There is no dependable single test that proves a website article was written by AI. The most defensible approach is layered: read the page as a source, look for the publisher’s disclosure and evidence trail, treat text-detector scores as clues rather than verdicts, and use provenance checks only for the media formats and watermark systems they actually support. A missing watermark, metadata record or detector hit does not prove that a person wrote the content.
Start by defining what you are trying to establish
“Generated by AI” can describe several different situations. A publisher might have used a model to draft every paragraph, to outline an article that a person rewrote, to edit grammar, or to create an image while a human wrote the page. Those are materially different claims. A detector score usually cannot tell you which workflow occurred, who accepted the final wording, or whether the factual claims are sound.
For a careful check, separate three questions:
- Was automation used? This is mainly answered by a publisher disclosure or a reliable production record.
- Can a particular signal be detected? A watermark, credential or metadata field may answer this for supported content.
- Is the article trustworthy? That requires checking authorship information, sources, dates and the claims themselves. Provenance is not proof of accuracy.
Keeping these questions separate prevents the most common mistake: treating a probability score or a missing technical signal as proof of authorship.
A reliable checking workflow
1. Read the page as a source
Begin with ordinary source criticism. Record the named author, publisher, publication date, update date, editorial policy and the references or links supporting important claims. Follow those links to the original evidence rather than accepting a citation at face value. Check whether dates, quotations, statistics and descriptions match the cited material.
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These checks tell you about credibility and traceability, not the writing method. A carefully sourced article may still have used an AI drafting tool; an unsourced article may have been written entirely by a person. Do not present a strong evidence trail as proof of human authorship, or weak sourcing as proof of AI use.
- Is a real person or organization identified as responsible for publication?
- Does the page show when it was first published and when it was last updated?
- Are references specific enough for another reader to verify?
- Do the linked sources actually support the surrounding sentence?
- Are there signs of review, such as an editor, corrections policy or contact route?
2. Look for an explicit AI disclosure
Search the article, author page, editorial policy and terms for a description of automation. A disclosure may explain that a model generated a draft, translated text, suggested headlines, produced an image or assisted with editing. Google’s guidance says publishers should consider explaining how automation was used when that information makes sense for their audience.
Treat the disclosure as evidence of what the publisher says it did, not as a sentence-by-sentence audit. A statement that an article was AI-assisted does not establish that every paragraph came from a model. Conversely, silence is not proof that no automation was used: publishers may have no disclosure policy, may use tools for routine editing, or may simply omit the information.
Save the wording and the page date if the question matters professionally or legally. Policies can change, and an article may be updated without preserving the earlier production notes.
3. Do not ask a chatbot for an authorship verdict
Asking ChatGPT, “Did you write this?” is not an authorship record. OpenAI’s Help Center states: “ChatGPT has no ‘knowledge’ of what content could be AI-generated or what it generated.” A chatbot can produce a plausible yes or no, but it has no reliable memory that connects a web page to a particular generation event. It may also recognize familiar phrasing incorrectly or confidently invent an explanation.
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The same limitation applies when you paste a passage into a general-purpose conversational model and ask it to identify the generator. Use a chatbot, if at all, to help list claims for fact-checking or to explain a technical term—not to certify who wrote the passage.
4. Treat text-detector output as a lead
Text detectors analyze patterns within the text and return a result according to their own method. The result might be a probability, a label, highlighted passages or a statement that the sample resembles model output. None of those formats, by themselves, proves that AI generated the article.
The available evidence does not establish comparative accuracy rates for general-purpose third-party detectors on current web articles. Do not quote an invented accuracy percentage, rank one detector as the most reliable, or claim that a particular score proves generation. A detector may be affected by the language, length, topic, editing, translation, quoted material and the model or detector version involved.
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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11If you use a detector, preserve the exact text submitted, the date, the tool’s name and version if shown, and the complete result. Explain that the output is a clue requiring corroboration. A high score can justify closer source checking; it cannot justify the statement that the author used AI. A low score cannot rule AI use out.
5. Check media provenance separately
Images, video and audio can carry technical signals that are different from anything available in the page’s prose. Check the original file, not a screenshot or a recompressed copy, when possible.
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- SynthID: SynthID detects a specific watermark associated with supported Google AI content. A positive result concerns that supported watermark; it is not a universal detector for every generator, model or web page. A negative result does not prove that a person created the media.
- Content Credentials: Content Credentials and ordinary file metadata may describe creation or modification history when the information is present and preserved. They can help explain a file’s origins and editing sequence, but they do not alone establish authorship, responsibility or the truth of the article’s claims.
- OpenAI provenance checks: OpenAI’s Content Provenance API is not a general-purpose detector for content from every AI system. Text verification is limited to approved organizations, and provenance can be missing or degraded.
Do not transfer a result from an image to the surrounding article. An image with a supported AI watermark shows something about that image’s production, not who wrote the headline or whether the text was machine-generated.
6. Report exactly what the evidence shows
A useful report names the signal, the tool or standard that recognized it, the content it applied to, and the uncertainty that remains. For example: “The attached image produced a positive SynthID result for a supported watermark. The page text was not authenticated, and the watermark does not establish who published the article.” That is stronger than saying, “The website is AI-generated.”
