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Check a course or employer AI policy before using a model on assessed or confidential work.
8 Responsible AI Writing Examples
Use these examples to study structure, specificity, tone, and variation. They are demonstrations—not claims about a real person or organization unless the example itself makes that explicit.
Before you copy
What to notice in the examples
Responsible practice begins with the governing rules and risk of the task, uses AI only where appropriate, minimizes sensitive input, verifies outputs, respects source and authorship requirements, and keeps a human accountable for the final communication.
- Define the human objective, source material, audience, and constraints before asking an AI system to contribute.
- Use the model for a bounded transformation or analysis task while preserving this guardrail: follow the applicable policy, protect sensitive information, verify outputs, and keep a human accountable.
- Finish with human verification, rewriting, source checks, and accountability for the final wording rather than treating model output as publication-ready.
2
Do not upload private client documents to a tool that your organization has not approved for that data.
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Verify model-generated factual claims with reliable sources before publishing.
4
Disclose AI assistance when a publisher, client, institution, or platform requires it.
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Do not present generated quotations, citations, interviews, or firsthand experiences as real.
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Use AI to critique your draft rather than impersonating a person whose consent you do not have.
7
Keep records of source material and substantive human decisions for high-stakes or regulated writing.
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When policy is unclear, choose a lower-risk workflow such as brainstorming nonfactual options or editing text you already wrote.
Keep the underlying decision or pattern, then replace the subject, evidence, relationship, constraints, and tone with details that belong to your situation. If your final line still works after swapping only one noun, it may be too close to the example.