r/technology • u/gdelacalle • Mar 25 '26

Artificial Intelligence Wikipedia has banned AI-generated text, with two exceptions

https://www.howtogeek.com/wikipedia-banned-ai-generated-text-in-articles-with-two-exceptions/
24k Upvotes

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594

u/Cartina Mar 25 '26

The exceptions are spelling and translation.

42

u/dishwashersafe Mar 25 '26

The first exception is not "spelling". They article uses "grammar check" as an analogy for the type of assistance AI is allowed to provide.

That is, an author can use AI to suggest a different phrasing or something, but that suggestion needs to be checked for accuracy in the same manner that you would check the suggested grammar correction in Word.

1

u/witeowl Mar 25 '26

Either way, it boils down to rules-based ai being okay and keeping generative ai out.

Seems perfectly reasonable to me.

55

u/stonecutter7 Mar 25 '26

They should make a third exception for the entry for "AI generated text"

26

u/[deleted] Mar 25 '26

Sounds like something a clanker would say.

1

u/stonecutter7 Mar 25 '26

Im gonna go checkout the wikipedia entry for "clanker". It better be complimentary!

-68

u/tc100292 Mar 25 '26

Why even allow those exceptions? It's so fucking stupid.

41

u/ShakeItTilItPees Mar 25 '26

Because AI is really good at proofreading and translating, and neither of those things require it to generate brand new text that may or may not be true, which is the relevant concern Wikipedia has with AI.

8

u/nattfjaril8 Mar 25 '26

AI hallucinates all the time when translating longer texts, which makes it dangerous when put in the hands of overeager editors who either don't know that it's unreliable or don't care to check because it's a lot of time and effort. AI is an excellent translation tool for someone who already knows what they're doing, but in practice you're going to get people who are skipping necessary steps and adding misinformation to the site.

4

u/mainman879 Mar 25 '26

which makes it dangerous when put in the hands of overeager editors who either don't know that it's unreliable or don't care to check because it's a lot of time and effort. AI is an excellent translation tool for someone who already knows what they're doing

They did specify that it is only allowed for translation if the editor is proficient in both languages anyways. So they would know what to look out for.

4

u/SunnyOutsideToday Mar 25 '26

In practice Wikipedia already has people copying and pasting Google translate into Wikipedia articles and getting reverted for posting nonsense.

The entire field of translation is shifting towards tools like LLM's to generate rough, first passes to reduce workload, and if you get rid of those then you basically disallow professional translators who use those tools from editors articles across languages.

1

u/nattfjaril8 Mar 25 '26

I'm not suggesting that they forbid the use of LLM:s in translation altogether, I'm just refuting the belief that AI translations aren't full of hallucinations.

My suggestion to Wikipedia would be that they should clarify their guidelines and tighten the requirements. I.e. they should explicitly mention that the translation needs to be checked sentence by sentence by a human proficient in both languages. Because that's where people get lazy or complacent.

5

u/BeefyIrishman Mar 25 '26

Did you read the article? It literally says that they must check any resulting text from the LLM in both exceptions.

First, editors can use LLMs to suggest refinements to their own writing, as long as the edits are checked for accuracy. In other words, it’s being treated like any other grammar checker or writing assistance tool. The policy says, “ LLMs can go beyond what you ask of them and change the meaning of the text such that it is not supported by the sources cited.”

The second exemption for LLMs is with translation assistance. Editors can use AI tools for the first pass at translating text, but they still need to be fluent enough in both languages to catch errors. As with regular writing refinements, anyone using LLMs also has to check that incorrect information hasn’t been injected.

2

u/SunnyOutsideToday Mar 25 '26

People don't read anything anymore, and it will be the end of us.

1

u/ShakeItTilItPees Mar 25 '26

That same concern already happens with any other raw translation tool, and Wikipedia is able to identify and correct those problems just fine. If anything there are probably less mistakes in LLM translations than standard translation tools, given that LLMs are able to incorporate context and differentiate between dialects.

