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Stop before acting, identify the claims that could change your decision, and verify them against authoritative sources you open yourself. If the answer could affect health, safety, money, rights, or someone else’s welfare, involve a qualified professional or the appropriate emergency service. Then use the product’s feedback or reporting control, while treating any revised AI answer as another draft—not proof that the original problem is fixed.
Why a fluent AI answer can still be wrong
Generative AI produces likely text, not a guaranteed statement of fact. It can give an answer that is polished, specific, and confident while containing a false claim, an obsolete detail, or advice that is unsafe in your circumstances. OpenAI’s consumer guidance describes “hallucinations” that include incorrect facts and fabricated quotations, studies, citations, or references. A confident tone is a style of output, not evidence that the underlying claim was checked.
The risk is not limited to obvious nonsense. An answer can be partly correct but omit a contraindication, apply a rule from the wrong country, confuse two similarly named products, or turn a general explanation into a recommendation for your particular case. A citation can also be real but fail to support the sentence attached to it.
Use an AI response as a starting point when accuracy matters. OpenAI’s help guidance summarizes the principle as: “Use ChatGPT as a first draft, not a final source.” The same discipline applies to other assistants.
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First response: pause and classify the risk
Do not execute a command, take a medicine, transfer money, sign a legal document, or make a safety-critical decision simply because an assistant sounds certain. Save the response and separate its claims before deciding what to do next.
Low-consequence information
An incorrect restaurant description, a rough brainstorming idea, or a wording suggestion may be inconvenient but reversible. You can still verify it, but the cost of a mistake is usually limited. Treat the answer as a draft and correct it before sharing.
Consequential information
Slow down when the answer could affect:
- Health, diagnosis, medication, pregnancy, or mental-health treatment.
- Physical safety, emergencies, hazardous equipment, travel conditions, or security.
- Money, taxes, investments, insurance, credit, or a business transaction.
- Legal rights, immigration, employment, housing, education, or benefits.
- Another person’s privacy, reputation, access, or safety.
For these categories, the assistant must not be your final authority. Contact the relevant qualified professional or emergency service when circumstances warrant it. There is no single cross-provider emergency procedure that makes an AI answer safe; the correct escalation depends on the situation and jurisdiction.
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Verification works better when you stop treating a long response as one indivisible answer. Copy the text into notes and mark each statement that could change your action.
Separate facts, calculations, and recommendations
- Facts: dates, definitions, product capabilities, regulations, dosage information, or quoted statements.
- Calculations: totals, percentages, conversions, code output, or financial projections.
- Interpretations: what a policy means, why an error occurred, or which option fits your circumstances.
- Recommendations: what to buy, take, configure, disclose, sign, or do next.
Check the factual premises first. A recommendation built on one wrong date or unsupported assumption is not rescued by clear prose.
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Look for warning signs
- A source, quotation, study, case, or standard that you cannot locate.
- A link that opens a different document or does not contain the claimed passage.
- Precise numbers without a date, region, edition, method, or stated assumptions.
- Absolute language such as “always,” “guaranteed,” or “safe for everyone.”
- Instructions that skip prerequisites, permissions, contraindications, or rollback steps.
- Conflicting answers in the same response or a sudden change of subject.
These signs do not prove that every sentence is false. They tell you which claims deserve independent checking before reliance.
Verify important claims against primary or authoritative sources
Open the underlying material yourself rather than trusting a citation label. Confirm that the source is genuine, current for your location and version, and actually supports the wording used by the assistant.
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Use a source hierarchy suited to the question
- Emergency or health questions: emergency services, a licensed clinician, a poison-control service, a pharmacist, or a public-health authority.
- Law and regulation: the relevant government, court, regulator, or a qualified lawyer; check the jurisdiction and effective date.
- Software and security: the vendor’s current documentation, release notes, security advisories, or a maintained standards body.
- Money: a regulator, tax authority, contract, account statement, or licensed adviser.
- Research: the original paper, dataset, or institution rather than an unsourced summary.
Secondary explanations can help you understand a source, but they should not replace the controlling document when the decision is consequential.
Check quotations, data, technical details, and references
Search for the exact quotation and read the surrounding paragraphs. Recalculate important figures with a calculator or a second method. For code, test in an isolated environment with non-sensitive data, inspect permissions and network access, and compare the result with official documentation. For a policy or contract, verify definitions, exceptions, dates, and territorial scope.
If a cited source cannot be found, or if it does not support the claim, label that claim unverified and do not use it as a basis for action. Do not fill the gap by assuming the assistant’s wording is probably right.
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Record what you verified
For a high-stakes decision, keep a short audit trail: the original prompt and response, the date, the exact claims checked, the sources consulted, and any unresolved uncertainty. This makes it easier for a professional to review the issue and prevents a later edited response from obscuring what you actually relied on.
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You can request a narrower, more useful draft after identifying a problem. Ask it to list assumptions, distinguish known facts from guesses, quote only text supplied in a document, show its calculation, or state what information is missing. You can also provide the authoritative passage and ask for a plain-language explanation limited to that passage.
This may improve the next response, but consumer guidance does not establish that re-prompting makes an answer reliable. A model can confidently produce a second error or change its answer without identifying why the first one failed. Continue to verify every material claim independently.
A NIST draft report dated July 31, 2025 describes a validation filter in one National Cybersecurity Center of Excellence chatbot prototype. That implementation detail is not a universal user procedure or a guarantee offered by other AI products. Treat it as an example of system design, not as a substitute for your own checks.
