Generative AI and Wikipedia editing: What we learned in 2025
wikiedu.org
wikiedu.org
This has been a rampant problem on Wikipedia always. I can't seem to find any indicator that this has increased recently? Because they're only even investigating articles flagged as potentially AI. So what's the control baseline rate here?
Applying correct citations is actually really hard work, even when you know the material thoroughly. I just assume people write stuff they know from their field, then mostly look to add the minimum number of plausible citations after the fact, and then most people never check them, and everyone seems to just accept it's better than nothing. But I also suppose it depends on how niche the page is, and which field it's in.
[1]: https://changelog.com/podcast/668#transcript-265
[2]: https://en.wikipedia.org/w/index.php?title=Eugen_Rochko&diff...
[1] https://en.wikipedia.org/w/index.php?title=Eugen_Rochko&diff...
> Applying correct citations is actually really hard work, even when you know the material thoroughly.
Why do you find it hard? Scholarly references can be sources for fundamental claims, review articles are a big help too.
Also, I tend to add things to Wikipedia or other wikis when I come across something valuable rather than writing something and then trying to find a source (which also is problematic for other reasons). A good thing about crowd-sourcing is that you don't have to write the article all yourself or all at once; it can be very iterative and therefore efficient.
It's more like, a lot of stuff in Wikipedia articles is somewhat "general" knowledge in a given field, where it's not always exactly obvious how to cite it, because it's not something any specific person gets credit for "inventing". Like, if there's a particular theorem then sure you cite who came up with it, or the main graduate-level textbook it's taught in. But often it's just a particular technique or fact that just kind of "exists" in tons of places but there's no obvious single place to cite it from.
So it actually takes some work to find a good reference. Like you say, review articles can be a good source, survey articles or books. But it can take a surprising amount of effort to track down a place that actually says the exact thing. I literally just last week was helping a professor (leader in their field!) try to find a citation during peer review for their paper for an "obvious fact" in the field, that was in their introduction section. It was actually really challenging, like trying to produce a citation for "the sky is blue".
I remember, years ago, creating a Wikipedia article for a particular type of food in a particular country. You can buy it at literally every supermarket there. How the heck do you cite the food and facts about it? It just... is. Like... websites for manufacturers of the food aren't really citations. But nobody's describing the food in academic survey articles either. You're not going to link to Allrecipes. What do you do? It's not always obvious.
And then you usually want to describe how the food is used. E.g. suppose it's a dessert that's mainly popular at children's birthday parties. Everybody in the country knows that. But where are you going to find something written that says that? Something that's not just a random personal blog, but an actual published valid source?
Ideally you can find some kind of travel guide or book for expats or something with a food section that happens to list it, but if it's not a "top" food highly visible to tourists, then good luck.
It's a big blind spot among the editors as well. When this problem was brought up here in the past, with people saying that claims on Wikipedia shouldn't be believed unless people verify the sources themselves, several Wikipedia editors came in and said this wasn't a problem and Wikipedia was trustworthy.
It's hard to see it getting fixed when so many don't see it as an issue. And framing it as a non-issue misleads users about the accuracy of the site.
It is a dark sunday afternoon, Bob Park is sitting on his sofa as usual, drunk as usual, suddenly the TV reveals to him there to be something called the Paranormal (Twilight Zone music) ..instantly Bob knows there are no such things and adds a note to the incomprehensible mess of notes that one day will become his book. He downs one more Budweiser. In the distance lightning strikes a tree, Bob shouts You don't scare me! and shakes his fist. After a few more beers a miracle of inspiration descends and as if channeling, in the time span of 10 minutes he writes notes about Cold Fusion, Alternative Medicine, Faith Healing, Telepathy, Homeopathy, Parapsychology, Zener cards, the tooth fairy and father xmas. With much confidence he writes that non of them are real. It's been a really productive afternoon. It reminds him of times long gone back when he actually published many serious papers. He counts the remaining beers in his cooler and says to himself, in the next book I will need to take on god himself. The world needs to know, god is not real. I too will be the authority on that subject.
https://en.wikipedia.org/w/index.php?title=Special:WhatLinks...
So maybe that's not a good description of him. But the link you posted is hardly dispositive.
You are now debunked.
(This comment is intentionally stupid, useless and the author knows nothing about the topic)
Example [SPOILERS]: the page for the movie Sorcerer claims that rough terrain caused a tire to pop. The movie never says that, the movie shows the tire popping (which results in the trucks cargo detonating). The next scene reveals the cause, but only to those paying attention; the bloody corpse of a bandito laying next to a submachine gun is shown in the rubble beside the road, and more banditos are there, very upset and quite nervous, to hijack the second truck. The obvious inference is that the first truck's tire was shot by the bandit to hijack/rob the truck. The tire didn't pop from rough terrain, the movie never says it did, it's just a conclusion you could get from not paying attention to the movie.
Citations have become heavily weaponized across a lot of spaces on the internet. There was a period of time where we all learned that citations were correlated with higher quality arguments and Wikipedia’s [Citation Needed] even became a meme.
