I think they have to; while at first glance AI generated content is impressive, it becomes noisy and sameish at larger scale or the more you read it. I'm of the opinion that AI is here to stay and a valuable tool for many use cases, but writing authoritative content ain't it. Wikipedia is fighting it (and other influences from before AI, like unsubstantiated claims and whatnot), I hope the scientific community and journalism steps up too.
Wikipedia is also a training source and shouldn’t also be a model output for content. Eventually it will be an oroborus, but it seems prudent to avoid that for as long as possible.
A little over a year ago, the MIT Technology Review ran a piece about how outputting AI content to non-English Wikipedia is rapidly corrupting the primary training data for uncommon languages because of exactly this process: https://www.technologyreview.com/2025/09/25/1124005/ai-wikip...
AI is great at making poor writing good. I've had good luck having AI turn my rough draft into something readable. (just check my comment history to see how bad my rough drafts normally are). AI is also reasonably good at research and fact checking. But in all cases you need to think before you accept anything AI says. AI generated content all too often hasn't been checked, some is good but some is awful and an expert needs to decide which is which.
That is AI is a tool. I've driven screws with a hammer - it worked in a pinch, but it was not good. People have also used hammers to kill others.
That's fair, ring shanks are a thing, but I was thinking more along the lines of a wood screw with deep threads. That just sounds like looking for pain. I'd expect it to chew things up pretty badly, too, though I have so far lacked the commitment to try pounding a screw with a hammer ;).
100%. Looks like they're using pangram (hope they're getting that for free...) which also flags stuff like Grammarly. That one's an interesting gray zone to me that I've not thought off before. LLMs whales doing the heavy lifting is one thing, but small edit tools like grammarly that "improve" your phrasing are likely a massive algea like contributor to what is out there too.
I attempted to fix some AI-generated content that I found on wikipedia recently - it had broken formatting, confusing + made-up text, and links on the wrong keywords; just generally very low quality edits.
I made my edits and they were immediately reverted by wikipedia's own AI bot. I gave up.
Also happy to help - Cluebot is mostly helpful but it tends to be overzealous on reverting with new accounts or temp accounts and especially with large-scale changes made by those types of accounts.
That would be good, as I imagine that wikipedia is in survival mode these days, as less and less people visit their site directly
Even so more people indirectly benefit from its content
Wikipedia can gain a lot by doing a cleanup using AI instead. There’s a lot of incorrect information in Wikipedia that you can easily detect using AI with a prompt like “find something wrong in a few randomly selected Wikipedia articles”. Usually it does find something.
If it’s that easy for me to correct it, it should be automated.
> It was around December 2023. A few other editors and I were chatting on Wikipedia’s Discord server, and we had all seen very strange articles with the same odd characteristics.
I was afraid of that. I grabbed a 2024-04-20 copy as a backup, in case it turned to slop, but I suspected it might be tainted already.
About a decade ago, I read the history of AIDS on Wikipedia. It was a very informative (and satisfying) 20 minute read.
Now it's pages and pages and pages of text: probably factual, but not a satisfying read. It feels like it's for a different audience, and it's not satisfying to read.
Is it AI generated? I don't know for sure, but it feels like either someone (or something)'s missing the point of who Wikipedia's audience is; or that someone is following an agenda, (or that there's an edit war going on between dueling agendas and the facts are added to drown out the "AIDS is a consequence of bad morals" agenda.)
Wikipedia is an encyclopedia. Being as detailed as possible is its goal. Simple English Wikipedia exists for shorter easier to read versions of articles. Generally though, turning a complex topic into a fun easy read is the goal of good scientific journalism, which is also important but a separate effort from an encyclopedia.
No, that is not the point of an encyclopedia. The point is to condense an entry as much as possible while being thorough enough to cover most relevant information.
In some ways that was the limitation of physical paper and weight of the set.
A digital encyclopedia has different constraints, and the hard part was always trying to figure out what to leave out. Also in encyclopedias, you get what you get from the one or two people that worked on that particular article. If they had biases it would shape what everyone in the world saw. In an online article it can become a battle on what people want to see.
