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Guidelines for using AI.

Guidelines for using AI.

These guidelines are offered for information only.

Artificial intelligence is becoming a daily tool for businesses, educators, and individuals — but using it responsibly requires clarity and care. The following overview summarizes widely recognized best practices for safe, ethical, and transparent AI use. These principles are drawn from commonly accepted industry standards and public guidance across multiple organizations. They are provided here for general informational purposes to help our users understand how to work with AI tools in a way that protects privacy, maintains accountability, and promotes fairness.

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Note” Numbers in the [ ] are links to other references for your reference

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AI guidelines are a set of principles designed to ensure the safe, ethical, and responsible use of artificial intelligence. While policies vary by organization, the core foundation rests on privacy, accountability, transparency, and fairness.

Adhere to these universal best practices when interacting with AI tools:

1. Data Privacy & Security

  • Never enter confidential or sensitive information: Avoid inputting proprietary business data, personal health information (HIPAA), or student records (FERPA).
  • Opt-out of training data: Check settings to ensure your inputs are not being used to train the platform’s future public models.
  • Scrub personal details: Remove any personally identifiable information (PII) before prompting.

2. Human Accountability

  • Verify all outputs: AI models can hallucinate (generate confident but false information). You are ultimately responsible for the factual accuracy of your work. [1, 2]
  • Maintain editorial control: Use AI to assist with brainstorming, outlining, or editing, rather than relying on it to write entirely autonomous, end-to-end original work. [1]

3. Transparency

  • Disclose AI use: If you publish or share content that is heavily influenced or generated by AI, clearly label or disclose its usage to your audience.
  • Respect intellectual property: Do not use AI to generate work that infringes upon existing copyrights or software licenses.

4. Fairness & Bias

  • Mitigate biases: Be aware that AI can inherit biases from its training data. Challenge the AI’s conclusions and cross-reference multiple sources to avoid blind spots.