But the quacks and the agenda pushers realized that during casual internet browsing readers won’t actually read, let alone scrutinize the citation links, so it didn’t matter what you linked to. As long as the domain and title looked relevant it would be assumed correct. Anyone who did read the links might take so much time that the comment section would be saturated with competing comments by the time someone can respond with a real critique.
This has become a real problem on HN, too. Often when I see a comment with a dozen footnoted citations from PubMed they’re either misunderstandings what the study says or some times they even say the opposite of what the commenter claims.
The strategy is to just quickly search PubMed or other sources for keywords and then copy those into the post with the HN footnote citation format, knowing that most people won’t read or question it.
Hope that helps you understand.
There’s a reason /s was a big thing, one persons obvious sarcasm is (almost tautologically) another persons true statement of opinion.
My go too example was the SDI page saying that brilliant pebble interceptors were to be made out of tungsten (completely illogical hogwash that doesn't even pass a basic sniff test.) This claim was added to the page in February of 2012 by a new wikipedia user, with no edit note accompanying the change nor any change to the sources and references. It stayed in the article until October 29th, 2025. And of course this misinformation was copied by other people and you can still find it being quoted, uncited, in other online publications. With an established track record of fact checking this poor, I honestly think LLMs are just pissing into the ocean.
I don't know how it will turn out. I don't have very high hopes, but I'm not certain it will all get worse either.
I guess the conclusion is there simply is no avenues to gain knowledge.
In general, I agree, but I wouldn't want to ascribe malfeasance ("making shit up") as the dominant problem.
I've seen two types of problems with references.
1. The reference is dead, which means I can't verify or refute the statement in the Wikipedia article. If I see that, I simply remove both the assertion and the reference from the wiki article.
2. The reference is live, but it almost confirms the statement in the wikipedia article, but whoever put it there over-interpreted the information in the reference. In that case, I correct the statement in the article, but I keep the ref.
Those are the two types of reference errors that I've come across.
And, yes, I've come across these types of errors long before LLMs.
For news articles especially the recommendation now is to use the archive snapshot and not the url of the page.
It’s not a perfect solution, but it tries to solve the link rot issue.
Not disagreeing - many existing articles on wikipedia have barely any references or citation at all and in some cases wrong citation or wrong conclusions. Like when an article says water molecules behave oddly and then the wikipedia article concluding that water molecules behave properly.
...y'know, I don't want to be that guy, but this actually seems like something AI could check for, and then flag for human review.
Far more insidious, however, was something else we discovered:
More than two-thirds of these articles failed verification.
That means the article contained a plausible-sounding sentence, cited to a real, relevant-sounding source. But when you read the source it’s cited to, the information on Wikipedia does not exist in that specific source. When a claim fails verification, it’s impossible to tell whether the information is true or not. For most of the articles Pangram flagged as written by GenAI, nearly every cited sentence in the article failed verification.
I agree, that's interesting, and you've aptly expressed it in your comment here.
I'm not saying that AI isn't making it worse, but bad-faith editing is commonplace when it comes to hot-button topics.
I think accepting that gets us to the starting line. Then we need to apply a lot of critical thought to sometimes difficult judgments.
IMHO quality newspapers do an excellent job - generally better than any other category of source on current affairs, but far from perfect. I remember a recent article for which they intervied over 100 people, got ahold of secret documents, read thousands of pages, consulted experts .... That's not a blog post or Twitter take, or even a HN comment :), but we still need to examine it critically to find the value and the flaws.
citation needed
Thank you for publishing this work. Very useful reminder to verify sources ourselves!
LLMs definitely fit the use-case of Wiki Edu students, who are just looking to pass a grade, not to look into a topic because of their interest.
Sometimes it is really sad to read from (even PhD level) students on social media about their paper writing practices.
So it's more about how generative AI is a problem in college right now because lazy students are using it to do the work than about Wikipedia itself, I think.
The WikiEdu article clearly demonstrates what everyone should have known already: an LLM has no commitment to the truth. An LLM's only commitment is to correct syntax.
It happens that what is popular is correct often enough for the whole thing to somewhat work but I think it's always gonna be bristle.
What if in fact a large proportion of articles were bot-written, but only the unverifiable ones were bad enough to be detected?
But it looks like Pangram is a text classifying NN trained using a technique where they get a human to write a body of text on a subject, and then get various LLMs to write a body of text on the same subject, which strikes me as a good way to approach the problem. Not that I'm in anyway qualified to properly understand ML.
More details here: https://arxiv.org/pdf/2402.14873
Anecdotally speaking, I'm heavily involved in AI cleanup work on Wikipedia. At this point, I can read article text typical of AI, guess within 6-12 months when that edit was made based on differences in LLM output over the years, and usually be right. (e.g., "delve" was common through early 2024 until GPT-4o killed it; I've seen theories that it's not a GPT-4o thing but rather the result of people avoiding the word when it became a meme, but its frequency dropped off hard even in edits that clearly were not reviewed or edited at all.) Given that Wikipedia has accumulated billions of edits over 25+ years, that says a lot.
These mega corporations are entirely free from blame and you're gonna see to it none of us question their role, right?
I think your analogy would hold if slop creators were creating requirements and contracting OpenAI to build the thing that lets them slop edit Wikipedia and GitHub issues. But since they aren’t, this is breaking the analogy.
