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Pause before acting on it. A chatbot’s confident wording is not proof that its answer is accurate, fair or safe. Check important claims against reliable primary sources or a qualified person, avoid adding sensitive information, save only a redacted record if you need to explain what happened, and report the output through the service’s current feedback or support channel. If health, safety, finances, legal rights, employment or another high-impact decision is involved, put a responsible human professional in charge.
What should you do first?
Use this sequence as soon as an answer seems discriminatory, dangerous or seriously wrong. It is prudent guidance, not a universal reporting protocol: providers use different controls, privacy settings and escalation processes.
- Stop and assess immediate risk. Do not follow instructions that could injure someone, expose confidential information, destroy evidence or cause an irreversible decision. If someone may be in immediate danger, contact the appropriate local emergency or professional service rather than relying on the chatbot.
- Separate the answer into claims. Mark which statements are factual and checkable, which are opinions, and which are recommendations. A response can contain a correct general fact and still reach an unsafe conclusion because it omitted context.
- Verify consequential claims. Check primary sources, official guidance, records or a suitably qualified professional. UK government guidance tells users to check LLM outputs for incorrect information and potential bias and to use human oversight in risky settings (Data and AI Ethics Framework).
- Do not disclose more information. Never add names, account numbers, medical records, passwords, confidential work material or identifying details simply to persuade the system to revise its answer.
- Record and report carefully. If it is safe and useful, retain the exact output, the prompt, approximate date and time, and the feature used. Redact personal or confidential content before sending anything to the provider.
- Hand the decision to a human when stakes are high. A qualified person must be able to examine the underlying facts and accept responsibility for the outcome.
Should you trust an answer that sounds certain?
No. Fluency and certainty describe how text is generated, not whether it is true or unbiased. NIST warns that AI systems can perpetuate or amplify harmful bias (NIST’s harmful-bias research page). A 2022 FTC report also describes inaccuracy, bias, discrimination, unrepresentative data, faulty classifications and failures to account for context in AI tools; it was about tools used to combat online problems, not a measured error rate for every consumer chatbot (FTC report, June 16, 2022).
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Verify facts, not just the final recommendation
Look for the specific proposition that would change your decision. For a medical answer, verify the symptom, dosage and contraindications with a clinician or authoritative health service. For a legal answer, check the current statute, regulation or court guidance and obtain advice for your jurisdiction. For a financial answer, confirm rates, fees, tax treatment and account rules with the institution or a licensed adviser.
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Check the date and location of any source the chatbot names. Laws, benefits, product specifications and safety instructions change. If the chatbot supplies no source, treat the claim as unverified rather than trying to infer reliability from its tone.
Look for missing context and unequal treatment
Ask whether the response stereotypes a person or group, applies a different standard to comparable people, assumes facts that were never provided, or leaves out a relevant disability, language, age, cultural or socioeconomic circumstance. These are practical checks, not a formal bias test prescribed by NIST or the FTC. A neutral-sounding answer can still produce discriminatory effects when the underlying classification or context is wrong.
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How can you test a suspected bias without making the situation worse?
Do not run a “test” that requires uploading someone’s private data or repeatedly naming a protected characteristic. First write down the smallest factual difference that appears to have changed the answer. If you need to compare outputs, use fictional, non-identifying examples and remove details that could identify a real person.
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- Compare like with like: keep the request, evidence and desired outcome constant while changing only the disputed attribute.
- Check whether the system explains a different recommendation with verifiable facts or merely repeats a stereotype.
- Ask for the assumptions and uncertainty behind a recommendation, but do not treat a more detailed explanation as proof that it is correct.
- Stop if the prompts could reveal a person’s identity, health status, immigration status, finances, employment records or other sensitive information.
Because chatbot behavior can vary between sessions and versions, one response does not establish a general rate of bias. It does establish a reason to verify the specific decision and alert the provider.
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How do you protect personal and confidential information?
Trying to “fix” an answer by adding more context can create a second problem: unnecessary disclosure. UNESCO’s human-centred guidance identifies data-privacy protection as a central consideration for generative AI use (UNESCO guidance, September 7, 2023; updated January 16, 2026).
Information to remove before continuing
- Names, addresses, phone numbers, email addresses and identification numbers.
- Passwords, authentication codes, payment details and account credentials.
- Medical records, photographs, genetic information and details that identify a patient.
- Confidential contracts, customer data, unpublished research and internal workplace documents.
- Details that could identify a child, victim, witness, client or colleague.
Use a generic description instead: “an employee in a small team” rather than a name and job title, or a fictional age range rather than a birth date. If private information is already in the conversation, review that provider’s current history, training-use, retention and deletion controls. The available controls differ by service, account type and region; do not assume that deleting a chat removes every copy or guarantees a particular response time.
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What should you save, and how should you report the answer?
