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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallBefore publishing AI-generated or AI-assisted copy, manually fact-check every material claim and review the content for accuracy and trustworthiness. Google Search Central explicitly says this review is critical—and it applies not only to article text but also to titles, meta descriptions, structured data and image alt text.
Why AI-generated content needs a manual fact-check
An AI draft is a starting document, not evidence. Generative models predict likely sequences of words; a fluent, confident sentence can still be inaccurate. Checking whether the prose sounds plausible—or whether an AI tool supplied a citation—is not the same as checking the underlying claim. Google’s guidance on using generative AI content on a website calls for manual review before publication.
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Google does not prohibit using AI or automation simply because of how content was produced. Its 2023 guidance says the concern is using automation primarily to manipulate Search rankings; the goal remains useful, original, high-quality content made for people. Google also says its systems place greater emphasis on reliability for topics where information quality is especially important, including health, civic and financial information. That is a reason to apply heightened editorial scrutiny to consequential claims, not a substitute for professional or legal standards. See Google Search’s 2023 guidance about AI-generated content.
How to fact-check an AI draft before publication
1. Extract the claims that need checking
Read the full draft and identify each discrete statement that could be true or false: dates, names, statistics, quotations, cause-and-effect claims, policy descriptions and assertions about what a product or organization does. Check material claims wherever they appear, including headings, summaries, captions and metadata. Prioritize claims by their likely reach and importance, but do not leave a central claim unchecked merely because it is difficult to verify. The International Fact-Checking Network’s Code of Principles describes selecting claims primarily by reach and importance and explaining that selection where possible.
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2. Trace each claim to evidence
Open the cited source and inspect the relevant passage, table or dataset. Do not rely on an AI-generated summary, a search snippet or a citation that you have not verified. Prefer a suitable primary source; if the best available support is secondary, explain why it is being used. Make the evidence visible enough that another editor—or a reader—can retrace the check.
A working claim log can help keep the review reproducible. For each item, record the claim as written, source and publication date, the precise supporting evidence, relevant counterevidence or caveats, the editorial finding and any correction needed. This is a practical editorial aid, not a form mandated by Google.
3. Look for corroboration and counterevidence
For important claims, seek another named source where possible. Record evidence that supports the statement as well as evidence that challenges it, and assess both using the same standard. If sources conflict, preserve the disagreement rather than smoothing it into a certainty. Keep scope attached to the claim: geography, date, population, edition or other limits may change what the evidence actually supports. The IFCN principles call for multiple sources where possible, consideration of counterevidence and consistent standards.
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- Quotes: Check the exact wording, speaker and the role the person held when speaking.
- Statistics: Preserve the original publisher, population, measurement period and date. Do not make a result sound broader or newer than its source.
- Source context: Consider whether a source has an interest readers would reasonably want to know about.
- Authorship: Confirm author credentials rather than accepting credentials invented or embellished by a generated draft.
Google’s guidance on helpful, reliable, people-first content emphasizes clear sourcing, evidence of expertise and accurate authorship.
5. Review images and unfamiliar sources
For an image, Google’s About this image feature may provide context such as when Search first saw that image or a similar one, earlier appearances on other pages, how other sites describe it, and creator-supplied metadata when available. Fact Check Explorer can help find whether an image appears in an existing fact-check. These features can point to useful leads; they are not conclusive authentication for every image. Google’s overview of Search tools for checking facts, images and sources also describes using About this result or page for background on unfamiliar websites. That background can inform what to inspect next, but it does not prove an individual claim.
6. Separate media provenance from factual truth
Origin and editing signals answer a different question from whether a sentence or image claim is true. In a May 19, 2026 announcement, Google described SynthID checks for image, video and audio, C2PA Content Credentials for learning whether content is an unaltered camera original or has been modified and by which tools, and an enterprise AI Content Detection API with fact-checking and labeling use cases. Those capabilities concern provenance, alteration or detection; they do not by themselves establish the truth of a factual claim. The announcement described expansion and rollout, not universal access. Check current documentation before assuming a feature is available in a particular region or for a particular media type. See Google’s announcement on understanding how content was created and edited.
7. Edit, document and correct
If evidence does not adequately support a claim, remove it or rewrite it. Where evidence is mixed or time-bounded, qualify the claim precisely. Keep source links and review notes so another editor can retrace the decision. If an error is confirmed after publication, correct it openly and, where possible, make the correction discoverable to readers who saw the original. The IFCN Code calls for transparent methodology and open corrections.
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When AI substantially helped create content, consider explaining how automation was used and why it was useful if readers would reasonably want that context. Keep the disclosure accurate and proportionate; do not imply that AI independently verified the work.
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Review the whole page, not just the article body
Google’s guidance, marked updated October 1, 2026, explicitly extends manual review to metadata that may appear in Search. Check the title, meta description, structured data and image alt text alongside the visible copy. A correct article can still mislead if its search snippet overstates a result, its structured data contains invented details or its image description assigns an unsupported meaning.
What fact-checking tools can—and cannot—tell you
Search tools can help locate a source’s background, an existing fact-check, or an image’s history and available metadata. Use them to find context and evidence, then open and evaluate the underlying material. A tool’s label, provenance signal or detection result is not a verdict on the accuracy of a claim.
Google’s 2026 announcement describes an enterprise detection API, but the cited material does not establish independent accuracy rates for AI-text detectors across languages, genres or degrees of editing. A detector score therefore should not be presented as proof of authorship or factuality. Likewise, a media-origin signal does not establish whether a caption or claim about that media is true.
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FAQ
Does Google ban AI-written content from Search?
No. Google’s 2023 guidance says appropriate AI or automation use is not against its guidelines when it is not used primarily to manipulate rankings. The content still needs to be useful, original and reliable.
Can an AI detector prove a passage was written by AI?
The cited sources do not establish independent, broadly applicable detector accuracy rates or show that a score proves authorship. Treat detection as a signal requiring context, not as proof.
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