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What to do first when an AI response may cause harm
- Pause reliance and sharing. Do not use the response to make a consequential decision or publish it while its accuracy and effects are uncertain. Avoid reposting harmful material, which can spread it further. The FTC cautions against treating AI as a solution to harmful online content; its June 2022 report announcement describes limitations including inaccuracy, bias, and missing context.
- Check the claims. Compare factual statements with original documents, authoritative sources, and, where needed, a qualified person. Do not treat a confident tone as proof. NIST identifies validity and reliability as elements of trustworthy AI; its AI Risk Management Framework describes a voluntary approach to considering trustworthiness across AI design, deployment, use, and evaluation.
- Protect information. Do not enter more personal, confidential, or organizational data to reproduce or diagnose the problem. If the output appears to expose such information, stop circulating it and follow the relevant privacy or security incident process.
- Report the response. Use the product’s reporting feature if one is available. At work, follow internal policy and contact the designated privacy, security, safety, or AI oversight official. Preserve only enough context to explain the concern, such as the tool, approximate time, prompt, output, and why it matters; limit unnecessary copying or retention of sensitive material.
- Escalate in proportion to the harm. Seek human review for suspected discrimination, privacy exposure, or high-stakes effects. If there is an immediate threat, focus on the affected person’s safety and use appropriate local emergency or support services. Reporting routes and legal duties vary by tool, organization, harm, and location.
Choose the right response for the type of harm
| Situation | First response | Escalation |
|---|---|---|
| Possible factual error | Hold use or sharing; check original sources and qualified reviewers. | Ask the responsible person or organization to correct any consequential decision or publication. |
| Biased or discriminatory content | Pause reliance and retain limited context that explains the concern. | Report it to the tool owner or relevant organizational review channel; consider who may be affected. NIST warns that AI can increase the speed and scale of harmful bias in its bias overview. |
| Possible exposure of sensitive information | Stop entering sensitive data and avoid spreading the exposed material. | Use the applicable organizational privacy or security incident process. Examples include Indiana FSSA guidance for state business and CMS workforce guidance; these are institutional procedures, not universal consumer rules. |
| Severe or immediate harm | Prioritize the affected person’s safety and do not amplify harmful content. | Report through the platform and use suitable local support or emergency channels. UNESCO’s guidance addresses technology-facilitated gender-based violence specifically, including prompt response and limiting further engagement with harmful material. |
How to verify misleading content
Identify the specific claims that could affect a decision, a person, or public understanding. Trace them to primary material where possible—such as the original document, dataset, announcement, or record—rather than relying on another AI summary. For specialized or high-stakes matters, ask a qualified professional or responsible human reviewer to assess the evidence and context.
AI can miss context, reproduce bias, or provide inaccurate information. NIST’s trustworthiness overview includes validity and reliability alongside safety, security, accountability, transparency, privacy, and fairness. These are useful evaluation concerns, not a guarantee that an individual output is correct.
How to report an AI response without spreading the harm
For a consumer tool, look for its current in-product feedback, report, or safety option. The exact label and route depend on the service. For an organizational system, use the institution’s own incident process rather than assuming the product’s feedback button reaches the people responsible for privacy, security, or safety.
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Describe what happened and why it is concerning, while sharing no more sensitive material than necessary. Workplace examples show why the route is context-specific: Indiana’s state-business guidance identifies an Agency Privacy Officer for inappropriate, biased, or harmful outputs, while CMS directs its workforce to report suspected or verified privacy breaches through its process. Neither establishes a universal procedure for consumers or other employers.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.When the output involves security or privacy
A response that appears to reveal personal or organizational information should be treated as a possible incident, not tested by supplying more data. Follow the privacy or security process that applies to the account, employer, or institution. Requirements differ across organizations and jurisdictions, so consult the responsible privacy or security official rather than assuming that deleting a prompt or reporting it to the AI vendor completes the response.
For developers, evaluators, deployers, and governance teams, NIST’s March 24, 2025 announcement of an adversarial machine-learning taxonomy covers attacks against generative AI and possible mitigations. It is technical risk-management context, not a consumer troubleshooting or emergency protocol.
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