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Do not treat an AI-generated answer as reliable because it sounds certain, includes citations, or matches what you expected. Treat it as a set of unverified claims. Before relying on it, decide how harmful an error would be, separate the response into checkable statements, verify important facts against current primary or authoritative sources, inspect every citation, and obtain qualified human judgment when the decision carries professional, legal, medical, financial, safety, or data-integrity consequences. For low-risk work, you may use verified portions and clearly label uncertainty. For high-impact work, an answer that cannot be checked should be corrected, qualified, or rejected.
Why can an AI answer sound right and still be wrong?
Generative AI produces a likely continuation of the text in its prompt and context; it is not automatically retrieving and validating each fact. That makes polished prose a poor test of truth. A response can be fluent while containing a false name, an outdated rule, an invented quotation, a distorted statistic, or a conclusion that the cited material does not support.
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Confidence is a style, not evidence
Models often state uncertain information in the same calm tone they use for well-established facts. Technical University of Munich’s AI-literacy guidance distinguishes confident wording from verified wording, and the OpenAI Help Center warns that ChatGPT can produce incorrect information and fabricated citations. Treat words such as “definitely,” “always,” and “the law requires” as claims that need stronger checking, not as proof.
Errors are not limited to individual facts
An answer can be factually correct in isolated sentences yet still mislead by omitting a material exception, presenting an opinion as a consensus, using an old version of a policy, or answering only part of the question. University of Alberta Libraries’ evaluation guidance therefore asks readers to check, analyze, and reflect: accuracy is only one part of quality.
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Is generative AI suitable for this task?
Start with the consequence of being wrong, not with the apparent quality of the prose. If accuracy or data integrity is essential, the Government of Canada’s guidance says not to use generative AI for that task. For other consequential uses, plan authoritative source checks and appropriate expert review before acting.
| Situation | What an error could cause | Appropriate treatment of an AI answer |
|---|---|---|
| Low consequence, reversible | Minor inconvenience or editing time | Use as a draft or idea list, then spot-check factual claims and remove unsupported details. |
| Moderate consequence | Reputational, operational, academic, or financial harm | Verify every material claim, check the date and jurisdiction, and have a knowledgeable reviewer examine the result. |
| High consequence | Safety, health, legal rights, major financial loss, privacy, or corrupted records | Use authoritative sources and qualified professionals as the basis for the decision. An AI output may help organize questions, but it should not be the final authority. |
| Accuracy or data integrity is essential | Irrecoverable or systemic harm | Do not use generative AI for the task unless a governing policy explicitly permits a tightly controlled, reviewable workflow. |
This classification can change during a project. A casual explanation may become high impact when copied into a customer notice, a clinical record, a contract, a safety procedure, or a production database.
How do I turn an AI response into checkable claims?
Review the answer sentence by sentence and rewrite each material assertion as a claim that could be proved or disproved. Do not try to “fact-check the vibe” of a long response.
- Mark factual assertions. Highlight names, dates, places, quantities, percentages, document titles, product capabilities, causal statements, and statements about what a rule or policy requires.
- Separate compound sentences. A sentence saying that an agency adopted a rule in a particular year and that the rule applies to a certain group contains at least two claims. Check each part separately.
- Identify quotations. Treat quoted words, attributed statements, and paraphrases as claims requiring an original transcript, publication, or recording.
- Flag time-sensitive content. Laws, prices, software features, office-holders, deadlines, scientific recommendations, and service availability can change. Record the relevant date and jurisdiction before searching.
- Mark interpretation. Label predictions, recommendations, opinions, and explanations separately from observations. An answer may support a fact but not the conclusion drawn from it.
- Record omissions to investigate. Note conditions, exceptions, affected groups, counterarguments, and steps the answer assumes without explaining.
Keep a simple claim log with columns for the claim, its importance, the source checked, the passage that supports or contradicts it, the source date and jurisdiction, and your decision. This prevents a plausible opening paragraph from distracting you from a critical unsupported sentence later.
How should I verify the claims?
Match the authority of the source to the importance of the claim. For a law, start with the current statute, regulation, court decision, or official agency guidance. For a product feature, use the current manufacturer documentation or release notes. For a scientific or medical statement, look for the responsible institution, professional body, guideline, or original study, then involve a qualified practitioner when action is involved.
