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Stop and assess before acting on the output. If an AI response could cause injury, financial loss, discrimination, privacy exposure, security damage or another serious consequence, do not treat it as authoritative. Make the immediate situation safe, obtain qualified human judgment, preserve a factual record, report the incident to the responsible provider or organization, and escalate through the appropriate professional, regulator or emergency channel for your sector and location.
There is no single reporting route that works for every AI system or country. The right response depends on how serious and urgent the harm is, who operates the system, whether a human decision-maker can review it, what sensitive information is involved, and which laws or procedures apply.
First, decide how urgent the risk is
Severity and immediacy determine what you do next. A strange answer that has not influenced anything can usually be documented and reported. An output that is about to influence a medical treatment, safety action, payment, employment decision or physical activity requires immediate interruption and human review.
| Situation | Priority action | Why |
|---|---|---|
| Imminent threat to life, physical safety or public safety | Stop the affected activity if you can do so safely; follow applicable emergency or sector procedures and contact emergency services where appropriate. | Waiting for a provider response can allow preventable harm to continue. |
| Serious but not immediate risk, such as a wrong medical, legal, financial or security recommendation | Do not act on the output. Contact a qualified professional or authoritative source and request human review from the system operator. | Consequential errors need independent judgment, not another unverified AI answer. |
| Potential bias, privacy exposure, harassment or harmful content without an immediate physical threat | Preserve a limited record, avoid redistributing the material, and report it through the operator or organization responsible. | Documentation supports investigation while reducing additional exposure. |
| Low-stakes error discovered before anyone relies on it | Correct the work, record the failure if useful, and send feedback through the available support or safety channel. | Early reporting can reveal recurring failure modes. |
NIST’s AI Risk Management Framework treats risks of serious injury or death as requiring the most urgent prioritization and thorough risk management. If someone is in immediate danger, safety takes precedence over collecting screenshots or composing a detailed complaint.
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Step 1: Make the situation safe
Stop relying on the output
Pause the action that depends on the AI response. Do not copy an unverified diagnosis into a treatment plan, send an automated message accusing someone of misconduct, approve a transaction, change a production setting, operate machinery, or publish a dangerous instruction merely because a model produced it confidently.
If the output has already triggered an automated action, use the organization’s stop, rollback, disable or escalation procedure. NIST identifies monitoring, the ability to shut down or modify a system, and adding human intervention as possible safety practices when behavior deviates from its intended use.
Protect people before protecting evidence
Move people away from a physical hazard, isolate a compromised account or system, and follow established incident-response procedures. Do not keep testing a dangerous prompt on a live system if doing so could expose additional people, data or equipment. A safe, redacted reproduction in an approved test environment is preferable.
Do not amplify harmful content
Share only what is needed with the people who can help. Avoid reposting abusive, private, criminal or self-harm content publicly. When reporting, redact personal data, credentials, medical details and identifying information that are not necessary to understand the failure. Keep an original copy only where retention is lawful and secure.
Step 2: Get qualified human judgment
An AI system can summarize information or suggest possibilities, but it is not a substitute for a responsible decision-maker in a consequential situation. Verify the claim with a person whose training and authority match the risk.
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- Medical or mental-health output: contact a licensed clinician, pharmacist, poison-control service or emergency service appropriate to the symptoms and location. Do not change medication or delay urgent care based on a model response.
- Legal output: consult a qualified lawyer, legal-aid service or relevant court or government source. AI-generated legal citations and deadlines can be fabricated or jurisdictionally wrong.
- Financial or tax output: check with a regulated adviser, accountant, bank or official tax authority before transferring money, filing, borrowing or investing.
- Employment, education or benefits decisions: ask the organization for human review, the criteria used and a way to correct inaccurate information where such a process exists.
- Cybersecurity or operational safety: involve the system owner, security team, safety officer or qualified engineer. Do not execute unfamiliar commands on production systems solely because an AI suggested them.
- Personal safety or threats: use local emergency, crisis or safeguarding services when appropriate; a chatbot cannot assess danger as reliably as trained responders.
Human review should be independent enough to detect the original error. Asking the same system to “double-check” itself may find some mistakes, but it does not establish that the answer is safe or correct.
Step 3: Preserve a factual, privacy-conscious record
A concise incident record helps a provider or organization reproduce the failure and decide whether other people may be affected. This is practical advice derived from official guidance on incident documentation, transparency, traceability and redress; it is not a universal consumer form or legal requirement.
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- The system name, version or model label, if shown, and the website, application, device or internal tool where it was used.
- The date and time, including time zone, and the account, workflow or business process involved.
- The relevant input and output, preserved exactly when safe and lawful. Include attached files or tool actions only if they are necessary.
- What the system was supposed to do, what it actually did, and whether a person or automated process acted on it.
- The observed or potential harm: who could be affected, how serious it is, whether it is ongoing and what protective action has already been taken.
- Any warning, refusal, confidence indicator, source citation or system setting that appeared alongside the output.
- The people or teams already notified and the date of each notification.
Use a stable file name and preserve the original capture in a restricted location. Make a redacted copy for routine support channels. Never include passwords, authentication tokens or unnecessary personal information in a ticket. If the system is used at work, follow your organization’s evidence-retention and privacy rules.
Step 4: Report through the responsible route
Start with the operator or provider
Use the system’s safety-report, support, abuse, privacy or complaint channel. State that the output may be harmful, describe the risk and ask for a case number or written confirmation. Attach the smallest evidence set that allows investigation, and explain whether the issue is still active.
