AI0-001 AI Governance and Ethics Practice Question
A company is required to disclose that content has been generated or significantly modified by AI. Which practice directly addresses this transparency obligation?
⚠ Common exam trap
The AI0-001 exam often tests the distinction between transparency of content origin (watermarking) and model transparency (model cards) or interpretability (LIME), leading candidates to confuse documentation with active disclosure mechanisms.
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
✓
Applying AI watermarking
AI watermarking directly addresses the transparency obligation by embedding a detectable signal into AI-generated content, enabling clear disclosure that the content was produced or significantly modified by AI. This practice aligns with regulatory requirements for provenance and traceability, as watermarks can be verified by automated systems or human inspection to confirm AI origin.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Applying AI watermarking
Why this is correct
AI watermarking embeds a detectable signal into generated content, enabling disclosure that material was AI-generated or modified. This directly satisfies the stem's transparency obligation, unlike consent, retention or accuracy controls that address different AI governance concerns.
- ✗
Using LIME for explanations
Why it's wrong here
LIME explains individual model predictions to developers and auditors; it produces no user-facing label, watermark or disclosure statement. It is tempting because explainability supports accountability, and would be correct where the requirement is interpreting why a model produced a given output rather than declaring AI involvement.
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Implementing federated learning
Why it's wrong here
Federated learning trains models across decentralised data without centralising it, addressing privacy and data-residency concerns. It is tempting because it is an AI governance practice, and would be correct where the requirement is keeping training data on-device rather than informing recipients that content is AI-generated.
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Publishing a model card
Why it's wrong here
A model card documents a model's intended use, training data and performance for reviewers; it does not mark or label deployed output. It is tempting because it is a recognised transparency artefact, and would be correct where the obligation is disclosing model characteristics to stakeholders rather than flagging AI-generated content.
About these practice questions
One of 962 original AI0-001 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
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.