I just read both and I'm not sure I understand what your point is here. I don't have much to say about the diabetes page other than there is some interesting (as well as unfortunate) information. The HIV page certainly doesn't seem as if it gives off the "not a bad disease" feeling. It lists an untreated life expectancy as 11 years, whereas the diabetes page lists an expected life expectancy of being reduced by 10 years. That certainly makes HIV more deadly. It's also made obvious that it's transmissible from normal sexual behavior, as well as being so for some time before one would even experience symptoms. It's definitely not a bed time story. If anything, I'd say the diabetes page is less scary in its overall presentation than it should be.
Obviously this is subjective. I'm not saying you're wrong, just genuinely curious at what made you think this. I'm not making assumptions, but perhaps you have (unfortunately) more personal and upsetting experiences with HIV/AIDS than with diabetes? I know that when I used to bartend at a neighborhood gay bar frequented by gen Xers it was very difficult to see and hear people lose or talk about losing their partners to something that alienated them even more than they already are/were.
It is interesting to think about how to convey information about these things though. I think it's probably a good thing to make HIV/AIDS not sound so terrifying. For pretty much every adult alive today, I'd assume, their idea of HIV/AIDS was something like being told it's a "gay disease" or that you can't touch people with it (thank you for your service, princess Diana) or some sort of anti-African racist nonsense. So conveying accurate information without bigotry, homophobia, or xenophobia is probably a good thing overall.
Also curious what sort of possible conspiracy would benefit from Wikipedia readers from not being more afraid of HIV/AIDS.
> just genuinely curious at what made you think this.
It feels like the first 2 paragraphs are doing a lot of work to downplay the seriousness of the illness:
- highlighting the "undetectable = untransmittable" PR campaign.
- reassurance that you can live a normal life with HIV, "die with virus, not of virus"
- reassurance that there's zero transmission risk with long term treatment
- reassurance that HIV is a "manageable chronic health condition"
After the first 2 paragraphs of the HIV article, I'm left thinking "okay, this isn't as bad as I thought" -- but maybe that's okay since historically there has been a lot of misinformation around HIV.
> what sort of possible conspiracy would benefit from Wikipedia readers from not being more afraid of HIV/AIDS.
De-stigmatization of HIV is the agenda. (An agenda I support)
I think I see your point. As you said, it's factual but it could be read as having an agenda. While we both support the agenda, it's not ideal to have one in the first place for a resource which should be as non-biased as possible, I suppose.
Always fun to think about different viewpoints. The same factual information could be represented (and is, as far as I know) in another way to denounce homosexuality and premarital sex, for example. Not making a statement about any particular belief system.
Thanks for the engaging think on a difficult night for me. I appreciate it. :)
I do think it's reasonable-- although certainly not the only valid approach-- to be aware of historical misinformation and emphasize certain facts more prominently to counteract it. It could skew the emphasis the other way in the long term, but the more immediate benefits of combating misinfo actively seem justifiable.
Hmm, its showing as roughly 9.4 kwords which is a little higher than ideal. I may raise the suggestion to spin a section out. Maybe § Emergence can have its own article and be only summarised in the parent? I see the New York subsection is also quite long.
Same feeling here - not sure if it’s AI, or zealous wikipedians + incentives that make addition easy but editing and pruning means stepping on many other writers turf, but I used to enjoy reading articles, while now many are more useful as “information fodder” for LLM to summarize and interpret.
On reflex, I searched for "reagan". 0 results as of the morning of October 27, 2026.
I was there in the 1980s when the AIDS outbreak started getting mainstream news coverage. I watched the Ryan White movie on TV, when it was the biggest topic at school for months afterwards:
I can tell you what really happened. HIV/AIDS scared the bejesus out of the political establishment of the time. Who then stoked that fear to push their socially conservative agenda onto everyone in an attempt to return the US to what they viewed as a morally just culture (basically the 1950s), much like MAGA today.
And just like when Donald Trump refused to wear a mask to set an example in protecting the elderly and other vulnerable groups from infection by COVID-19, Ronald Reagan refused to devote real resources to slowing the spread of of AIDS and finding a cure. Because AIDS furthered the GOP's efforts to expand the War on Drugs, push abstinence-only sex education, demonize same-sex relationships and criticize secular culture in general.
