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Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Repair Windows errors before they cause bigger problemsFix Now →Before acting on an AI answer, verify its individual factual claims against reliable evidence. Treat the answer as a lead to investigate—not evidence in itself. AI can produce fluent but false or incomplete statements, including citations that are invented or do not support the claim.
Use a verification process that matches the stakes
A mistaken suggestion for a low-impact task is different from a false claim that could affect someone’s health, money, legal rights, security, or access to public services. The greater the potential harm, the stronger the evidence and review you should require. For consequential decisions, confirm with the responsible authority or a qualified professional before acting.
The UK Government’s Artificial Intelligence Playbook warns that plausible but false AI responses can contribute to harm, legal problems, or security vulnerabilities. The House of Commons Library puts the role succinctly: “AI should be treated as an assistant, not an authority.”
A step-by-step way to check an AI answer
- Pause and identify the consequences. Decide what could happen if the answer is wrong. Use more rigorous checks and expert review when the decision could cause harm or affect another person’s rights.
- Break the answer into checkable claims. Separate factual statements from opinions, predictions, interpretations, and recommendations. For example, check a date, a statistic, a quotation, a person’s role, and a suggested action separately rather than treating a whole paragraph as one claim.
- Find evidence for each claim. You can ask the AI for sources to help locate material, but do not treat its answer or citations as proof. Look for original documents, legislation, official statistics, regulator or agency information, or original research. Use reputable expert analysis when the primary material needs interpretation.
- Open and inspect every citation. Confirm that the link works, leads to the source described, and supports the exact statement—not merely a related topic. Compare the AI’s wording with the source passage, table, or record. A real source can still be misquoted or used to support a claim it does not establish.
- Check date and context. Look at when the source was published or updated, and whether later information may have superseded it. Check that its geography, population, definitions, and units match the AI’s claim.
- Look for independent corroboration. Seek another credible source that relies on its own reporting or underlying records. Several pages repeating the same unsupported assertion are not the same as independent confirmation. If credible sources disagree, identify what evidence each relies on rather than forcing a single confident answer.
- Escalate unresolved questions. Ask a qualified expert when a claim is disputed, technical, or consequential. If the evidence does not settle it, treat it as uncertain rather than letting confident wording stand in for proof.
- Keep a record when the decision matters. Note the exact claim, the source title and URL, its relevant date, the passage or data that supports it, and any caveats that remain. UNESCO’s media-literacy exercise recommends documenting the steps in a fact-check.
What to check in text and citations
Give particular attention to dates, numbers, quotations, names, and claims about what an institution or official did. Trace each one to the underlying evidence. Do not rely on a summary of a source when the original wording or data is available.
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The House of Commons Library’s guidance, Working with AI and spotting AI-generated text, advises treating every factual statement produced by AI as unverified until checked. It also cautions that signs of generated writing are not definitive and that AI-detection tools are unreliable as conclusive evidence. Judge the claim by its sources and support, not by whether text sounds human or machine-written.
How to check images, video, and audio
For media, verify where it came from, when it appeared, and whether the surrounding account is credible. A genuine image or clip can still be misleading if it is old or presented without its original context.
- For a still image, use reverse image search to look for earlier appearances and context.
- For a video or image, check whether its date, location, timestamps, geotags, or source details can be independently verified.
- For suspicious details, treat odd shadows, distorted features, mismatched lip movement, or unusually smooth textures as prompts to investigate—not proof that content is synthetic.
- For provenance information, distinguish evidence about a file’s origin or history from a detector’s guess about how it was made. The absence of a label does not establish authenticity, and a label or detector result needs context.
The Indiana Department of Homeland Security’s misinformation guidance recommends checking sources, dates, corroboration, and reverse-image results. NIST’s 2024 report, Reducing Risks Posed by Synthetic Content, surveys approaches including content authentication and provenance tracking, synthetic-content labeling, and detection. These approaches provide different kinds of evidence; none should be treated as a universal verdict about a particular file.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Keep confidence and evidence separate
A polished answer is not necessarily a reliable one, and a confident citation is not necessarily relevant. NIST’s AI Risk Management Framework describes trustworthiness as context-dependent, with considerations such as validity, safety, security, accountability, transparency, privacy, and fairness. Those system-level considerations do not verify an individual sentence: the specific claim still needs evidence.
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UNESCO’s media and information literacy unit on misinformation offers a classroom fact-checking exercise that distinguishes verifiable claims from opinion and records the checking process. It also lists Craig Silverman’s Verification Handbook for Disinformation and Media Manipulation as a further resource.
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