Do not assume that a general product-feedback form is the only option. A provider may separate urgent safety reports, security vulnerabilities, privacy complaints and account support. Use the route that matches the failure, and follow any instructions for secure submission of sensitive material.
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Contact the organization that used the AI
If an employer, school, insurer, lender, government office, clinic or other organization used AI in a decision about you, contact that organization as well as the technology provider. Ask for human review, correction of inaccurate information and an explanation of the decision or process where those options are available. The provider may not be able to change a decision made by its customer, and the organization may not control the underlying model.
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Escalate when the first route is inadequate
Escalation depends on the sector and jurisdiction. Possible destinations include a professional licensing body, data-protection or privacy authority, consumer-protection agency, financial regulator, workplace or equality body, school safeguarding lead, product-safety authority, law-enforcement agency or court. A qualified lawyer or local advice service can help identify the appropriate process when rights, deadlines or compensation are at issue.
The available remedies, complaint deadlines and disclosure rules differ by country and by the role the AI played. Do not present an international ethics recommendation as an automatic legal entitlement, and do not assume that a regulator accepts complaints about every private model or individual incident.
Choose the next channel using five questions
| Question | If the answer is “yes” | What it changes |
|---|---|---|
| Could someone be injured, killed or exposed to immediate danger? | Use emergency or sector-specific safety procedures first. | Urgency outranks evidence collection and ordinary support queues. |
| Can a named human decision-maker review the result? | Contact that person or organization and request intervention. | Human oversight may stop or reverse a consequential action. |
| Who operates or controls the system? | Report to both the operator and, where distinct, the underlying provider. | Different parties may control the model, workflow, data or remedy. |
| Would reporting reveal sensitive information? | Redact, use a secure channel and ask how data will be handled. | Reporting should not create a second privacy or security incident. |
| Which sector and jurisdiction apply? | Look for the relevant professional, regulatory or legal route. | Rights, deadlines, evidence rules and available remedies vary. |
Recognize the main types of harmful AI output
Confabulation and fabricated facts
Generative systems can produce plausible but false statements, invented citations, altered quotations or nonexistent procedures. A polished tone is not evidence. Verify names, figures, sources, deadlines and instructions against an authoritative source before relying on them.
Unsafe instructions
An answer may omit a critical precaution, misread a situation or give steps that are unsuitable for a particular device, patient, workplace or environment. Treat instructions affecting health, machinery, chemicals, software production systems or personal security as high risk unless a qualified person has checked them.
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Bias and discriminatory impact
AI can amplify harmful bias in data, labels, rankings or decision rules. NIST’s bias work identifies this risk, and its publication Towards a Standard for Identifying and Managing Bias in Artificial Intelligence was published on March 15, 2022. Record the affected characteristic, comparison group, decision context and practical consequence without exposing more personal data than necessary.
Privacy and confidentiality failures
An output may reveal personal information, reproduce confidential text, infer a sensitive trait or send data to an unintended recipient. Stop further disclosure, preserve access logs if authorized, notify the organization’s privacy or security contact and follow applicable breach procedures.
Security and operational failures
AI-generated code, commands or automated actions can weaken defenses, delete data or create a new vulnerability. Isolate affected systems according to your incident-response plan, involve security personnel and preserve logs. Do not publish exploit details while a live vulnerability remains unmitigated.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What organizations should do after receiving a report
If you operate an AI-enabled service or use one in a decision process, treat the complaint as a potential incident rather than ordinary user dissatisfaction. Confirm receipt, assign an accountable owner, preserve relevant logs, assess whether other people may be affected and provide a human contact for urgent cases.
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UNESCO’s Recommendation on the Ethics of Artificial Intelligence calls for risk assessment, safety and security across the AI lifecycle, oversight, impact assessment, audit, traceability and accountability for AI content and outcomes. These principles support investigation and governance; they do not create an identical complaint process in every country.
What the major guidance says
NIST’s AI Risk Management Framework describes trustworthy AI through validity and reliability; safety; security and resilience; accountability and transparency; explainability and interpretability; privacy; and fairness, including management of harmful bias. NIST emphasizes that context matters and that these qualities can involve trade-offs. Transparency can make it possible to challenge an incorrect output and seek redress.
NIST’s July 26, 2024 announcement about generative AI highlights risks including harmful content and confabulated or “hallucinated” output and points organizations toward its Generative AI Profile. The announcement is organizational risk guidance, not a universal consumer complaint service. Laurie E. Locascio, Under Secretary of Commerce for Standards and Technology and NIST Director, said: “For all its potentially transformational benefits, generative AI also brings risks that are significantly different from those we see with traditional software.”
The AI Risk Management Framework 1.0 page indicates that the framework is being updated. Check the current NIST material when making a policy or compliance decision rather than assuming the 1.0 text is the latest edition.
The UK Government’s Data and AI Ethics Framework warns that systems can behave unexpectedly, recommends monitoring unusual behavior including harmful outputs, and calls for human oversight and control. Its advice is aimed at responsible development and use, so the personal steps in this article apply those principles to an individual incident.
Quick Recap
A compact incident checklist
- Stop the action that depends on the unsafe output.
- Protect people, systems and data; use emergency procedures for imminent danger.
- Obtain judgment from a qualified person or authoritative source.
- Capture the system, time, input, output, action and harm in a factual record.
- Redact unnecessary personal, confidential and security-sensitive information.
- Report to the provider or operator and to any organization that made the decision.
- Request human review, correction, explanation or containment where available.
- Escalate through the appropriate professional, regulator, safeguarding or emergency route for the jurisdiction and sector.
- Keep the case number and follow-up dates; do not continue using the system for the same high-risk task until it is shown to be safe.
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