In a very real sense, Ronald Reagan and his administration let AIDS grow from being a manageable disease to becoming an epidemic that killed millions of people. His misplaced priorities set back research and treatment options by decades.
Omitting Reagan's name from the history of AIDS is like casually leaving Benedict Arnold out of the history of the American Revolutionary War.
The domino effect of his abdication of duty has touched everything from US police interventions in developing nations that it's exploited to its $40 trillion national debt. It's literally fogged the lens through which we see the world.
Its easy to forget all of that now that once-daily HIV treatment pills and bi-monthly preventative injections exist, and we're finally seeing cures on the horizon.
Revisionist history now dominates our political discourse. I write this because the "AIDS is a consequence of bad morals" agenda is not something to be lightly swept under the rug. It's literally a pillar upon which the alternate timeline we're on now stands.
I mean this is good, because AI generated content is explicitly against the guidelines, however I can't help but think there is some utility to be had with AI and online encyclopedias, and we might be missing out on that.
Of course I'd love for this experiment to be done outside of the main site, and only integrated when it's mature, stable, and proven to be actually useful, but other than that implementation concern, I feel this is something that needs to be explored.
If we leave out environmental (energy, datacenters, coolant) and political arguments (copyright stealing, private data harvesting etc.) even if we agree that those are "bad".
What then, is the problem of AI-Generated Content in Wikipedia?
> Fake or misleading citations have become a major worry.
Why is this not a standalone problem? Humans can fake and mislead in citations too, in fact, this is a major problem and has been so, for literally centuries in science.
> Being a place that was, in theory, free from AI slop has become part of Wikipedia’s identity.
Isn't this a separate issue in itself too? One of "quality". If AI generates poor quality content, than I would think the poor quality is the problem, not the producer of it.
The article mentions several times how hard it is to detect AI content. If it is that hard, then obviously AI is doing a good job and producing content that matches that of humans. Why then insist on one type of producer?
Poor quality is the problem and since the bandwidth of editors doesn't magically grow with the amount of input, rejecting AI content is a very effective way to keep average quality up.
>Isn't this a separate issue in itself too? One of "quality". If AI generates poor quality content, than I would think the poor quality is the problem, not the producer of it.
Yes, but who will review the mountains of slop to determine whether it is of acceptable quality? The main problem AI introduces is high volume at low quality, often overwhelming the human resource bottlenecks these systems have in place.
It isn't possible, in the same way that keeping copyrighted material out of Wikipedia isn't possible: there's probably going to be a backlog spanning years or decades, but some of those investigations will eventually complete and result in an action being decided on.
There will be a point in the future, possibly near future, when AI will be capable of reliably producing encyclopedic content, and we'll have tools to verify that the content produced passes reasonable standards.
Today is not the day. Especially not regarding the verification.
That's really not how probabilistic systems work though. They're great at getting 80% of the way to the goal but the last 20% is always excruciatingly difficult. I really don't intend that a knock because LLMs are useful, but they also aren't magic boxes where anything is possible.
This is the problem that a lot of user-content based sites, and open software projects, are experiencing. The tools make prodiving 80% correct submissions so easy that many people are doing that and thinking that it is fine not to bother verifying for correctness (or not even knowing how to verify correctness). This means those projects are being inundated by submissions that are 20% tosh or worse.
Another problem with user content sites, these numbers are completely pulled from the ass and are a meme that just gets repeated ad nauseam. They mean nothing, but there will be people that take it seriously.
Is 80/20 ever generally correct? Why is it favored over the 90/10 meme? Why would it apply to this? Why wouldn’t the numbers be vastly different for different domains of content generation? Etc.
If you pay attention, so much user content is just repetition of something they read on the same fucking website and uncritically checked into their brain.
Current HN top post is Roblox downloaded 145GB models from us (including adult content) without asking. I fully expect to start seeing comments to the tune of “Roblox is stealing porno to train AI for children” within the day in any discussion Roblox comes up in.
Why would these folk’s contribution to any other user content site be any more thoughtful?
