substitute for an explicit intended-use statement, when scope must be declared separately.

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

✓

The 'Intended Use' section, which specifies the clinical populations, care settings, and decision boundaries for which the model was validated.

A model card's intended use section is the formal declaration of the validated operating envelope: the populations, settings, and decision types the model supports, plus explicitly excluded uses. Compliance reviewers rely on it to confirm that a proposed deployment falls inside the validated scope. Training data, performance metrics, and ethical considerations are supporting evidence but do not define the boundary of appropriate use.

Answer analysis

Option-by-option breakdown

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

  • ✗

    The 'Performance Metrics' section, which reports AUROC, sensitivity, and specificity at the deployed decision threshold.

    Why it's wrong here

    Performance metrics quantify how well the model discriminates on a held-out set, but they are conditional on the evaluation population and threshold. They do not define the boundary of legitimate use or list excluded applications. A high AUROC on one cohort says nothing about whether the tool may be used in a different care setting, so this section is not the primary scope reference.

  • ✗

    The 'Training Data' section, which lists the source datasets, their collection dates, and demographic composition.

    Why it's wrong here

    Training data provenance is important for understanding potential bias and representativeness, but it describes inputs rather than the validated operating envelope. It does not by itself state which clinical settings or patient groups the model is cleared to support, so it cannot answer the compliance team's question about intended and out-of-scope applications as directly as the scope declaration does.

  • ✓

    The 'Intended Use' section, which specifies the clinical populations, care settings, and decision boundaries for which the model was validated.

    Why this is correct

    This section is the authoritative declaration of the model's scope. It records which patient populations, care environments, and decision types were validated, and explicitly lists out-of-scope uses such as autonomous diagnosis without clinician review. Without this, downstream users cannot judge whether deploying the tool in a new setting is appropriate, so it is the most directly relevant element for the compliance question.

  • ✗

    The 'Ethical Considerations' section, which discusses potential harms and mitigation strategies identified during review.

    Why it's wrong here

    Ethical considerations document identified risks and planned mitigations, which supports responsible deployment but does not itself define the validated scope. It may reference intended use, yet it is not the canonical statement of which populations and settings the model supports. The compliance team needs the explicit scope declaration, making this section secondary for their question.

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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

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