Wikipedia:Signs of AI-generated comments

From Wikipedia, the free encyclopedia

This is a list of writing and formatting conventions typically found in comments written by Wikipedia users who are (or have been) suspected of using large language models or similar technology to write content, with real examples taken from talk pages and other discussion pages. Comments suspected of having been pasted from an LLM may be collapsed via {{collapse AI}} per WP:AITALK. Using AI to write comments is considered disruptive, and editors who do so may be blocked if they persist after being warned.

Although several of the tells mentioned at Wikipedia:Signs of AI writing (including boldface, em dashes, curly apostrophes and quotation marks, negative parallelisms, vertical lists, Markdown, and the rule of three) often appear in such comments, this project page only includes tells that typically do not appear in content added to articles or drafts.

Moreover, this list is descriptive, not prescriptive; it consists of observations, not rules. Advice about formatting or conduct can be found in the talk page guidelines, but does not belong on this page.

Content

Canned assurance of quality, good faith, and adherence to policies and guidelines

Most people on Wikipedia want others to believe that they're here for the right reasons and are willing to follow the rules, and may insist that they make their contributions with such rules in mind. AI chatbots, however, have a strong tendency to communicate this in a specific way: invoking policies, guidelines, and standards as a broad, formal, and abstract whole, as in legalese, and often using "AI vocabulary" to do so.

Examples

Links to searches

Assertions of a topic's notability

Whereas AI-generated articles emphasize their subject's impact, AI-generated comments may exaggerate how notable that subject may be under Wikipedia's guidelines.

Examples

Claims of responsibility for content

When called out for using an AI to write or rewrite their content, some users will admit that they used AI tools to write or rewrite their content, but then follow that up with an assurance that they have checked their content to ensure it aligns with Wikipedia's editorial guidelines, or that the words in their comments truly reflect their thoughts.

Examples

From this comment and this comment left at Talk:Arthur Katalayi in October 2025

Canned offers to receive constructive criticism

Expressions of willingness to take constructive criticism for edits are very common in AI comments by users whose drafts were declined by reviewers, or in rare cases, themselves. The difference between this sign and similar reassurances by conscientious humans will generally become obvious after you actually provide that criticism.

Examples

Could you kindly provide me with specific feedback or reasons for the decline so that I can make the necessary improvements to the article? This will help me better understand and rectify any issues that may have caused the initial decline.

I'm committed to contributing valuable content to Wikipedia and am open to making revisions to ensure the article meets Wikipedia's standards and guidelines. Your guidance would be greatly appreciated.

Once I've made the necessary revisions, I would be grateful if you could reconsider the article for approval. Your assistance in this matter would be invaluable, and I'm eager to work together to ensure the article is a valuable addition to Wikipedia.

I am open to any suggestions or feedback from experienced editors to ensure that the modifications I propose maintain the integrity of the article.

If there are specific areas that need further attention or modification, I am more than willing to make adjustments. I highly value the opportunity to contribute to Wikipedia and would be grateful for any guidance you could provide to help my article meet the necessary standards for publication.

From multiple December 2024 comments at the AfC help desk

I am happy to address any further concerns or comply with any additional requirements to demonstrate my commitment to responsible editing.

If you or any editor have any specific sections that still feel promotional, unclear or non-neutral, I would really appreciate guidance so I can adjust them accordingly.

From this December 2025 comment at the AfC help desk

I understand the concern about AI-generated drafts flooding AfC, and I respect the need to maintain quality standards. If there are specific sections where the tone reads as machine-generated, I'm happy to rework those. I'd also welcome any feedback on sourcing gaps - I want this to meet Wikipedia's standards properly.

Could you point me to which parts raised the flag? That would help memake [sic] targeted improvements before resubmitting.