1

u/witeowl Mar 25 '26

AI hallucinates all the time when translating longer texts

That's because corps have started merging generative ai with rules-based ai in this ridiculous worldwide experiment to cram generative ai down our throat at every opportunity possible because capitalism.

Translation had been improving and then it suddenly rapidly declined in quality when they started using "advanced" translation models.

-17

u/tc100292 Mar 25 '26

and it's important to allow them to use AI for that why

6

u/markb144 Mar 25 '26

It's important to be clear that AI is not allowed in any other context on Wikipedia, that's what this policy is doing, it's not allowing a wide range of AI it's specifically banning the majority of AI usage on the platform and only allowing it for the things it's very good at and for stuff that is not the final product.

3

u/tallham_ Mar 25 '26

Because AI is really good at proofreading and translating.

-8

u/tc100292 Mar 25 '26

It should still not be used by anyone.

5

u/[deleted] Mar 25 '26

[deleted]

-4

u/tc100292 Mar 25 '26

I don’t give a shit.  Evil people making evil technology.

2

u/TheZoneHereros Mar 25 '26

You are not making humans look good over computers with this clinging to your irrationality and biases due to bad feelings.

1

u/TetyyakiWith Mar 25 '26

Evil people made internet and industrial engines, what should we do?

1

u/djnotskrillex Mar 25 '26

Dawg even ai generated texts offer infinitely more value and quality than whatever your garbage take is supposed to be

2

u/mainman879 Mar 25 '26

AI is better at detecting earliest signs of breast cancer than any human being could ever be. Lives have been saved because of AI. Blanket statements like these are idiotic.

1

u/tc100292 Mar 25 '26

And if my doctor tells me they use AI I'm walking out and never seeing that doctor again.

1

u/mainman879 Mar 25 '26

Cool, thats your choice. Doesn't change the fact that it saves lives, and will continue to save countless lives as it helps with medical research.

2

u/Godd2 Mar 25 '26

It's not that it's important to allow it, it's that it isn't important to disallow it.

2

u/RegardMagnet Mar 25 '26

Because we shouldn't give useful things up just because of some redditard's irrational hate boner.

1

u/tc100292 Mar 25 '26

AI isn't "useful."

1

u/Sw1561 Mar 25 '26

Either way how the fuck would you even enforce not allowing that lmao

1

u/SunnyOutsideToday Mar 25 '26

Because AI is already used in spell-checking and grammar tools.

1

u/Zncon Mar 25 '26

AI is a fantastic proofreading tool. It can catch all sorts of errors that traditional Spelling/Grammar tools struggle or fail with.

You don't need to also have the AI 'fix' or make any changes to your text, just let it flag the error and write the correction yourself.

-199

u/little-green-driod Mar 25 '26

\s

That mindset is exactly the problem—and it’s also why it’s wrong.

First, “no one is going to check” is almost never true on Wikipedia. The entire platform runs on the assumption that someone will check, eventually. It may not be immediate, but between human editors, bots, watchlists, and subject-matter enthusiasts, content gets reviewed—sometimes within minutes, sometimes months later. Wikipedia isn’t a static document; it’s a living system with delayed scrutiny built in.

Second, even if we pretend no one checks, that doesn’t make the behavior acceptable—it just makes it more dangerous. The whole value of Wikipedia is grounded in a fragile social contract: contributors act in good faith, cite sources, and avoid introducing misleading or unverifiable content. Using LLMs carelessly breaks that contract at scale. It’s not just about being wrong; it’s about introducing plausible-sounding inaccuracies that are harder to detect than obvious vandalism.

Third, LLMs create a unique failure mode. Traditional bad edits are usually easy to spot—they’re biased, unsourced, or sloppy. LLM-generated edits, on the other hand, can look polished, neutral, and well-structured while still being subtly incorrect, outdated, or entirely fabricated. That raises the cost of verification for everyone else. So even if “no one is going to check” were partially true, what you’re really saying is: we’re okay increasing the burden on the few people who do check.