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What each check can and cannot tell you
| Check | What it can indicate | What it cannot establish |
|---|---|---|
| Byline, dates and references | Who claims responsibility, when the page was published or updated, and whether important claims have a traceable evidence trail | Whether a person or model produced the wording |
| Publisher disclosure | What the publisher says about its use of automation | That every sentence followed the declared workflow, or that undisclosed automation was absent |
| Generic text detector | That a sample matches patterns used by that detector’s method | Definitive authorship, the specific model used, or a universal probability of AI generation |
| Chatbot answer about its own writing | At most, a generated opinion or explanation | A reliable record that the chatbot produced the passage |
| SynthID result | Presence of a supported watermark associated with supported Google AI content | Use of every other generator, authorship of page text, or the truth of the content |
| Content Credentials or metadata | Available creation or editing history for supported media and preserved records | Complete history when records are absent, or proof of who is legally responsible |
How to handle common evidence patterns
The page openly says AI was used
Quote or summarize the disclosure, identify the stated role of automation, and keep the claim within that scope. “The publisher says a model generated an initial draft” is precise. “Every sentence was written by AI” goes beyond the evidence unless the publisher explicitly makes that claim and provides a verifiable record.
A detector gives a high AI score but the publisher says nothing
Record the detector result as an unverified lead. Inspect the byline, references, update history and editorial contacts, then fact-check the article’s consequential claims. You can report that the detector flagged the sample; you cannot report the score as proof of generation.
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The article has polished prose but no technical provenance
That is an absence of evidence, not evidence of human authorship. Text may have been copied into a new content-management system, edited by several people, translated, or generated without a supported watermark. Return to disclosure and source-traceability checks.
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Limit the conclusion to the file and signal. Verify that the file tested is the one displayed, note any resizing or recompression, and check whether the page labels the image as illustrative, synthetic or edited. Then assess the article text independently.
The page has no byline, references or contact information
That is a credibility warning regardless of the production method. Explain that responsibility and verification are difficult to establish. If the page makes consequential claims, seek the original documents or a more accountable source rather than trying to settle authorship with a detector.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Text checks and media checks are not interchangeable
People often combine an image result, a page’s HTML metadata and a prose detector into one overall “AI score.” That creates false precision. Each signal has its own scope:
- A prose detector examines the submitted text and the patterns recognized by its model.
- A watermark check examines whether a compatible signal survives in a supported file.
- Metadata and Content Credentials describe records attached to a file, if those records remain intact.
- Source checking evaluates whether claims can be traced and verified.
A page can contain human-written text with an AI-generated illustration, AI-assisted text with a human-created photograph, or copied material with no provenance record at all. State which component you examined instead of assigning one label to the entire website.
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Provenance is not the same as truth
Creation and editing history can answer “what happened to this file?” It cannot answer “is the claim accurate?” A credential showing that a camera captured an image does not make a caption truthful. A supported AI watermark does not make an accompanying statistic false. Conversely, an article with no credential can still be factually correct.
For documentary or news material, verify the underlying claim separately: find the primary document, compare the date and location, check whether quotations are complete, and look for independent confirmation where the stakes justify it. Keep the authorship question and the fact-checking question in separate paragraphs in your report.
Search guidance is not an authorship detector
Google’s guidance distinguishes AI use from its search policy. Using AI is not itself the policy violation described in that guidance; producing many pages without adding value may fall under scaled content abuse. That policy helps publishers understand quality expectations. It does not provide a method for determining how a particular article was authored, and a search ranking is not evidence of human or machine writing.
A concise reporting template
When you need to explain your findings to an editor, researcher or audience, use four parts:
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- Signals found: quote the publisher disclosure, identify the detector and its output, or name the supported watermark or credential.
- Limits: state whether the signal applies to text, an image, audio or video, and whether it can identify a specific system.
- Remaining uncertainty: say what cannot be established and list the factual claims that still require verification.
Example wording: “The publisher discloses AI-assisted drafting. A third-party text detector also flagged portions of the supplied passage, but no comparative accuracy evidence establishes that the score proves generation. The article’s claims were checked against the linked primary sources.” This separates observed facts from interpretation.
Practical checklist
- Capture the page URL, title, byline and publication or update date.
- Read the publisher’s AI-use and editorial policies.
- Follow references and test the article’s important claims against original evidence.
- Do not ask a chatbot to certify that it wrote the passage.
- If using a detector, preserve the submitted sample and report the output as a clue.
- For media, test the original file with a tool that supports the relevant watermark or credential system.
- Record whether metadata may have been stripped or altered.
- Keep text authorship, media provenance and factual accuracy as separate conclusions.
- Use “no supported signal found” rather than “human-written” when checks are negative.
What a responsible conclusion sounds like
The strongest conclusion is usually narrower than the question. You may be able to show that a publisher disclosed automation, that a particular file carries a supported watermark, or that a detector flagged a passage. You generally cannot prove from a generic detector score, a chatbot response or missing metadata that an entire website was generated by AI. Contact the publisher about disputed production details, and judge the article’s substance by the quality and traceability of its evidence.
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