Links to searches

Complaints about accusers acting on speculation

When a user is confronted for allegedly pasting content from a large language model, they will likely dismiss these concerns as unsubstantiated speculation based on tone or writing style rather than hard evidence of LLM use. Most if not all users who do so also tell those who confront them to just point out what needs to be improved and focus on that instead of calling them out.

Examples

From this comment, this comment and this comment left at User talk:Damjana12 in October 2024

From this comment, this comment, this comment, this comment and this comment left at the AI noticeboard in May 2026

Canned requests to focus on content instead of conduct

In many cases, editors have responded to accusations of AI use by denying that they have used AI to write content (or that Wikipedia prohibits doing so) and calling for discussions to instead be focused solely on the improvement of affected articles. Such editors often ask accusers to help them by pointing out which contributions have tone issues or other problems.

When told that the general pattern of their editing has been disruptive, they often dismiss the accusation as being merely speculative, unfounded, or having no basis in policy, and accuse their critics of acting in a manner that they believe is uncivil, hostile, dismissive, unprofessional, counterproductive, or an affront to Wikipedia's collaborative nature. Persistence from others is interpreted as aggression; if challenged sufficiently they may state their intent to withdraw from the discussion as it has become "emotionally charged". Since the editor did not write this comment themselves, they will often continue the discussion or return to it shortly afterwards.

AI will seldom confirm that it's being used without the prior consent of the user, so if the response is vague, sidesteps the question or considers it to be a personal attack, this may be a sign of AI use.

Examples

From this comment and this comment left at the reliable sources noticeboard in December 2024

From this comment and this comment left at User talk:Grayfell in February 2026

From this comment, this comment, this comment and this comment left at the AI noticeboard in June 2026

Denial that Wikipedia prohibits using AI to write content

When confronted about using AI to write content, some users falsely claim that Wikipedia allows large language models to be used to generate content, and that whether the content they generate adheres to Wikipedia's other content guidelines matters more than how the content has been produced.

Examples

From this comment and this comment left at the AI noticeboard in May 2026

Non-existent policies or guidelines

When AI chatbots try to cite Wikipedia's policies or guidelines by mentioning shortcuts, they have occasionally misattributed hallucinated policies or guidelines to specific pages, including to pages that were never intended to be cited in such a manner to begin with.

Examples

From this comment and this comment left at the AI noticeboard in June 2026

Non-existent shortcuts

In some cases, users of AI chatbots have pasted text containing hallucinated shortcuts that do not redirect to any existing page at all.

Examples

Confusion over the reason for a declined draft

AI chatbots cannot read the decline notice left on the draft, and can only respond to whatever information regarding the declined draft that the user gives them. As a result, AI-generated questions regarding declined drafts will often express uncertainty or request clarification over the reason a draft was declined, even if the decline notice on the draft is very clear. They may even compose self-contradictory comments that simultaneously acknowledge the specific reason for the draft's decline, but go on to say that they are trying to understand whether that was really the reason, or whether it was declined for some completely unrelated reason.

The latest decline says the draft needs multiple published secondary sources that provide significant coverage, are reliable, and are independent. I understand the concern... I am trying to understand whether the problem is mainly that these sources are not strong enough for WP:BIO / WP:NARTIST, or whether the draft structure and tone are still the main issue.

How could the "draft structure and tone" still be the "main issue" when it has just been specifically acknowledged what the issue is?

I am requesting guidance on Draft:Alexis Marcou after repeated AfC declines... I am trying to understand whether the issue is mainly source quality, article tone, or both before making any further changes.

From this archive of the Articles for creation helpdesk concerning a draft that was declined for not meeting WP:NPERSON and reading like an advertisement

Note that the latest decline notice on that draft when this question was asked was for both notability and promotional tone; so the answer to this question is obviously 'both'.

Is the primary issue related to notability, sourcing, tone, conflict of interest, or article structure?