It’s just a rough way to say “mostly this with a decent bit of that” because 20% seems like a medium-small percent that could or could not matter depending on the context
That’s all anyone means when they say 80/20
To your second point, the 80% could be lots of basic things and the 20% could be the important facts, so it’s not always meant as a dismissal that the 20 doesn’t matter
Even putting aside accuracy, if the plan is for the tools that verify the written content to be in any shape or form outside of the human loop, then this feels like it glosses over the issues of both passive bias in data & active bias (e.g data filtering etc. ) when training such models that you'd be poisoning this information sources with.
Even subtle bias can manifest in significant ways. Given that the predominant market leaders in producing such models are currently : A country that's attempting to squeeze the word "america" in any geographic formation possible + rewriting history to put itself first, and a country that has perfected censorship en-mass and already actively doctors its own history.
I'm not convinced giving LLMs carte blanche to write authoritative sources on topics that - often are ideologically sensitive/controversial isn't just needlessly reckless and short-sighted. It's not a far reach to imagine such models reflecting the current views of administrations in these countries and becoming reluctant to mention certain colonial ambitions, environmental damage, political corruption, etc. where it might be relevant to authoritative content.
Wikipedia already struggles with issues in idealogical bias from authors - human validation (somewhat)helps mitigate that. You could argue that human validation is still prone to same bias - but you can always draw on a more diverse pool of editors with little ideological overlap. With LLM validation you're pretty much at the mercy of a pretty incestuous pool of data & a handful of self-serving corporates & governments.
I don't think anyone's arguing against whether or not it's possible, the question is whether it's valuable, correct, and A Good Thing.
I have access to a number of LLMs and can order it to build me a wiki site with all knowledge of the world, just like everyone else with the same access. What would make mine any more valuable or better than another?
Wikipedia is a tertiary source. Its editors are parroting secondary sources. (No disrespect intended.) There's no reason why LLMs couldn't be good at that.
I would rather be worried about the quality of all the primary and secondary sources going forward.
There is a reason why LLMs can not be good at this: They don't know what they are quoting or citing. A different kind of model with factoid provenance could do it?
What do you mean by this? I have passed very large documents into LLMs and they are able to accurately extract quotes and identify their location in the source documents. I don’t see any reason to think that they couldn’t accurately quote from and cite existing literature.
LLMs cook up new sentences based on probability, based on everything in their training and their context. There's just nothing in their model that traces provenance of facts, they physically don't store that information. Once they have written a sentence, they can't tell you from which work they got this information.
There are tools where they try to retroactively add references, the LLM interfaces try to do this, but it's usually inaccurate.
I think of the way a scientific article works. "The sky is blue (Pearson, 1992)." The writer is fully aware what the factual statement is and which publication supports it (not just that, but which kind of publication - primary, secondary source, peer reviewed?). An LLM can try to imitate this, but the actual information to support this does not exist in its training.
They can. I had one doing original OCR of a scanned piece yesterday. It found relevant page numbers and understood the context. It read the whole book to find the relevant cites. Even went though the genealogy table and found ground breaking references no one noticed before. Total cost under 5 dollars and time was less than 20 mins.
That's not how academic literature works. The structure is like this: Statement (Citation). The citation is not an affirmation of truth but a content declaration; this statement is supported by this publication. The receipts are there, so that you can trace the argumentation and make your own conclusions if necessary.
'Knowledge' formed this way is a living, evolving graph, and sometimes links are broken (findings are reevaluated or disproven); having the content declaration so clearly in the open makes it easier to deal with this evolving landscape.
the thing is: if AI-Generated Content (if correct, obviously) is just some topics learnt from humans, what's the difference between something correct written by a machine and something correct written by a human?
Why to multiply instead of going to the same place for knowledge? It is almost like you want to make a different Wikipedia for conservatives and liberals because one cannot tolerate a tone or style of the other. Probably we should dedicate dozens of sites for the same topic depending on the writing styles of the humans too. There are a few out there.
In worst case we might have an 'AI language' (or languages) instead, so the sensitive souls could find a safe heaven from it elsewhere, choosing something else. Perhaps one along the idea of 'simple English', have it 'AI English'. Or something else satisfies those looking for a specific way of delivery they can handle exclusively.
I think knowledge is the important here, not the tone.
Honestly Wikipedia is just fine being written by humans. It's not the lack of copy that is holding Wikipedia back.
However,
> Perhaps one along the idea of 'simple English', have it 'AI English'.