A minimal, redacted record is usually enough to explain the issue. Keep the exact chatbot output and the prompt that produced it when doing so is lawful and safe. Add the approximate date and time, the product or feature name, and what harm or error you observed. Do not preserve a whole personal conversation when a short excerpt demonstrates the problem.
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- Open the message’s feedback control, “Report,” help centre or support form.
- Choose the closest category, such as unsafe content, discrimination, privacy, misinformation or self-harm risk.
- Describe the specific statement, why it is wrong or dangerous, and what reliable source or professional advice contradicts it.
- Attach only the redacted excerpt needed to reproduce or understand the issue.
- For an important decision, explicitly request human review and state whether a deadline or ongoing risk exists.
Providers may acknowledge a report, change a model, ask for more information or do nothing. General guidance does not establish a guaranteed correction, human response, deletion or timeline. Keep your own redacted record if you may need to explain the incident to an employer, school, clinician, regulator or adviser.
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When should a human take over?
NIST’s AI Risk Management Framework treats safety, fairness, privacy, transparency and accountability as context-dependent characteristics of trustworthy AI (NIST AI RMF resource). In a high-impact situation, the chatbot can help you prepare questions, but it should not be the decision-maker.
| Situation | Responsible next step |
|---|---|
| Medical symptoms, medication, pregnancy, mental-health crisis or physical danger | Contact a licensed clinician, poison-control service or appropriate local emergency resource. Do not delay urgent care while seeking a chatbot explanation. |
| Legal rights, immigration, housing, benefits or an imminent deadline | Speak with a qualified lawyer, legal-aid service or the responsible public agency in the relevant jurisdiction. |
| Banking, investing, debt, taxes or insurance | Confirm the facts with the institution and, where appropriate, a licensed financial or tax professional before transferring money or signing. |
| Hiring, firing, promotion, discipline, admissions or access to essential services | Require a responsible human reviewer to examine the evidence, applicable policy and possible discrimination; do not treat the chatbot’s ranking as a final decision. |
| Threats, abuse, self-harm or immediate safety concerns | Use appropriate local emergency, crisis or safeguarding services. A provider report is an additional step, not a substitute for urgent help. |
The UK framework puts this responsibility plainly: “People must be able to monitor and influence how systems work, even when the system is partially or fully automated.” That principle supports keeping a human able to challenge and override an automated output.
Which escalation route fits the problem?
| Route | Use it when | What to provide |
|---|---|---|
| Routine provider feedback | The answer is inaccurate, offensive or biased but no immediate decision or danger is involved. | Redacted prompt, output, date, feature and a concise explanation. |
| Provider support or human review | The output affected an account, workplace, school, service or other consequential process. | The minimum evidence, the decision affected, relevant deadline and request for review. |
| Qualified professional or local authority | Health, safety, finances, legal rights, employment or another high-impact interest is at stake. | Verified facts, the chatbot’s claim as a secondary record, and the professional question you need answered. |
These routes can overlap. Reporting a harmful output does not pause a legal deadline, reverse a transaction or provide medical treatment.
What official guidance does—and does not—promise
UNESCO’s 2021 Recommendation on the Ethics of Artificial Intelligence is an international ethics recommendation, not a chatbot help desk or a universal legal remedy. UNESCO’s generative-AI guidance is focused on education and research, although its privacy and human-centred principles are relevant to everyday use.
In September 2025, the FTC announced an inquiry into companies offering consumer-facing AI companion chatbots. The inquiry sought information about safety evaluation, effects on children and teenagers, disclosures and data handling; it was an inquiry, not a final finding about all chatbots (FTC announcement, September 11, 2025). Neither that action nor general government guidance supplies one complaint form, guaranteed remedy or worldwide standard. Your location, the provider and the type of harm determine what additional rights or regulators may apply.
Quick Recap
Common mistakes to avoid
- Following a dangerous instruction while “testing” it: preserve safety first; do not reproduce hazardous steps.
- Arguing with the chatbot until it agrees: a changed answer is not evidence that either answer is right.
- Uploading more personal data: extra detail can increase privacy exposure without improving accuracy.
- Publishing an unredacted screenshot: remove identities, account information and private conversation before sharing.
- Assuming a report solved the problem: independently correct the decision and obtain human help.
- Treating a general warning as legal advice: complaint rights and deadlines depend on jurisdiction and circumstances.
A compact checklist
- Pause; do not act on a dangerous or high-impact answer.
- Identify the exact factual claim, assumption or unequal treatment.
- Verify it with a primary source or qualified professional.
- Stop adding sensitive information; redact what is already present.
- Save only the prompt, output, timing and feature details needed to explain the issue.
- Report through the provider’s current feedback or support route.
- Ask for human review when a decision, right, health issue, finance or safety concern is involved.
- Use local professional or emergency services for urgent risk.
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