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English Wikipedia does not permit large language models (LLMs) to generate or rewrite article content. It allows only narrow uses—such as carefully reviewed copyediting of an editor’s own prose and human-reviewed translation into English Wikipedia—and its rules do not automatically apply to other language editions.
What the English Wikipedia rule covers
The practical question is not whether an AI-written paragraph sounds accurate. It is what task the model performed and whether a human can verify every resulting claim against reliable sources. The Meta-Wiki index of project policies identifies English Wikipedia’s guidance as restricting LLM use for creating or rewriting articles. The same guidance also addresses AI-generated images, sources and comments, with only limited exceptions.
| Activity | Status under the English guidance | Conditions or cautions |
|---|---|---|
| Ask an LLM to write a new article or section | Not permitted | Generating publishable article prose is the prohibited use. |
| Ask an LLM to rewrite existing article text | Not permitted | Changing wording, structure or emphasis with a model is still rewriting, even when the editor supplies the original text. |
| Use an LLM to create images, sources or comments | Covered by the AI guidance | The project index describes these categories and notes narrow exceptions. Check the current English Wikipedia policy for the exact boundary of any exception. |
| Suggest basic copyedits to your own writing | Allowed narrowly | A human must review the suggestions; the model may not add content or alter meaning beyond what the citations support. |
| Translate material into English Wikipedia mainspace | Permitted with qualified review | A human skilled in both the source and target languages must review the translation before publication. |
| Use AI to find background material or give feedback | Recommended as a lower-risk use by Wiki Education | It is not a license to paste generated prose into an article. Facts and sources still require independent checking. |
These are English Wikipedia rules. Wikimedia projects are independent communities, so a different language edition may set a different policy. Treat the edition named on the project’s own policy page as the authority for an edit.
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Why generated prose creates a policy problem
Wikipedia’s central editorial test is verifiability: a reader should be able to follow a citation and confirm that the source actually supports the statement in the article. A fluent paragraph, a neutral tone and a footnote do not satisfy that test if the cited publication says something different, says less, or does not exist.
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Language models can combine true details with invented dates, names, quotations or causal links. They can also attach a real citation to a claim that the citation never makes. Wiki Education’s explanation of the policy treats that mismatch—not the mere presence of unusual wording—as the fundamental risk. Unverifiable material damages the encyclopedia’s credibility and should be removed.
The same danger applies when an editor asks for a seemingly harmless rewrite. A model may strengthen a conclusion, remove a qualification or turn an example into a general claim. The Guardian’s 27 March 2026 report reproduced the policy’s warning that LLMs can go beyond the instruction and change meaning so that the result is no longer supported by the cited sources.
Can I use ChatGPT to write a Wikipedia article?
No. Under the English guidance, asking a chatbot to draft a new article, section, lead, summary or replacement passage is the kind of generation the rule prohibits. Having a person lightly edit the output, disclose that AI was used, or add references afterward does not change what the model did.
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An editor can still use ordinary tools to organize notes, search for publications or identify questions that need answering. The safe boundary is that the article’s prose and claims are written from the editor’s understanding of the sources, not copied or paraphrased from a model’s response. If a model supplies a factual lead, treat it as an unverified suggestion and check the underlying source before deciding whether the fact belongs in the article.
The two narrow exceptions
Basic copyediting of your own prose
English Wikipedia permits an LLM to suggest basic copyedits to text you wrote yourself. The permission is deliberately narrow. Human review is mandatory, and the model must not introduce content of its own. A change that adds a fact, interpretation or implication is outside the exception.
Copyediting can also change meaning without adding an obvious new sentence. For example, replacing may with does, removing a limitation, changing the subject of a sentence or merging two claims can make a citation appear to support something it does not. Compare every accepted edit with the source and with your original wording. Reject suggestions that alter scope, certainty, chronology or attribution.
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“Editors are permitted to use LLMs to suggest basic copyedits to their own writing, and to incorporate some of them after human review, provided the LLM does not introduce content of its own.”
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This wording was reproduced by Oliver Milman in The Guardian’s 27 March 2026 report. The policy’s accompanying caution is why a grammar improvement is not automatically harmless: a polished sentence can still overstate its evidence.
AI-assisted translation
AI-assisted translation into English Wikipedia mainspace is listed as permissible when a human who is skilled in both languages reviews the result. Review means more than checking whether the English sounds natural. The reviewer must compare the translation with the original, resolve ambiguous terms, preserve qualifications and confirm that any cited source supports the translated claim.