That's actually an interesting idea. It could work, but I don't personally think it would be better than the English Wikipedia.
Also, are you expecting that humans would still be on the loop by deciding what gets added to AI English Wikipedia, or you think that LLMs should get to decide that too?
> It is almost like you want to make a different Wikipedia for conservatives and liberals because one cannot tolerate a tone or style of the other.
Many conservative worldview elements such as climate change denialism, creationism or anti LGBT view (e.g. LGBT being "unnatural") are not backed by reality because they run counter to scientifical consensus. And that's before we go into the outlandish bullshit conspiracy crap like "ZOG/zionist occupied government", "flat earth", "9/11 was faked", "the moon landing was faked" and the likes that gains more and more momentum among "conservative" people.
You cannot make a Wikipedia appealing to conservatives.
Not sure what question you're supposing he asked which was in the article. OP's point seemed to be that correct words written by a human could be effectively the same as correct words written by a machine, supposing the machine managed to be correct by learning from human content. The 'obvious' part is this wouldn't be true if the AI content was incorrect. At least that is what I got.
Ironically enough I just started an "Encylopedia of AI" project, and I've decided to generate all of the content with DeepSeek, with me being an editor/reviewer. I'm not really doing it for anyone except myself but I'm quite enjoying it so far. https://enkuklios.com/
Almost all of these websites or platforms are doing these massive cleanup to remove ai content from them. Well appreciated.
I think they have to; while at first glance AI generated content is impressive, it becomes noisy and sameish at larger scale or the more you read it. I'm of the opinion that AI is here to stay and a valuable tool for many use cases, but writing authoritative content ain't it. Wikipedia is fighting it (and other influences from before AI, like unsubstantiated claims and whatnot), I hope the scientific community and journalism steps up too.
Wikipedia is also a training source and shouldn’t also be a model output for content. Eventually it will be an oroborus, but it seems prudent to avoid that for as long as possible.
A little over a year ago, the MIT Technology Review ran a piece about how outputting AI content to non-English Wikipedia is rapidly corrupting the primary training data for uncommon languages because of exactly this process: https://www.technologyreview.com/2025/09/25/1124005/ai-wikip...
It's funny to think that pre-LLM archives are the new low-background steel.
The models are already trained on model output on purpose
Maybe so, but in a controlled and deliberate fashion.
Not just random output of who knows what model, from who knows what prompt.
Unsubstantiated claims is one thing.
If it doesn’t act to fix the politically Left biased perennial sources list, it will continue to be a propaganda machine.
...accurate username? I'm genuinely not sure if this comment is satire or not
AI is great at making poor writing good. I've had good luck having AI turn my rough draft into something readable. (just check my comment history to see how bad my rough drafts normally are). AI is also reasonably good at research and fact checking. But in all cases you need to think before you accept anything AI says. AI generated content all too often hasn't been checked, some is good but some is awful and an expert needs to decide which is which.
That is AI is a tool. I've driven screws with a hammer - it worked in a pinch, but it was not good. People have also used hammers to kill others.
It makes poor writing readable, not good.
> I've driven screws with a hammer
That takes a lot of commitment, you really have to want that screw in pretty badly! And when you're done it ends up just being a worse nail.
There are nails that have threads on them that are made especially for this purpose.
That's fair, ring shanks are a thing, but I was thinking more along the lines of a wood screw with deep threads. That just sounds like looking for pain. I'd expect it to chew things up pretty badly, too, though I have so far lacked the commitment to try pounding a screw with a hammer ;).
It seems good. And that's a major problem, one of the signals for quality is not useless.
100%. Looks like they're using pangram (hope they're getting that for free...) which also flags stuff like Grammarly. That one's an interesting gray zone to me that I've not thought off before. LLMs whales doing the heavy lifting is one thing, but small edit tools like grammarly that "improve" your phrasing are likely a massive algea like contributor to what is out there too.
Why for free? Wikimedia is very well funded, and I'm sure that Pangram could use a leg up...
I attempted to fix some AI-generated content that I found on wikipedia recently - it had broken formatting, confusing + made-up text, and links on the wrong keywords; just generally very low quality edits.
I made my edits and they were immediately reverted by wikipedia's own AI bot. I gave up.