Check names, dates, numbers, and titles exactly
Search distinctive names and phrases rather than accepting a general web result. Confirm spelling, the correct edition, publication date, units, denominator, geographic scope, and whether a number is a forecast, a one-time figure, or a recurring measure. A number without its population, time period, and method can be technically accurate yet misleading.
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Read the source, not just the search result
Open the document and find the passage, table, definition, or data record that bears on the claim. Check whether the wording is conditional, whether the surrounding paragraphs add an exception, and whether the source has been superseded. Google Search Central’s guidance emphasizes manual fact-checking because generated text can predict plausible wording without retrieving a verified fact.
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Use independent confirmation for disputed or unfamiliar points
The House of Commons Library recommends checking claims against reputable sources and assessing whether they remain current. For a contested or surprising assertion, locate a second authoritative source that reached its conclusion independently. Agreement between two pages that copied the same press release is not genuine independent confirmation.
How can I audit the citations and links in an AI answer?
A citation is a lead to evidence, not evidence by itself. Open each link and test four things: existence, relevance, authority, and support.
- Existence: Does the URL resolve to a real document rather than a missing page, a generic home page, or an unrelated result?
- Relevance: Does the source address the same subject, population, jurisdiction, version, and time period as the claim?
- Authority: Is the publisher competent and accountable for this information? An official record, recognized professional body, or original research source is generally stronger than an unattributed summary.
- Support: Does the cited passage actually establish the statement as written? Check for omitted qualifiers, changed numbers, and conclusions the source does not make.
Watch for citations that look precise but cannot be found, quotations with no original wording, references that point to a source discussing a different issue, and a single citation attached to several unrelated assertions. OpenAI and British Columbia guidance both stress that the presence of a citation does not guarantee that it is genuine or supportive.
How do I check whether an answer is complete and logically sound?
After verifying individual facts, evaluate the response as an argument and as an answer to the actual request.
Check coverage
List every part of the question and map it to a section of the response. Look for missing definitions, prerequisites, exceptions, affected stakeholders, implementation steps, costs, risks, and alternatives. A short answer may be appropriate, but it should be short because the task is narrow, not because the model silently dropped difficult parts.
Check the connection between evidence and conclusion
Ask whether the cited facts justify the recommendation. A source may show that a treatment was studied without proving that it is suitable for a particular person; a report of correlation does not establish causation; a policy description does not necessarily answer how an individual case will be decided. Identify assumptions and test whether the conclusion changes when one assumption is removed.
Separate fact, interpretation, and advice
Rewrite paragraphs with labels such as “documented fact,” “inference,” “uncertain,” and “recommended next step.” This exposes places where a model has presented an interpretation as if it were a quoted rule or where a recommendation depends on values the user has not supplied.
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Look for missing perspectives
Consider who might be affected but absent from the answer: customers, employees, children, people with disabilities, minority jurisdictions, or users with a different technical setup. The University of Alberta’s Check, Analyze, Reflect approach and British Columbia’s review guidance both call for examining context and omissions, not merely correcting typos.
Should I use lateral reading when checking an AI answer?
Yes. Lateral reading means leaving the original page to investigate the publisher, its purpose, its evidence, and how other credible sources describe the issue. The US Naval War College’s AI-literacy materials recommend this kind of source evaluation rather than judging a page by its design or confident language.
- Open a new search and identify who publishes the source, what expertise or authority it has, and who is accountable for corrections.
- Search the source’s distinctive claim in quotation marks and compare coverage from independent institutions.
- Check whether the page is quoting an older document, an advocacy position, a marketing claim, or a preliminary finding.
- Return to the original source and record the strongest passage that supports or disputes the AI claim.
Lateral reading is especially useful when the answer cites an unfamiliar organization, a secondary explainer, a viral post, or a page with no clear author or date.
How should I compare two AI-generated answers?
Run the same prompt, constraints, and date context through both systems, then compare their claims against sources. Do not treat a disagreement as a vote in favor of the more polished answer; neither system is an authority merely because it agrees with the other.