Wiki Education describes this use as currently allowed but discourages relying on it casually. A machine translation can mistranslate a technical term, flatten a distinction or make an indirect statement sound definite. If the reviewer cannot confidently evaluate both languages and the subject matter, the translation should not be placed in mainspace on the strength of the model output alone.
Using AI for preparation and feedback
Wiki Education presents source discovery, brainstorming and feedback as more defensible uses than drafting. These activities still require human judgment. A chatbot’s list of books may contain nonexistent works, and its summary may omit the very qualification that makes a source usable. Open the publication yourself, check its relevant passage and record the bibliographic details independently.
A practical workflow for staying within the rules
- Identify the project. Confirm that you are editing English Wikipedia and read its current AI guidance. If you are working in another language edition, use that community’s policy instead of assuming the English rule applies.
- Use primary sources for fact-finding. You may use an AI tool to suggest search terms or questions, but locate the books, papers, official records or reputable reporting yourself. Do not treat a chatbot’s citation list as evidence.
- Make a source-based outline. For each proposed statement, note the exact source passage that supports it and any limits on date, geography, population or certainty. An outline is not a generated article; it is a checklist for your own writing.
- Draft the prose yourself. Write the lead, sections and transitions from the sources. Do not paste model output and then try to disguise it through manual paraphrasing; that remains model-generated or model-rewritten content.
- Audit every claim. Follow each citation as a skeptical reader would. Remove statements that the source does not support, even when they are plausible. Check names, numbers, quotations, dates and cause-and-effect language separately.
- Apply copyediting only to your own draft. If you use an LLM for grammar or spelling suggestions, review each proposed change and reject anything that adds information or changes meaning. Keep the source check in view while accepting edits.
- Review translations bilingually. For AI-assisted translation, compare the original and English sentence by sentence, have a reviewer competent in both languages check the result, and correct terminology before publication.
- Do a final human read. Look for unsupported synthesis, missing qualifications, invented references and wording that sounds more certain than the evidence. A clean style is not proof of compliance.
How Wikipedia checks for possible AI text
English Wikipedia’s editing infrastructure includes LLM Paste Check. The MediaWiki documentation records default-on deployment at English Wikipedia on 24 September 2026. The prompt can appear when some text is pasted from an external AI chatbot, with the goals of reminding newcomers about the rules and directing experienced editors to inspect possible pasted text for hallucinations or unverifiable claims.
The feature is not an authorship detector. Its documentation describes detection based on factors including text length and chatbot metadata, so it will not identify every AI-generated passage. A passage that is not flagged can still violate the policy, and a passage that is flagged is not automatically proof that an LLM wrote it.
Wiki Education likewise describes AI-detection systems as signals for additional human scrutiny rather than conclusive evidence. The decisive review remains editorial: inspect the wording, open the citations and determine whether the sources support the claims.
What to do when an edit appears AI-generated
Check the content before the style
Start with the article’s claims and references. Look for citations that do not contain the asserted information, references that cannot be located, unexplained jumps in reasoning and details that conflict with reliable sources. These are actionable problems regardless of how the prose was produced.
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A detector result or paste prompt can justify a closer look, but it cannot establish authorship by itself. Avoid accusing an editor solely because text has a particular rhythm or because a tool assigned a high probability. Explain the specific sourcing or meaning problem and invite correction.
Remove or repair unverifiable material
If a claim cannot be supported, remove it or rewrite it from a source you have checked. If the edit is otherwise useful but contains unsupported additions, retain only the material that can be verified. Discuss disputed edits on the article’s talk page when collaboration is needed.
Common situations and the correct boundary
- “I asked an AI to make my paragraph more encyclopedic.” That is rewriting, not basic copyediting, and falls outside the English exception.
- “I wrote the article and used AI to fix spelling.” This can fit the copyediting exception only when you review every suggestion and the model adds no content or meaning.
- “I translated a foreign-language article with an AI tool.” It can be placed in English mainspace only after review by someone skilled in both languages, with terminology, nuance and citations checked.
- “The chatbot supplied real-looking references.” Do not cite them until you have located the publication and confirmed that it supports the exact statement.
- “The paste checker did not appear.” The absence of a prompt does not grant permission and does not show that text was written without AI.
- “Another Wikipedia allows this.” Verify that project’s own policy. Wikimedia communities do not share one universal AI rule.
Bottom line for editors
For English Wikipedia, keep LLMs away from article generation and rewriting. The defensible uses are tightly limited: human-reviewed copyediting of your own words, qualified human-reviewed translation into English mainspace, and preparatory tasks such as finding sources or requesting feedback. In every case, verifiability controls the outcome. A citation must support the claim, and neither polished language nor an AI-detection result can replace that check.
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