Could you link me the article? Cluebot is very good, but it does make mistakes sometimes.
Also happy to help - Cluebot is mostly helpful but it tends to be overzealous on reverting with new accounts or temp accounts and especially with large-scale changes made by those types of accounts.
Which page? Let me see if I can help.
I wonder if the AI companies would even pay for this, because it increases the quality of the training data.
That would be good, as I imagine that wikipedia is in survival mode these days, as less and less people visit their site directly Even so more people indirectly benefit from its content
Related:
"Low-background Steel: content without AI contamination (jgc.org)" 10.jun.2025 https://news.ycombinator.com/item?id=44239481 269 comments
"Wikipedia: Database Download (wikipedia.org)" 27.apr.2025 https://news.ycombinator.com/item?id=43811732 99 comments
"Low Background Steel (lowbackgroundsteel.ai)" 27.apr.2025 https://news.ycombinator.com/item?id=43814531 2 comments
Wikipedia can gain a lot by doing a cleanup using AI instead. There’s a lot of incorrect information in Wikipedia that you can easily detect using AI with a prompt like “find something wrong in a few randomly selected Wikipedia articles”. Usually it does find something.
If it’s that easy for me to correct it, it should be automated.
> It was around December 2023. A few other editors and I were chatting on Wikipedia’s Discord server, and we had all seen very strange articles with the same odd characteristics.
I was afraid of that. I grabbed a 2024-04-20 copy as a backup, in case it turned to slop, but I suspected it might be tainted already.
Early 2024 is probably still 99.99% handcrafted text.
Still, 2023-10 is probably the last pure https://en.wikipedia.org/wiki/Low-background_steel
Archive.org should have some old dumps, for example https://archive.org/details/enwiki-20220501 is supposed to be May 2022 (All the later ones look like incrementals).
About a decade ago, I read the history of AIDS on Wikipedia. It was a very informative (and satisfying) 20 minute read.
Now it's pages and pages and pages of text: probably factual, but not a satisfying read. It feels like it's for a different audience, and it's not satisfying to read.
Is it AI generated? I don't know for sure, but it feels like either someone (or something)'s missing the point of who Wikipedia's audience is; or that someone is following an agenda, (or that there's an edit war going on between dueling agendas and the facts are added to drown out the "AIDS is a consequence of bad morals" agenda.)
Wikipedia is an encyclopedia. Being as detailed as possible is its goal. Simple English Wikipedia exists for shorter easier to read versions of articles. Generally though, turning a complex topic into a fun easy read is the goal of good scientific journalism, which is also important but a separate effort from an encyclopedia.
No, that is not the point of an encyclopedia. The point is to condense an entry as much as possible while being thorough enough to cover most relevant information.
"most relevant info" is highly subjective though. One mans "most relevant info" is another mans "unsatisfying read".
In some ways that was the limitation of physical paper and weight of the set.
A digital encyclopedia has different constraints, and the hard part was always trying to figure out what to leave out. Also in encyclopedias, you get what you get from the one or two people that worked on that particular article. If they had biases it would shape what everyone in the world saw. In an online article it can become a battle on what people want to see.
It is a difficult problem.
Encyclopedias are for summaries, not maximal detail. For that, you look at the source material.
I'm normally against conspiracy theories and BS like this, but...
There's a pretty stark difference between the first few paragraphs of the HIV/AIDS page and the first few paragraphs of the Type 2 Diabetes page.
Both are "factual", but when I read the HIV/AIDS page, I feel like someone is trying to convince me "HIV is not a bad disease".
I just read both and I'm not sure I understand what your point is here. I don't have much to say about the diabetes page other than there is some interesting (as well as unfortunate) information. The HIV page certainly doesn't seem as if it gives off the "not a bad disease" feeling. It lists an untreated life expectancy as 11 years, whereas the diabetes page lists an expected life expectancy of being reduced by 10 years. That certainly makes HIV more deadly. It's also made obvious that it's transmissible from normal sexual behavior, as well as being so for some time before one would even experience symptoms. It's definitely not a bed time story. If anything, I'd say the diabetes page is less scary in its overall presentation than it should be.