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| Comparison dimension | Questions to ask |
|---|---|
| Claim-level accuracy | Which specific statements survive checking against authoritative sources? |
| Evidence quality | Do the cited sources exist, fit the claim, and support it in context? |
| Currency | Does either answer use an outdated rule, version, office-holder, price, or statistic? |
| Completeness | Which answer covers exceptions, stakeholders, assumptions, and counterarguments? |
| Clarity about uncertainty | Does the answer distinguish evidence, interpretation, prediction, and unknowns? |
| Review burden | How much checking is required, and what is the consequence if an error remains? |
These dimensions support a reasoned choice about which draft is easier to verify; they do not establish a universal ranking of AI systems. A shorter answer with fewer unsupported claims may be safer than a comprehensive-looking answer that creates a large verification burden.
What should I do with claims I cannot verify?
Choose among use, revise, and reject based on consequence.
Use verified portions
Keep statements that are supported by current, appropriate evidence. Preserve the source, date, and scope alongside the text so a later editor can reproduce the check.
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Revise claims that need context
Add the missing jurisdiction, date, definition, exception, uncertainty, or attribution. If the source supports only a narrower statement, rewrite the sentence to that narrower scope rather than leaving the stronger wording.
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Delete a claim when you cannot find adequate evidence and an error would matter. Do not retain it merely because it sounds plausible, appears in several generated answers, or would make the explanation more complete.
For medical, legal, financial, safety, employment, education, or public-service decisions, show the checked material to a qualified person with responsibility for the outcome. The reader remains accountable for how an AI output is used; transferring the text from a model to a document does not transfer that responsibility.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Are writing-style clues useful for spotting AI errors?
Only as prompts to inspect the substance. Repetition, generic transitions, excessive certainty, oddly specific details, or a smooth “AI-like” voice can occur in human writing and in accurate machine-generated writing. The House of Commons Library says style indicators are not definitive, and TUM likewise emphasizes that likely-sounding language is not verified language.
Do not reject a claim because it sounds machine-written, and do not accept it because it sounds human. Check the claim, its evidence, its date, and its scope.
What does a practical review record look like?
For work that will be reused or audited, save the prompt, the unedited output, the date, the model or service version if available, and your claim log. For each material claim, record:
- the exact wording you evaluated;
- the consequence if it is wrong;
- the authoritative source and its publication or update date;
- the passage, table, or data that supports or contradicts it;
- the jurisdiction, population, version, and time period;
- the reviewer’s decision: accepted, narrowed, corrected, or removed;
- any unresolved question assigned to a subject-matter expert.
For changing information, schedule a recheck rather than assuming today’s verification remains valid indefinitely. NHS Education for Scotland’s AI-literacy guidance also stresses reference checking and independent sources, which are useful habits even when the initial answer appears straightforward.
What is the safest overall rule?
Use AI-generated answers to accelerate drafting, question formation, and information triage—not to bypass evidence or accountability. The higher the consequence, the more your workflow should shift from trusting a response to documenting each claim, checking primary material, testing omissions and reasoning, and obtaining expert approval. An answer is ready to rely on only after the parts that matter have earned that reliance through evidence.
Frequently Asked Questions
Should I ask an AI system to provide sources with every answer?
Yes, asking for sources can make checking faster and can reveal which claims the system considers important. Treat the list as search leads: request the exact document, section, page, or data table, then open the original and verify the wording yourself.
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Can another AI model fact-check the first model?
A second model can identify possible omissions or generate search terms, but agreement between models is not independent evidence. Resolve the disagreement with an authoritative source or a qualified reviewer, especially when the decision is consequential.
What if the cited source is behind a paywall or no longer available?
Look for the issuing organization’s current public record, an official archive, a library copy, or a later document that explicitly replaces it. Until you can inspect evidence adequate to the claim, mark the statement unverified rather than inferring what the inaccessible source said.
Can an AI critique its own answer reliably?
Self-critique may surface contradictions, missing steps, or questions to investigate, so it is useful as a preliminary pass. It cannot prove that a citation exists, that a fact is current, or that the model’s revised wording is correct; external evidence is still required.
How often should a verified AI-assisted document be reviewed again?
Set the interval according to how quickly its facts and consequences can change. Recheck immediately when a law, policy, software version, price, safety recommendation, or responsible organization changes, and record the new source date with the revision.
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