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Stop treating the answer as an instruction. Pause, save the exact prompt and response, remove unnecessary personal information, verify important claims with authoritative sources or a qualified professional, and report the output through the provider’s feedback or abuse channel. If the exchange points to an imminent and credible threat of violence, contact local emergency services or the appropriate authorities immediately; a platform report is not an emergency response.
Chatbots can produce stereotypes, unequal recommendations, omissions and confidently wrong advice. OpenAI’s Help Center warns that ChatGPT is “not free from biases and stereotypes.” Treat any surprising or harmful answer as a warning signal that needs human review, not as evidence that the system is right.
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1. Pause, contain the harm and check for immediate danger
Do not act on, forward or repeat the answer
Stop using the chatbot’s response as a basis for a decision. Do not forward it as fact, paste it into a workplace or school record, or use it to judge another person. If you already acted on it, stop the activity where possible and tell the person responsible for the decision what happened.
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Handle an imminent threat first
If the conversation suggests an imminent and credible threat of violence, move yourself and others to a safe place and contact local emergency services or law enforcement. Give responders the relevant wording and context, but do not delay the call while waiting for a chatbot provider to answer. OpenAI describes escalation and possible law-enforcement referral for such cases; that process cannot substitute for immediate help.
2. Preserve evidence without exposing more personal data
Record the details a reviewer needs
Save the complete prompt and response, including any system-generated warnings, the date and time, the product and model name if shown, and enough preceding conversation to explain the context. Note whether you obtained the same answer more than once, whether you used a particular language, and what harm or risk you observed.
- Exact wording of the prompt and answer.
- Date and approximate time, with your time zone if relevant.
- Service, application and model or version displayed in the interface.
- Relevant conversation context, attachments or settings that affected the answer.
- The decision, person or group that could be affected.
- What happened, or what could happen, if someone followed the advice.
Redact before sharing
Remove passwords, authentication codes, account numbers, health identifiers, full addresses, private contact details and any other information that is not needed to understand the incident. Replace a real name with a neutral description such as “employee” or “patient,” while retaining facts that are necessary to assess discrimination or safety. Keep an unredacted copy only in a secure location with access limited to people handling the incident.
Screenshots can omit metadata and surrounding context, while a full transcript can reveal more personal information than a reviewer needs. Choose the smallest set of files that proves what happened, and explain any redactions.
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3. Verify the substance independently
Match the checking method to the stakes
For a casual question, compare the answer with a reliable primary source. For health, legal rights, finance, employment, housing, education or personal safety, stop and obtain qualified human advice before taking action. The chatbot’s confidence, fluent wording or citation-like formatting is not evidence of accuracy.
Use official government guidance, the relevant institution’s written policy, professional standards, court or regulator information, or a licensed practitioner. Check the date and geographic scope: a rule for one country, state, employer or school may not apply to you.
Bring in an independent reviewer
Ask a second person with relevant subject expertise to examine the answer and the evidence. When language stereotypes or targets a community, include a knowledgeable reviewer from the affected community where practical. Ask the reviewer to identify both factual errors and unequal assumptions about people.
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4. Report the output with enough context to support correction
Use the provider’s built-in route
Submit the incident through the conversation’s thumbs-down or feedback control, or through the provider’s abuse and safety-reporting form. Include the minimum redacted transcript needed to reproduce the problem. OpenAI says flagged conversations can be assessed in context by trained personnel and that enforcement decisions can be appealed.
Explain the harm, not only the offensive phrase
A useful report states what the system said, why it is inaccurate, discriminatory or unsafe, who could be affected, whether the behavior repeated, and what safeguard or correction you are requesting. Distinguish an explicit slur from a stereotyped assumption, an unequal recommendation, a missing perspective or advice that is simply wrong; each points to a different remedy.
Date and time: 18 October 2026, 14:20 UTC
Service and model: product name and displayed model
Prompt: exact wording
Response: exact wording, with unnecessary personal data removed
Observed risk: factual error, stereotype, unequal treatment or safety danger
Potential impact: person, group or decision affected
Reproduction: whether the result appeared again
Requested action: review, correction, safeguard or explanationKeep the provider’s case number and any reply. If the decision is disputed, use the stated appeal route and attach new evidence rather than reposting private data publicly.
5. Escalate high-stakes cases outside the chatbot
Health and personal safety
Contact a qualified clinician, poison center or emergency service as appropriate. Tell the professional that an AI system supplied the information, show the exact wording, and identify any action already taken. Do not let a provider’s moderation queue determine whether you seek urgent care.