In particular, I would like to understand: Whether the issue relates to notability, sourcing, or tone If any specific sections need revision or removal

Language and grammar

Itemization of content policies

Whenever LLM users bring up a few of Wikipedia's policies and guidelines, they tend to mention each one by name. In some cases, each policy's title is written in title case and its corresponding shortcut is mentioned in parentheses. This has sometimes been the case when the user attempts to either assure others that their content is compliant or request input to help them ensure such compliance. Editors might name-drop policies and guidelines in this fashion to exaggerate their comprehension of the rules and make a point that their reasoning is based on them, even though AI chatbots sometimes get them wrong.

Examples

Moving forward, I will strictly adhere to Wikipedia’s Neutral Point of View (NPOV) and verifiability guidelines, ensuring that all contributions are non-promotional, well-sourced, and align with Wikipedia’s standards.

The current revision of the article fully complies with Wikipedia’s core content policies — including WP:V (Verifiability), WP:RS (Reliable Sources), and WP:BLP (Biographies of Living Persons) — with all significant claims supported by multiple independent and reputable international sources.

Thank you for your question. Yes, I did use an AI tool to assist with parts of initial drafting process. However, I understand that Wikipedia requires all content to meet its core policies, including verifiability, neutrality, and no original research.

As part of the ongoing rewrite, I am reviewing and rewriting the article in my own language to ensure it fully complies with Wikipedia’s guidelines, with proper sourcing and independent verification. I appreciate your patience and any constructive suggestions on improving the article.

Links to searches

Use of the word concrete as an adjective

Comments posted by suspected by AI users often use the word concrete as an adjective, especially in cases where users insist on being given "concrete examples" of text that needs improvement or "concrete evidence" that they used AI asides from "stylistic indications". When users don't get the "concrete evidence" or "concrete examples" they demand, they dismiss the AI accusations against them as subjective speculation.

Examples

**Review:** The use of "significantly more" is subjective and requires specific figures to validate this claim. Without concrete financial data from reliable sources, this statement could be misleading or exaggerated. The source provided is a blog.

In the absence of concrete evidence, I propose removing the AI-generated tag immediately to maintain the article's integrity.

Without concrete examples, your concern cannot be evaluated in line with WP:V, WP:RS and WP:BURDEN.

Style

Subject lines

Historically, some comments generated by AI chatbots have begun with text that appears intended to be pasted into the Subject field on an email form.

Examples

Subject: Request for Permission to Edit Wikipedia Article - "Dog"

Subject: Edit Request for Wikipedia Entry

Subject: Request for Review and Clarification Regarding Draft Article

From this November 2024 comment at the AfC help desk

Subject: Concerns about Inaccurate Information

Subject: Behavioral issues and Wikihounding by User:Binksternet

Division of text into titled sections

AI chatbots sometimes generate messages with text broken into sections with titles. In some cases, such text may either appear with Markdown or as plain text when pasted. They may resemble or include inline-header vertical lists.

Misuse of section subheadings

Some LLM-generated comments contain level 2 or level 3 subheadings, or syntax intended to produce those subheadings, sometimes in Markdown, in which cases ## is used to denote each section. In some cases, the syntax for subheadings appears in replies, where indentation prevents subheadings from forming.

Examples

More information From this February 2026 RfC at Talk:Proposed acquisition of Warner Bros. Discovery by Paramount Skydance ...
Close
More information From this June 2026 ANI report ...
Close

Transclusion of article maintenance banners

When mentioning maintenance tags, AI chatbots often just write the names of such templates in curly brackets (e.g. {{Example}}), resulting in unintentional transclusions. These can be avoided by typing tl| between the opening pair of brackets and the template's name (e.g. {{tl|Example}}) so that each mention will instead appear like this: {{Example}}

Examples

More information From this September 2024 comment at Talk:2024 Bangladesh anti-Hindu violence ...
Close
More information From this July 2025 comment at Wikipedia:Articles for deletion/AI book generation (2) ...
Close
More information From this June 2026 comment at Talk:Culture jamming ...
Close