You are still within the edit window to change up your analogy (but unfortunately not to completely delete your post), so you have a little time to make it coherent.
For example, previous Secretary of War Lloyd Austin was on the board of Ratheon
https://www.opensecrets.org/revolving-door/lloyd-austin/summ...
Missiles have a lot of legitimate and good uses. They sold to the only entity that can buy them, the government, then redistributed from there.
Missiles will be created because there is financial incentive to do so. If you really want to make the point you're trying to make, at least blame the people who create the financial incentive or the people giving orders. You've omitted the obvious most responsible party.
Its not even unique to Wikipedia. Its really not difficult to find very misleading statements cited through a citation that doesn't even support the claim when you check the original.
I think the point is that it already has.
This happens a lot on Wikipedia. I'm not sure why, but it does and you can see its traces through the Internet as people post the mistaken information around.
One that took me a little work to fix was pointed out by someone on Twitter: https://x.com/Almost_Sure/status/1901112689138536903
When I found the source, the twitter poster was correct! Someone had decided to translate "A hundred years ago, people would have considered this an outrage. But now..." as "this function is an outrage" which honestly is ironically an outrageous translation. What the hell dude.
But it takes a lot of work to clean up stuff like that! https://en.wikipedia.org/w/index.php?title=Weierstrass_funct...
I had to go find the actual source (not the other 'sources' that repeated off Wikipedia or each other) and then make sure it was correct before dealing with it. A lie can travel halfway around the world...
It seems to deflect, even gaslight TFA.
> For most of the articles Pangram flagged as written by GenAI, nearly every cited sentence in the article failed verification.
So why deflect that into convenient other pedantry (surely not under the guise tech forums often do so)?
WSo why the discomfort for part of HN at an assertion AI is being used for nefarious purposes and creation of alternate 'truths'?
This varies wildly by timezone. Usually I get upvoted during European timezones and then brace for the Americans to wake up.
I'm not a fan of certain trends either, but I wouldn't say it's inorganic. It's just a shift in the industry, and humans being human.
But ... isn't this with regards to Wikipedia a much more general problem?
Usually revisions are approved manually by real people. This already can be negative; takes a lot of time; no guarantee that new information is true but old information can be wrong too. To me it seems more as if the problem has much more to do with the quality control problems of wikipedia itself. Yes, AI spam fatigues here but if the quality control steps are bad then AI spam will only make this worse. But AI spam going away, does not mean the quality control steps have gotten any better. These two issues should be separate. Wikipedia needs to find better quality control mechanisms in general. And that also includes existing articles - some are written by people who are experts in the field. But they don't really explain anything at all. So, these articles appear good but are virtually useless for 98% of the people. I am not saying one should dumb down wikipedia, but you need to kind of focus primarily on the average person really - not stupid but not a godlike expert either. Explain it to, say, someone at age 18 or perhaps even a bit less than that.
almost never the case besides a select few articles that get heavily vandalized and require all edits to be approved. otherwise, anyone can edit Wikipedia at any time, which famously is the point of Wikipedia
But as I understand the situation, even the major Deep Research systems still have this issue.
Found your problem right there
I don't care if AI is used. I care about citations.
I don't know what happened between that thread and this, maybe the narrative really changes how people respond.
From https://grokipedia.com/page/Spain#terrain-and-landforms > Spain's peninsular terrain is dominated by the Meseta Central, a vast interior plateau covering about two-thirds of the country's land area, with elevations ranging from 610 to 760 meters and averaging around 660 meters
Segovia is at 1.000 meters, and so is most of the top half of the "Meseta". https://en-gb.topographic-map.com/map-763q/Spain/?center=41....
I still stand on not trusting any of what AI spits out, be it code or text. And it takes me usually longer to check that everything is ok than doing it myself, but my brain is enticed by the "effort shortcut" that AI promised.
The nice thing about grokipedia is that if you have counter examples like that you can provide it as evidence to change it and it will rewrite the article to be more clear.
Meseta Central mean central tableland. Segovia is on the edge of the mountain range that surrounds that tableland, but often referred to as part of it. This is fuzzy though.
Wikipedia says: The Meseta Central (lit. 'central tableland', sometimes referred to in English as Inner Plateau) is one of the basic geographical units of the Iberian Peninsula. It consists of a plateau covering a large part of the latter's interior.[1]
Looking at the map you linked the flat part is between 610 to 760 meters.
Finally, when speaking about the Iberian Peninsula Wikipedia itself includes this:
> "About three quarters of that rough octagon is the Meseta Central, a vast plateau ranging from 610 to 760 m in altitude."[2]
Encyclopedia Britannica (the website not the printed book) is the main competitor to Wikipedia and gets an order of magnitude more traffic than grokipedia. Right now grokipedia is the new kid on the block. It has yet to be seen if its just a novelty or if it has staying power but either way it still has a ways to go before its Wikipedia's primary competitor.
If more people use it then it is more popular. Simple metric.
Approximately 3.2m Americans drink Hard Kombucha.
Approximately 5m Americans use Cocaine.
Simple metric.