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Check an AI summary one factual claim at a time against the original material and, when the stakes warrant it, independent authoritative evidence. A fluent summary is not proof that its claims are accurate, its citations are genuine, or its account preserves the source’s meaning.
What to check in an AI summary
Start by breaking the summary into separate propositions. Check names and roles, figures, dates, quotations, attributions, legal or policy descriptions, and claims about causes, comparisons, or what a source concluded. Split compound sentences: one part may be supported while another is not.
Then compare those claims with the underlying material. A summary can repeat accurate details yet still change the takeaway by dropping a qualification, exception, counterpoint, uncertainty, or risk. UK government guidance warns against using generative AI outputs as the only source on a topic, and Microsoft’s guidance highlights the need to catch omissions that could affect a decision.
How to verify claims step by step
- Extract each claim. Make a checklist of factual assertions rather than judging the summary by its overall tone. Include claims embedded in headings, captions, or conclusions.
- Trace the evidence. Open each citation and follow it to the primary document, dataset, legislation, official statement, or original study where possible. If no citation is supplied, look independently for a competent authoritative source. The House of Commons Library identifies official statistics, primary legislation, government departments, regulators, peer-reviewed research, and its own briefings as examples of reputable material. House of Commons Library guidance on AI and generated text
- Test the source-claim fit. Read enough of the source—including surrounding passages and relevant definitions—to determine whether it supports the exact assertion. A page that mentions the same topic is not necessarily evidence for the claim.
- Check scope and context. Compare the source’s date, geography, population, timeframe, definitions, and caveats with the summary’s wording. For a statistic, confirm what was measured and whether the summary has described it accurately.
- Look for omissions and framing. Compare the summary with the source’s overall argument, not just isolated excerpts. Ask whether it leaves out a condition, uncertainty, contrary finding, or risk that changes the meaning or practical implication.
- Assess the source itself. Consider the publisher’s expertise, proximity to the original evidence, traceability, and possible motivation. Then look for corroboration from a genuinely independent authoritative source when the claim is disputed or consequential. The Commons Library describes “lateral reading”—leaving a page to learn about its publisher and find independent accounts—as one way to assess sources. House of Commons Library guidance on evaluating sources
- Record a result for every claim. Mark each as supported, contradicted, unsupported, or needing qualification, and keep a note of the evidence you checked. This is a practical review method, not a formal classification scheme prescribed by the cited guidance.
- Resolve or remove uncertainty. For a specialist, disputed, or high-impact claim, seek review from a qualified person. If you cannot substantiate a claim, qualify it as unverified or remove it rather than repeating confident-sounding prose.
How to judge whether a source is good enough
Use the following questions when deciding whether evidence supports a particular claim. Authority is claim-specific: a source may be reliable for one subject and not competent to establish another.
#1 Best Overall
- Authority and proximity: Is this the original record, dataset, law, study, or statement, or a secondary account? Is the publisher competent on this subject?
- Accuracy and traceability: Can you inspect the underlying evidence, and does the source represent it faithfully?
- Date and scope: Is the evidence current enough? Do its geography, population, timeframe, and definitions match the claim?
- Context and completeness: Are uncertainty, qualifications, exceptions, and relevant opposing evidence visible?
- Motivation and independence: Could the source have an interest in how the claim is framed? Does the corroboration come from a genuinely independent source?
- Claim-source fit: Does the evidence establish this precise proposition, or merely discuss a related subject?
What to do with citations and facts that may have changed
Open every citation
Do not assume an AI-generated reference is real, relevant, or reliable. Confirm that the cited page exists, inspect what it actually says, and check whether it supports the statement attached to it. British Columbia’s public guidance specifically advises reviewing references for those qualities. Government of British Columbia guidance on reviewing generative AI outputs
Recheck changeable information
Dates, policies, statistics, and other facts can become outdated. Compare the evidence’s date and scope with the claim, and prefer a current primary source where the subject can change. A citation that once supported a statement may no longer establish the current position.
When human review is essential
For consequential decisions, specialist topics, or disputed assertions, do not rely on the AI output alone. Seek independent evidence and, when needed, a qualified subject-matter reviewer. The UK government says not to use generative AI outputs as the only information source on a topic. The Government of Canada’s guidance also cautions that generated content can appear credible while being inaccurate. UK Government guidance on using generative AI Government of Canada guide on generative AI
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Before publishing, make a final human pass over the most consequential claims and follow any disclosure requirements set by your organization or editorial policy. Google Search Central says AI-generated website content should be manually fact-checked for accuracy and trustworthiness before publication. Google Search Central guidance on generative AI content
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Why fluency and AI detectors are not fact checks
Confidence, specificity, and polished prose do not establish that a statement is true. Nor does an AI detector determine whether a claim matches its evidence. To establish accuracy, compare the content with sources; detection is not a substitute for that work.
The House of Commons Library’s Chris Rhodes puts the distinction plainly: “AI should be treated as an assistant, not an authority.” Microsoft’s support guidance makes a related point: “Using AI doesn’t transfer accountability.” Microsoft guidance on validating Copilot output
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