AI0-001 AI Governance and Ethics Practice Question
During an audit of an AI system, the auditor requests documentation on the model's intended use, performance metrics, and limitations. Which tool is designed to provide this information in a standardized format?
⚠ Common exam trap
AI0-001 often tests the confusion between explainability techniques (SHAP, LIME) and documentation artifacts (model cards, data cards) — candidates must recognize that the auditor is asking for standardized documentation, not a prediction-explanation method.
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
✓
Model card
A model card is a standardized document that describes a model's intended use, performance metrics, limitations, ethical considerations, and other relevant details. It is specifically designed to provide transparency and accountability documentation for AI models, matching the auditor's request. Model cards were popularized by Google and are now a common governance artifact.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
SHAP values
Why it's wrong here
SHAP values quantify each feature's contribution to an individual prediction, explaining model output rather than documenting intended use, metrics or limitations. It would be the correct choice when an auditor needs local feature-attribution evidence for a specific prediction, not standardised model-level documentation.
- ✗
LIME
Why it's wrong here
LIME generates local surrogate explanations showing which features influenced a single prediction, producing no standardised model-level documentation. It would be the correct tool when an auditor needs to understand why one specific prediction was made, not the model's intended use, metrics and limitations.
- ✓
Model card
Why this is correct
A model card is the standardised artefact documenting a model's intended use, performance metrics and limitations, directly satisfying the auditor's request. Unlike datasheets, which describe training datasets, model cards address the deployed model itself, giving the transparency evidence required for AI governance audits.
- ✗
Data card
Why it's wrong here
A data card documents a dataset's provenance, composition, collection methods and preprocessing, not the model's intended use, performance metrics or limitations. It would be the correct artefact when an auditor requests standardised documentation about the training or evaluation data itself rather than the model.
About these practice questions
Courseiva writes every AI0-001 question from scratch — 962 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
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.