Limits, risks, and responsible use

Useful tools still need boundaries. Responsible use is mostly habits, not legalese.

Privacy

Don’t paste secrets: passwords, private keys, confidential work docs, health details, or other people’s personal data — unless you fully trust the product’s policy and your organization’s rules. Prefer redaction and synthetic examples when exploring.

Copyright-ish caution

Models may echo patterns from training data. Don’t treat generated text or images as automatically free to publish as your original work in every context. When in doubt, rewrite, attribute sources you used, and follow your local rules.

Bias and uneven quality

Outputs can reflect stereotypes or overconfident generalizations. Ask for alternatives, check who might be harmed by a careless answer, and don’t outsource judgment about people.

When not to trust the answer

• Medical, legal, or financial decisions without a qualified human.
• Citations you haven’t opened.
• Anything you’d need to defend under scrutiny.

Takeaway

Two habits transfer everywhere: minimize sensitive input, and verify high-stakes output.