CCAR-P Governance, Safety, and Risk Management Practice Question
A startup is using Claude to generate marketing copy. The legal team is concerned about potential copyright infringement if the model reproduces copyrighted text. Which governance measure should the startup implement to best mitigate this risk?
⚠ Common exam trap
The trap here is assuming that technical settings like temperature or fine-tuning can prevent copyright infringement, when in fact external verification is needed.
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
✓
Use a plagiarism detection tool to scan all generated content before publication.
The plagiarism detection tool is the most direct mitigation because it actively checks generated content against known copyrighted works and flags potential matches. This allows human review and modification before publication. Other options either do not prevent infringement or are ineffective, such as disclaimers or temperature adjustments.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Include a disclaimer that any resemblance to existing works is coincidental.
Why it's wrong here
A disclaimer does not absolve the startup of legal liability for copyright infringement. It is not a preventive control and would not mitigate the risk of reproducing copyrighted text. The legal team requires a measure that actively reduces the chance of infringement, not just a notice.
- ✗
Set the model's temperature to zero to ensure deterministic outputs.
Why it's wrong here
Lowering temperature reduces randomness but does not prevent the model from reproducing copyrighted material from its training data. Deterministic outputs could still infringe. This setting affects creativity, not copyright compliance, so it does not address the legal team's concern.
- ✓
Use a plagiarism detection tool to scan all generated content before publication.
Why this is correct
A plagiarism detection tool compares generated content against a vast database of copyrighted works and can flag potential infringements. This allows the startup to review and modify problematic outputs before publication, directly mitigating the risk of reproducing copyrighted text. It is a practical and effective control for this scenario.
- ✗
Fine-tune Claude on the startup's own proprietary content to avoid using external data.
Why it's wrong here
Fine-tuning on proprietary content does not eliminate the risk that the model might still generate copyrighted material from its pre-training. It may even amplify specific styles but does not guarantee avoidance of infringement. This approach is costly and does not directly address the concern of reproducing external copyrighted text.
About these practice questions
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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 Anthropic exam blueprint
This CCAR-P practice question is part of Courseiva's free Anthropic 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 CCAR-P exam.