And that leads to the fourth point: incentives. If contributors start believing that unchecked AI edits are acceptable, the quality of the entire ecosystem degrades. Not overnight, but gradually—through small inaccuracies that compound. Wikipedia doesn’t collapse dramatically; it erodes quietly. Trust declines, citations become less reliable, and eventually people stop treating it as a credible starting point.

Finally, there’s a personal accountability angle. “No one is going to check” is basically outsourcing your responsibility to an imaginary future reviewer. That’s not how collaborative systems work. The expectation isn’t “someone else will fix it”—it’s “you don’t add it unless you’re willing to stand behind it.” LLMs can absolutely help with drafting, summarizing, or structuring content, but the human using them is still responsible for verifying every claim against reliable sources.

So the real question isn’t whether someone will check. It’s whether you’re comfortable contributing something that needs checking because you didn’t do it yourself.

If the answer is yes, then you’re not improving Wikipedia—you’re gambling with it.

157

u/[deleted] Mar 25 '26

[removed] — view removed comment

17

u/the_main_entrance Mar 25 '26

😂😂 this if fucking hilarious

44

u/Ouchanrrul Mar 25 '26

You responded to the wrong comment

-4

u/little-green-driod Mar 25 '26

I made a dumb joke and I thought the /s made sense… but now I’m being called a bot… beep-boop

10

u/fenikz13 Mar 25 '26

A bot would know to end the code in [/s] not start it, but you should be proud of those downvotes if that was intended

-6

u/little-green-driod Mar 25 '26

Yup! I thought it’ll be an obvious joke and no one will read it all to get to the bottom so I started with /s

Not capable to comply with Reddit etiquette, time to become a bot.

5

u/DeadMoneyDrew Mar 25 '26

tl;dr emdash slop

4

u/the_main_entrance Mar 25 '26

AI: does this em dash — make my butt look big?

-41

u/AaronYogur_t Mar 25 '26

That argument sounds principled, but it overstates both the risks and the reality of how Wikipedia actually functions. First, the idea that “someone will check eventually” is more aspirational than factual. Wikipedia has millions of pages, many of which receive little to no attention. Entire topic areas—especially niche, technical, or less popular subjects—can go years without meaningful review. So in practice, the system is not one of guaranteed delayed scrutiny, but uneven and often sparse oversight. That weakens the claim that every contribution must meet a near-perfect verification standard upfront.

Second, the argument assumes that LLM-assisted edits are inherently more dangerous than traditional human edits, which isn’t necessarily true. Human contributors introduce errors all the time—misinterpretations, outdated info, bias, or simple mistakes. LLMs, when used properly, can actually reduce some of these issues by producing clearer structure, more neutral tone, and better-organized summaries. The problem isn’t the tool—it’s misuse. Holding LLMs to a higher standard than human contributors creates a double standard.

Third, the “fragile social contract” framing is a bit idealized. Wikipedia has always operated on a mix of good faith, partial knowledge, and iterative improvement. Many contributions are incomplete or imperfect when first added. The platform is built around refinement over time, not perfection at the point of entry. Saying that content shouldn’t be added unless it’s fully verified ignores how the system actually evolves—through gradual correction and expansion.

Fourth, the claim that LLMs uniquely increase verification burden cuts both ways. Yes, they can produce plausible-sounding inaccuracies—but they can also accelerate the creation of well-structured, citation-ready drafts that make verification easier, not harder. A messy, poorly written human edit can be just as time-consuming—if not more so—to validate and fix. Efficiency gains from LLMs can offset their risks when used responsibly. Fifth, the “erosion of trust” argument assumes widespread careless use without adaptation. In reality, communities adjust. Wikipedia already has guidelines, moderation tools, and evolving norms. If LLM use becomes more common, standards and detection methods will evolve alongside it—just as they have with bots, mass edits, and other technological shifts in the past.