Report the problematic response in the product
Feedback helps the provider identify patterns and may support filters or other mitigations, but it does not guarantee an investigation, a correction to your conversation, or a future error-free answer. Capture the problematic text and relevant context before submitting a report.
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ChatGPT
- Find the response that is inaccurate or unsafe.
- Select the thumbs-down control under that message.
- Choose the issue that best describes the problem.
- Select Safety or Legal concern when that is the applicable category.
- Follow the prompts and include concise context: what claim was wrong or dangerous, what harm could result, and which authoritative source contradicts it.
OpenAI’s reporting guidance says reports may be reviewed and may lead to filters or other mitigations. It does not promise a particular review outcome or a correction to every affected answer.
Gemini Apps
Google’s Gemini Apps help provides feedback options for responses that are inaccurate or feel unsafe and points users to a reporting route. A separate help instruction recommends using thumbs-down for a hallucination or inaccurate answer. The exact control labels and placement can vary by platform and version, so use the feedback or report option shown in your current interface.
Other assistants
Look for a thumbs-down, “report,” “send feedback,” or safety link attached to the specific message. If the product has no visible control, use its official support channel and include the conversation identifier if one is available. Do not paste passwords, private health records, payment details, or other sensitive data merely to explain the error.
Escalate when the stakes are high
Verification and reporting are not emergency services. If someone may be in immediate danger, contact local emergency services or the relevant crisis, poison-control, medical, or security authority. If a legal deadline, financial transfer, employment action, or other irreversible step is imminent, pause the action and contact a qualified professional who can assess your facts and jurisdiction.
Health and medication
Do not start, stop, combine, or change a medicine based only on an AI response. A pharmacist or clinician can check allergies, interactions, dose, age, pregnancy status, existing conditions, and the product actually available to you. For possible poisoning or an acute reaction, use the appropriate emergency or poison-control service immediately.
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Legal, financial, and employment matters
Bring the exact contract, notice, account terms, or government form to a lawyer, licensed adviser, regulator, or qualified workplace representative. AI summaries often omit exceptions and deadlines; a small omission can change your rights or obligations.
Physical and cybersecurity safety
Stop a procedure if an instruction could expose people, equipment, or data to harm. For code or configuration, isolate the test system, remove secrets, review privileges, and use vendor security guidance. For an active incident, follow your organization’s incident-response plan and contact the responsible security team.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to judge an AI product before relying on it
Do not rank products by confidence, friendliness, or one impressive demonstration. Compare the controls that let you detect and manage failure.
| What to examine | Questions to ask | Why it matters |
|---|---|---|
| Checkable sources | Does the answer expose sources you can open, and do those sources support the claim? | Traceability lets you test the answer instead of accepting an unsupported assertion. |
| Uncertainty and limitations | Does the system identify missing information, assumptions, and situations outside its competence? | Clear limits help you decide when to stop and seek professional help. |
| Feedback and reporting | Can you report a specific message, and is there a safety or legal category? | A precise report gives the provider actionable context after a failure. |
| Human review | For consequential use, is a qualified person available to review or approve the result? | Human intervention provides a second line of defense when automated checks miss an error. |
This is a decision framework, not a measured ranking of products. The National Institute of Standards and Technology (NIST) treats validity and reliability as characteristics of trustworthy AI and notes that ongoing monitoring and human intervention can matter when a system fails to detect or correct errors.
Build a repeatable verification workflow
- Pause: do not act on a consequential answer because it sounds certain.
- Scope: identify the exact decision, people affected, location, version, and deadline.
- Decompose: list the factual claims, calculations, interpretations, and recommendations.
- Prioritize: verify first the claims whose failure would cause the greatest harm or loss.
- Source: open primary or authoritative material directly and check date, jurisdiction, edition, and exceptions.
- Test: recalculate figures, reproduce technical steps safely, and ask a qualified person to review high-risk conclusions.
- Decide: act only when the evidence and professional advice support the action; otherwise pause or choose a safer alternative.
- Report: submit the problematic response through the product’s feedback route without exposing unnecessary personal data.
- Document: retain the response, sources, assumptions, and unresolved questions for later review.
What trustworthy behavior looks like—and what it does not
A trustworthy system is not one that never makes a mistake; current AI systems can fail. More useful signs are that it provides inspectable evidence, communicates uncertainty, limits claims to the information available, and supports monitoring and human intervention. NIST describes deployment of systems that are inaccurate, unreliable, or poorly generalized beyond their training as increasing negative AI risks and reducing trustworthiness.
Those principles apply to the surrounding process as well as the model. A product may display citations that are difficult to open, while a human workflow may still require an expert to confirm the interpretation. Conversely, a model that admits uncertainty can still be wrong. Treat transparency as a control that helps you verify—not as a guarantee of correctness.
Common mistakes after an unsafe answer
- Arguing until the model agrees: a changed answer is not evidence that either version is true.
- Checking only the headline claim: a small omitted condition can make otherwise correct advice unsafe.
- Trusting a citation badge: read the linked source and confirm the exact passage.
- Assuming a report fixes your case: provider mitigation may be possible, but no outcome is guaranteed.
- Sharing sensitive context to get help: redact personal, financial, medical, and security information before submitting feedback.
- Using prototype safeguards as universal instructions: a control described for one system may not exist or work the same way elsewhere.
Bottom line
When an AI answer may be unsafe or unreliable, pause, isolate the claims that matter, and verify them against authoritative material you open yourself. Ask for a clearer revision only as a drafting aid, report the specific response through the product’s feedback controls, and escalate consequential decisions to qualified humans or emergency services. Confidence, citations, and a second AI-generated answer can all be useful clues, but none is a substitute for evidence and appropriate human judgment.
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