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If an AI system gives advice or takes an action that could hurt someone, stop relying on the result. Make the situation safe first, obtain a qualified human review, preserve a factual record, and report the incident to the organization that operates or used the system. The right escalation—professional, organizational, regulatory or emergency—depends on the harm, the sector, the system and your jurisdiction.
Start with the potential harm, not the technology
An unsafe output can be a fabricated fact, dangerous instruction, discriminatory recommendation, privacy exposure, security weakness or an automated decision that unfairly affects a person. You do not need to prove exactly why the system failed before taking precautions. Treat the possible consequence as the deciding factor.
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| Situation | First response | Next escalation |
|---|---|---|
| Immediate risk of injury, death or serious damage | Stop the AI-guided action and move people away from danger if you can do so safely. | Use applicable emergency, clinical, workplace-safety or other sector procedures immediately; do not wait for a provider reply. |
| High-stakes advice that is not an immediate emergency | Do not act on the output as an authority. | Ask a suitably qualified professional or authoritative service to check the facts and recommend the decision. |
| Potential privacy, security or financial harm | Contain access, transactions or disclosure where possible. | Notify the responsible organization, security or fraud contact, and any relevant authority required by the circumstances. |
| Offensive, biased or otherwise harmful content with no immediate physical danger | Stop sharing or using the content in the affected process. | Report it to the operator and, when an organization deployed the system, request a human review. |
NIST’s AI Risk Management Framework treats safety, security, reliability, privacy, fairness, transparency and accountability as connected properties. It also says that context and severity matter: a mistake that is tolerable in a creative exercise may be unacceptable in a medical, employment, financial or safety decision.
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- Pause the action. Do not send the message, administer the treatment, approve the payment, publish the allegation, disable the safeguard or make the personnel decision solely because an AI system suggested it.
- Protect people and systems. If there is a physical hazard, follow the applicable emergency or workplace procedure. If an account, device or data set may be compromised, disconnect or restrict access using your organization’s incident process. Avoid taking a risky technical step you are not qualified to perform.
- Get a human decision-maker. Contact the professional or responsible manager who can evaluate the facts: for example, a clinician for medical advice, a lawyer for legal consequences, a finance professional for a transaction, or a safety officer for an operational hazard. Ask the person to assess the underlying situation, not merely to approve the AI answer.
- Preserve only what is necessary. Save the relevant prompt, output, date and time, system or model name if shown, settings or attached material, and the action taken or considered. Keep the record factual and secure.
- Report through the responsible route. Use the provider’s safety, support or complaint channel. If the output was generated inside a company, school, hospital, government service or other organization, notify that organization as well and request human review or an explanation where such an option exists.
For imminent danger, emergency or sector-specific procedures take priority over troubleshooting the software. A provider response cannot make an unsafe situation safe in real time.
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How to decide whether an output is consequential
Medical and personal safety decisions
An AI response about symptoms, medication, dosage, self-harm, violence, food safety or equipment operation can create immediate risk. Treat it as unverified information. Contact an appropriate health professional, poison-control service, crisis resource or emergency service for your location, depending on the facts. Do not delay urgent care while trying additional prompts or waiting for an automated moderation review.
Legal, financial and employment decisions
Generated legal citations, tax calculations, investment claims, credit assessments, hiring scores and disciplinary recommendations may be wrong or incomplete. Have a qualified person check the primary documents and the facts of the case. If an organization used AI to decide something about you, ask which human decision-maker is responsible, request a review of the underlying information and keep copies of notices or records you are allowed to retain. The availability of a formal appeal or explanation varies by sector and jurisdiction.
Security and technical operations
Code or commands can delete data, expose credentials, weaken access controls or disrupt a production system. Do not run an unverified command on a live environment. Use an approved change process, test in an isolated environment and involve a qualified administrator or security team. If secrets may have been exposed, follow your organization’s credential-rotation and incident-response procedures rather than pasting the secrets into another chatbot.
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How to document an unsafe AI incident
A concise record helps a human reviewer reproduce the problem and helps an organization investigate patterns. This is practical incident documentation, not a universal consumer form or legal requirement.
- System and operator: record the product or internal system name, model or version if displayed, the account or workflow involved, and who was using it.
- Context: note the task, relevant instructions, uploaded files or data categories, and whether the system acted automatically or only made a suggestion.
- Timing: write down the date and time, time zone if relevant, and when a person noticed the problem.
- Exact evidence: preserve the smallest necessary portion of the input and output, including warnings, confidence indicators or citations. Keep the original file format when possible so it is not accidentally altered.
- Consequences: describe what happened, what action was taken or considered, who could be affected, and whether harm is confirmed, suspected or only possible.
- Containment: record steps taken to stop further impact, such as cancelling a transaction, correcting a record or taking a system offline.
