AI0-001 AI Governance and Ethics Practice Question
A company trains a large language model on a dataset that includes copyrighted books. Under current legal interpretations, which statement about copyright infringement is MOST accurate?
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
✓
Training on copyrighted data without permission likely infringes copyright, though fair use may be a defense.
Training on copyrighted works without permission is generally considered copyright infringement, unless a specific exception applies (e.g., fair use in the US). Fair use is determined on a case-by-case basis and is not automatically granted. Using only public domain works avoids infringement. The EU AI Act does not provide blanket permission.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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Training on copyrighted data is generally permissible under the EU AI Act.
Why it's wrong here
The EU AI Act does not address copyright; it focuses on risk management.
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Training on copyrighted data is always covered by fair use in the US.
Why it's wrong here
Fair use is a defense, not an automatic right; many cases are still being litigated.
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Training on copyrighted data is allowed as long as the model is not used commercially.
Why it's wrong here
Non-commercial use does not automatically excuse infringement.
- ✓
Training on copyrighted data without permission likely infringes copyright, though fair use may be a defense.
Why this is correct
Copyright law protects original works; using them for training without permission is prima facie infringement, but fair use may apply.
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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.