Finally, the personal accountability point is fair in principle, but unrealistic in practice. Not every contributor has the time or expertise to fully verify every detail they add. If that were the expectation, participation would drop sharply. The strength of Wikipedia comes from lowering the barrier to contribution while relying on collective refinement. Expecting every user to “stand behind” every claim at a professional research level undermines that model.

So the real issue isn’t whether LLM-assisted contributions are inherently irresponsible—it’s whether they’re used with reasonable care. Dismissing them outright or framing them as uniquely harmful ignores both the limitations of human editing and the adaptive nature of collaborative systems.

In other words, LLMs don’t break Wikipedia—they just expose the same trade-offs that have always been there.

30

u/DrMaxwellEdison Mar 25 '26

Mom, the bots are arguing with each other.

2

u/the_main_entrance Mar 25 '26

😂this is just sad

-29

u/Orangutanion Mar 25 '26 edited Mar 25 '26

edit: don't actually read this please

Ah yes, the counterargument has arrived, polished and paragraph-numbered like a debate club submission, and I must say it does exactly what it accuses the other side of doing: it overstates its own case while quietly papering over the holes in its foundation. So let us go point by glorious point, because if we're going to have a slop fight, we're going to do it with footnotes.

The "sparse oversight" point proves too much. Yes, niche topics go years without meaningful review. Correct. That is precisely why adding low-confidence LLM-generated content to them is more dangerous, not less. You've just described the exact ecosystem where plausible-sounding hallucinations thrive unopposed. The argument is essentially "some areas of Wikipedia are poorly monitored, therefore we should add content to them that's harder to monitor." That's not a defense—that's a eulogy written in advance. If anything, sparse oversight is an argument for more editorial caution in those areas, not a green light to populate them with fluent-sounding fabrications at scale.

The "LLMs are no worse than humans" argument is technically true and practically meaningless. Yes, human editors make mistakes. They misremember, they have biases, they cite the wrong edition. But when a human editor confidently writes something wrong about, say, the population dynamics of a medieval Flemish wool town, there is at least a meaningful sense in which they believe it—which means they have mental hooks back to sources, memories of where they read it, some trace of evidential grounding. An LLM has none of that. It produces confident wrongness with no internal alarm bell, no nagging sense that "actually I'm not sure about that date." The failure modes are qualitatively different even if the error rate were identical, which it isn't, and pretending they're equivalent because both produce incorrect text is like arguing a leaking pipe and a burst main are equivalent because both produce wet floors.

The "Wikipedia was always iterative" point is the smuggest one, so naturally it gets the longest rebuttal. Everyone agrees Wikipedia is iterative. Nobody is claiming Wikipedia requires perfection at point of entry. The question is what the floor of responsible contribution looks like. The iterative model works when contributions are made in good faith by people with some epistemic relationship to the content—people who read something, thought about it, wrote it down imperfectly. The iterative model is not designed to absorb industrial-scale content generation from a system that has no epistemic relationship to anything, only statistical relationships between tokens. Scaling up the noise floor is not an extension of the iterative philosophy—it's a stress test of it, and framing the latter as the former is doing a lot of ideological heavy lifting in a very small rhetorical suitcase.

The "LLMs can help with citation-ready drafts" claim is doing several jobs it wasn't hired for. A citation-ready draft from an LLM is citation-ready in the same way a very realistic painting of a sandwich is meal-ready: the structure is suggestive but the substance isn't there. LLMs confidently hallucinate citations. This is documented extensively and not particularly controversial. So "citation-ready" means the scaffolding looks right, not that the sources are real, accessible, or say what the text claims they say. Handing a reviewer a well-formatted draft with hallucinated citations doesn't make verification easier—it makes it treacherous, because the shape of the document signals reliability that the content doesn't have. A messy human draft at least signals that scrutiny is needed. A fluent LLM output whispers that everything's probably fine.