Links to searches

Miscellaneous

Canned unblock requests

When a user is blocked, they might ask an AI chatbot to write an unblock request for them. Many AI-generated unblock requests tend to go something like this:

Dear Wikipedia Administrators,
I respectfully request that the block on my account be lifted. I acknowledge that my recent behavior has been in violation of Wikipedia's standards. My intention was to edit constructively, and I sincerely apologize if my behavior has appeared disruptive. I have since carefully read and reviewed all of Wikipedia's policies and guidelines, and I now understand the importance of adhering to them when editing. Moving forward, I am committed to ensuring that all of my future edits are constructive. If there are any specific concerns that need further clarification, feel free to ask me about them, and I will be happy to provide the answers you may need. I look forward to collaborating in a constructive manner. Thank you for your time and consideration.

In these requests, blocked users often try to assure administrators of their good faith and (future) adherence to policies, express their willingness to communicate, and offer to receive constructive criticism for their edits.

Canned ANI reports

Sealioning

Sealioning is a disruptive practice where someone relentlessly demands users to provide evidence to back up the statements they make. When targets express frustration over the sealioner's behavor, the sealioner criticizes the targets for responding negatively to them, even though they were just asking questions.

Several AI users have resorted to sealioning when confronted about their AI use. They write long comments that sometimes present arguments as entries in bulleted lists or separated into multiple sections. They often ask which specific passages have caused suspicion and need to be fixed, and accuse confronters of acting on unsubstantiated speculation and being uncivil.

Wikilawyering

Wikilawyering is a disruptive practice where someone selectively cites or interprets policies, guidelines, or perceived precedent as justification for their conduct, even if their interpretations go against the purpose of the policies or guidelines they mention. In many cases, users have emphasized their content's compliance (or overlooked their non-compliance) with certain policies and guidelines. This is especially the case for users of AI chatbots, which often generate text that affirms what the user may want others to believe, even if the points they present don't actually hold up against Wikipedia's policies and guidelines.

When an article is tagged as possibly containing AI-generated content, a user might try to defend it by asking accusers to point to specific passages causing concern or reassuring them that the content they've contributed is "neutral", "verified" by citations to reliable sources, and comprises none of the items described in Template:AI-generated, regardless of the amount of actual effort put in to ensure that such claims are true.

Common AI wikilawyering tropes include:

Ineffective indicators

False accusations of AI use can drive away new editors and foster an atmosphere of suspicion. Before claiming AI was used, consider whether the Dunning–Kruger effect or confirmation bias may be clouding your judgement. Detecting LLM texts on the basis of style alone is not as easy as it seems, see WP:AIDETECTIVE. Here are some somewhat commonly-used indicators that are ineffective in LLM detection—and may even indicate the opposite.

  • Letter-like writing (in isolation)  Although many talk page messages written with salutations, valedictions, subject lines, and other formalities after 2023 tend to appear AI-generated, letters and emails have conventionally been written in such ways long before modern LLMs existed. Human editors (particularly newer editors) may format their talk page comments similarly for various reasons, such as being more accustomed to formal communication, posting as part of a school assignment that requires this tone, or simply mistaking the talk page for email. Other tells, such as vertical lists, placeholders, or abrupt cutoffs, are stronger.
  • Canned requests for source assessment (in isolation) – Although a few LLM users who have their drafts declined may go to the AfC help desk to ask for an editor (in some cases, an "experienced" or "uninvolved" one) to advise them as to which sources (out of the ones they're trying to use) help establish the notability of a given topic,[b] such inquiries have also been made by users who don't use LLMs. In some cases, a user might be trying to figure out how certain cells on a particular source assessment table should be filled.

See also

Notes

  1. Some of the search results may be human-written. They are sorted by edit date (latest first) to put results predating ChatGPT on the bottom.
  2. A few examples of such requests can be found via this search link.

References

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