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Employment, housing and education
Notify the organization that controls the decision—such as a human-resources team, landlord, school administrator or admissions office—and request a human review and a way to correct the record. Preserve the date, decision, criteria communicated to you and any evidence that an AI-generated statement influenced the outcome. Affected people should be able to challenge a decision rather than being forced to accept an opaque automated judgment.
Legal and financial rights
Consult a qualified lawyer, accredited adviser or appropriate regulator. Ask which deadline, appeal, complaint or disclosure rule applies in your jurisdiction. Do not submit an AI-generated interpretation as if it were professional advice, and do not disclose more financial or identity information than the adviser needs.
Credible violence
Contact emergency services or appropriate authorities immediately. Share the original wording, timing and any identifying context that responders need, while protecting unrelated personal information. If the threat concerns a particular institution, notify its established security or safeguarding contact after emergency help is underway.
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Data and classification problems
NIST explains that bias can be embedded in data and technology processes. Training data may underrepresent groups, encode historical discrimination or associate a group with a negative label. A faulty classifier can then turn an uncertain pattern into a confident recommendation.
The FTC has highlighted unrepresentative datasets, faulty classifications and lack of context as sources of inaccurate or harmful AI results. A chatbot may not know the facts that a human decision requires, may infer sensitive characteristics from irrelevant wording, or may generalize from examples that do not fit your situation.
Bias can run through the full lifecycle
NIST’s AI 100-4, Toward a Standard for Identifying and Managing Bias in Artificial Intelligence (SP 1270, 2022), says “biases remain endemic across technology processes and can lead to harmful impacts regardless of intent.” Its framework addresses identifying, measuring, managing and reducing bias rather than treating a single output as an isolated mistake.
OpenAI also notes that conversational interaction can reinforce a user’s existing bias and that safeguards may perform differently across languages. A polite conversation can therefore still produce an unequal result, and a safeguard that works in one language may not work as well in another.
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- Explicit slurs or demeaning descriptions.
- Stereotypes presented as facts about a gender, race, disability, religion, nationality, age or other group.
- Different recommendations for comparable people without a legitimate reason.
- Omission of relevant perspectives that changes the practical outcome.
- Confidently wrong health, legal, financial or safety guidance.
- Refusal or warning behavior that is inconsistent across languages or contexts.
7. Apply human oversight and appeal rights
UNESCO’s Recommendation on the Ethics of Artificial Intelligence (2021) calls for fairness, non-discrimination, accountability, prompt explanations and appeal mechanisms. In practice, that means a person should be responsible for a consequential decision, know enough about the basis for it to challenge an error, and have a route to request correction.
Ask the responsible organization four questions: Was an AI system used? What role did its output play? Who reviewed the result? How can the affected person appeal or correct the record? If no one can answer, treat the process as a governance problem and escalate to the organization’s privacy, compliance, safeguarding or complaints function.
8. Choose the response by urgency, stakes and remedy
| Situation | First action | Additional review or remedy |
|---|---|---|
| Personal curiosity with no immediate consequence | Pause, save the exchange and check a reliable primary source | Report the harmful pattern if it is discriminatory, unsafe or reproducible |
| Health, legal, financial, employment, housing or education decision | Do not act on the answer; obtain qualified human review | Notify the responsible organization and use its correction or appeal process |
| Imminent and credible threat of violence | Move to safety and contact emergency services or appropriate authorities | Provide the preserved evidence to responders and report to the provider afterward |
Before uploading evidence, weigh five factors: urgency, the stakes for the affected person, the quality of independent corroboration, the amount of private data exposed, and the remedy that can actually change the outcome. A provider correction may help future users, while an institutional review or emergency intervention may be necessary for harm already underway.
9. Practical checks before you rely on any chatbot answer
- Source check: Can you confirm the claim in an authoritative, current source?
- Context check: Did the system have the facts, jurisdiction, language and timeframe that matter?
- Fairness check: Would the same facts about another person or group produce the same treatment?
- Uncertainty check: Does the answer acknowledge limits, alternatives and the need for professional judgment?
- Impact check: Who could be harmed if the answer is wrong, and can the decision be reversed?
- Privacy check: Have you removed information that the checker does not need?
10. What not to do
- Do not keep prompting until the chatbot produces the answer you want and then call that confirmation.
- Do not publish a discriminatory response with real names or identifying details when an anonymized transcript will prove the point.
- Do not use a chatbot’s output as the sole reason to deny someone a job, home, education, service or medical care.
- Do not assume a disclaimer makes dangerous advice safe.
- Do not wait for a platform’s moderation process when someone faces immediate physical danger.
The safest pattern is consistent: contain the advice, preserve a privacy-conscious record, verify with people and sources that have authority, report the failure with context, and escalate to the institution or emergency service that can act.
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