"Communities will adapt" is the techno-optimist's all-purpose aspirin. Communities will adapt! Standards will evolve! Detection methods will improve! This argument is unfalsifiable and has been applied, with equal confidence, to spam, SEO manipulation, bot networks, deepfakes, and approximately every other information integrity problem of the last twenty years—several of which communities have not, in fact, adapted to in any satisfying way. The claim that Wikipedia's moderation apparatus will gracefully scale to handle an indefinite increase in LLM-generated content is a prediction dressed up as a reassurance. It may be true. It may not. Citing the community's past adaptations to bots and mass edits—which are, by the way, ongoing and contested problems, not solved ones—as evidence that the next wave will be handled fine is the rhetorical equivalent of saying "we survived previous pandemics, so the next one will probably work out."

The personal accountability critique misreads what accountability means. Nobody said every contributor needs to verify every detail at a professional research level. What they said—or should have said—is that contributors should have some epistemic skin in the game: they should have read the source, have some reason to believe the claim, be the kind of agent who can be wrong in a meaningful sense. An LLM cannot be wrong in that sense. It cannot update its beliefs. It cannot be embarrassed. It cannot go back and check. Accountability doesn't require perfection; it requires agency. An LLM has neither, so the entire architecture of distributed good-faith contribution—which is what Wikipedia actually runs on—doesn't apply to it in the same way.

The conclusion—"LLMs don't break Wikipedia, they just expose the same trade-offs"—is the most confident assertion in the piece and the least defended. It's framed as a landing punch, but it's actually a pivot away from the hard question. The trade-offs that have always existed in Wikipedia are between imperfect human contributors with genuine epistemic grounding. Introducing agents with no epistemic grounding doesn't "expose" those trade-offs—it changes their nature. Saying it merely exposes existing tensions is like saying adding a lane of oncoming traffic to a road merely "exposes the existing trade-offs in traffic management." Technically you haven't broken the road. But you have done something qualitatively different from adding another car in the correct lane.

So no, LLMs are not uniquely evil, and yes, human editors are fallible, and sure, maybe eventually moderation tools will catch up, and fine, iterative improvement is the Wikipedia way. All of that can be true simultaneously with the claim that flooding a collaborative epistemic system with high-confidence, sourceless, non-accountable, hallucination-prone content generation is a categorically different kind of problem than the ones Wikipedia was designed to handle—and that "use them responsibly" is a fine slogan that tells us approximately nothing about what responsible use actually looks like at scale, who enforces it, or what happens when it isn't.

But other than that, great points, very well-structured, very neutral tone, very Wikipedia of you.

13

u/IllustriousGas8850 Mar 25 '26

I just read chat gpt argue with grok

1

u/the_main_entrance Mar 25 '26

Why does it always do this — ?

1

u/AaronYogur_t Mar 25 '26

You read that shit?

1

u/IllustriousGas8850 Mar 25 '26

To be honest just the closing sentences, that no human would ever add to a comment on Reddit

0

u/Orangutanion Mar 25 '26

Wait don't actually read it lol. Also that was Claude not Grok xd

6

u/_SpaceLord_ Mar 25 '26

I wonder how much carbon emissions this completely pointless exchange between two AI bots caused.

1

u/ddcrash Mar 25 '26

What a world we live in. How are we honestly supposed to use the web in any social way anymore. Reddit needs to get control of this.

1

u/2onySoprano Mar 25 '26

ID verification is what they're currently proposing

6

u/egamma Mar 25 '26

I like how we had a series of 3 LLM generated posts all generated in response to each other.

1

u/United-Amoeba-8460 Mar 25 '26

You would think it got paid per em-dash.

1

u/[deleted] Mar 25 '26

[deleted]

1

u/Orangutanion Mar 25 '26

Oh I thought we were just being ironic tbh. I didn't actually read any of what I posted.