Minimize personal, medical, financial and confidential information in screenshots or reports. Redact data that is not needed to investigate, and use a secure channel. Do not repost harmful instructions or private records merely to gain attention; wider distribution can increase the damage.
How to report the problem effectively
Report to the provider or system operator
Use the safety-report, support or complaint mechanism made available by the service. Include the factual record, explain the potential or observed harm, and state what you want the operator to do—for example, investigate the output, preserve logs, correct a record, disable an unsafe workflow or provide a human response. Do not assume that a generic thumbs-down control creates a formal case; if the situation is serious, look for a documented support or safety route as well.
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Report to the organization that used the AI
When a school, employer, bank, clinic, public agency or other organization used AI in a process affecting you, contact the organization’s responsible department as well as the software provider. Ask for the human owner of the decision, the information considered, and the process for correction or review. An organization cannot shift accountability simply by saying that an algorithm produced the result.
Escalate outside the organization when appropriate
Serious incidents may warrant a professional body, regulator, ombuds service, law-enforcement agency, data-protection authority or emergency service. Which route is appropriate depends on your country, the sector, the people affected and the type of harm. There is no single worldwide AI complaint office, universal deadline or remedy established for every system.
When an AI answer may be biased or discriminatory
Harm is not limited to dramatic false statements. A system may produce systematically different quality, recommendations or treatment for people because of language, disability, race, sex, age, religion, location or another protected or sensitive characteristic. NIST’s bias work identifies the risk that AI can amplify harmful bias; its publication Towards a Standard for Identifying and Managing Bias in Artificial Intelligence was published on March 15, 2022.
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If you suspect bias, preserve examples from comparable cases without exposing unnecessary personal information. Note the relevant criteria, the people or groups affected, and the decision or opportunity lost. Ask for a human review using the organization’s normal correction or appeal process. Do not try to prove a statistical pattern by publishing identifiable records. A single incident can justify a review even when you cannot establish a broader trend.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.When the safest choice is to stop using the system
Mitigations are not always enough. The UK Government’s Data and AI Ethics Framework says that systems can behave unexpectedly, should be monitored for harmful or unusual outputs, and require human oversight and control. It also states that if a system cannot be made sufficiently safe for its intended use, it should not be used for that problem.
For an organization, that may mean suspending an automated workflow, adding a mandatory human approval step, limiting the system to lower-risk tasks, changing the data or instructions, or replacing it. A disclaimer alone is not a safety control when users are likely to rely on the result. The decision to resume use should identify the failure mode, the safeguard added, who is accountable, and how ongoing monitoring will detect a recurrence.
What trustworthy-AI guidance says about prevention
NIST’s AI Risk Management Framework 1.0 describes practices for validity and reliability, safety, security and resilience, accountability and transparency, explainability and interpretability, privacy, and fairness with harmful bias managed. NIST notes that these qualities can involve trade-offs and that transparency can support redress when an output causes a negative impact. The framework page is being updated, so organizations should check for a newer edition when planning controls.
NIST’s July 26, 2024 Department of Commerce announcement highlights generative-AI risks such as harmful content and confabulated, or “hallucinated,” output, and points organizations to its Generative AI Profile. Laurie E. Locascio, NIST Director and Under Secretary of Commerce for Standards and Technology, said: “For all its potentially transformational benefits, generative AI also brings risks that are significantly different from those we see with traditional software.”
UNESCO’s Recommendation on the Ethics of Artificial Intelligence calls for risk assessment, safety and security throughout the AI life cycle, oversight, impact assessment, audit, traceability and accountability for AI content and outcomes. It is an international recommendation, not a specific legal entitlement in every country. Together, these frameworks support practical controls: define an accountable owner, test before deployment, monitor real-world behavior, keep an intervention or shutdown capability, protect personal data, and provide a way to challenge and correct harmful results.
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Quick Recap
Common mistakes after an unsafe result
- Continuing because the answer sounds confident: fluency is not evidence of accuracy.
- Asking the same system to verify itself: a second response from the same model does not provide independent confirmation.
- Deleting all evidence: removing the prompt and output can make correction or investigation impossible.
- Sharing the complete transcript publicly: this can expose private data or spread dangerous instructions.
- Assuming a disclaimer removes responsibility: warnings do not substitute for human oversight in a high-stakes workflow.
- Using one country’s remedy everywhere: complaint channels, appeal rights, regulators and deadlines differ by jurisdiction.
A compact decision checklist
- Could someone be injured, killed, defrauded, discriminated against or exposed because of this result?
- Have I stopped the AI-guided action and taken reasonable containment steps?
- Has a suitably qualified human checked the underlying facts?
- Have I recorded the system, context, time, output, action and impact while protecting sensitive information?
- Have I reported the issue to both the provider and the organization responsible for the decision, when both exist?
- Does the seriousness or sector require an emergency service, professional body, regulator or other external escalation?
- Is the system safe enough for this task to continue, or should its use be suspended?
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