Obviously this is subjective. I'm not saying you're wrong, just genuinely curious at what made you think this. I'm not making assumptions, but perhaps you have (unfortunately) more personal and upsetting experiences with HIV/AIDS than with diabetes? I know that when I used to bartend at a neighborhood gay bar frequented by gen Xers it was very difficult to see and hear people lose or talk about losing their partners to something that alienated them even more than they already are/were.
It is interesting to think about how to convey information about these things though. I think it's probably a good thing to make HIV/AIDS not sound so terrifying. For pretty much every adult alive today, I'd assume, their idea of HIV/AIDS was something like being told it's a "gay disease" or that you can't touch people with it (thank you for your service, princess Diana) or some sort of anti-African racist nonsense. So conveying accurate information without bigotry, homophobia, or xenophobia is probably a good thing overall.
Also curious what sort of possible conspiracy would benefit from Wikipedia readers from not being more afraid of HIV/AIDS.
> just genuinely curious at what made you think this.
It feels like the first 2 paragraphs are doing a lot of work to downplay the seriousness of the illness:
- highlighting the "undetectable = untransmittable" PR campaign.
- reassurance that you can live a normal life with HIV, "die with virus, not of virus"
- reassurance that there's zero transmission risk with long term treatment
- reassurance that HIV is a "manageable chronic health condition"
After the first 2 paragraphs of the HIV article, I'm left thinking "okay, this isn't as bad as I thought" -- but maybe that's okay since historically there has been a lot of misinformation around HIV.
> what sort of possible conspiracy would benefit from Wikipedia readers from not being more afraid of HIV/AIDS.
De-stigmatization of HIV is the agenda. (An agenda I support)
I think I see your point. As you said, it's factual but it could be read as having an agenda. While we both support the agenda, it's not ideal to have one in the first place for a resource which should be as non-biased as possible, I suppose.
Always fun to think about different viewpoints. The same factual information could be represented (and is, as far as I know) in another way to denounce homosexuality and premarital sex, for example. Not making a statement about any particular belief system.
Thanks for the engaging think on a difficult night for me. I appreciate it. :)
I do think it's reasonable-- although certainly not the only valid approach-- to be aware of historical misinformation and emphasize certain facts more prominently to counteract it. It could skew the emphasis the other way in the long term, but the more immediate benefits of combating misinfo actively seem justifiable.
Hope your night works out well in the end.
Hmm, its showing as roughly 9.4 kwords which is a little higher than ideal. I may raise the suggestion to spin a section out. Maybe § Emergence can have its own article and be only summarised in the parent? I see the New York subsection is also quite long.
I don't think it has anything to do with AI. Wikipedia has been like that for at least a decade for me.
Same feeling here - not sure if it’s AI, or zealous wikipedians + incentives that make addition easy but editing and pruning means stepping on many other writers turf, but I used to enjoy reading articles, while now many are more useful as “information fodder” for LLM to summarize and interpret.
Just so we're on the same page, this is the one I just skimmed:
https://en.wikipedia.org/wiki/History_of_HIV/AIDS
On reflex, I searched for "reagan". 0 results as of the morning of October 27, 2026.
I was there in the 1980s when the AIDS outbreak started getting mainstream news coverage. I watched the Ryan White movie on TV, when it was the biggest topic at school for months afterwards:
https://en.wikipedia.org/wiki/Ryan_White
I can tell you what really happened. HIV/AIDS scared the bejesus out of the political establishment of the time. Who then stoked that fear to push their socially conservative agenda onto everyone in an attempt to return the US to what they viewed as a morally just culture (basically the 1950s), much like MAGA today.
And just like when Donald Trump refused to wear a mask to set an example in protecting the elderly and other vulnerable groups from infection by COVID-19, Ronald Reagan refused to devote real resources to slowing the spread of of AIDS and finding a cure. Because AIDS furthered the GOP's efforts to expand the War on Drugs, push abstinence-only sex education, demonize same-sex relationships and criticize secular culture in general.
In a very real sense, Ronald Reagan and his administration let AIDS grow from being a manageable disease to becoming an epidemic that killed millions of people. His misplaced priorities set back research and treatment options by decades.
Omitting Reagan's name from the history of AIDS is like casually leaving Benedict Arnold out of the history of the American Revolutionary War.
The domino effect of his abdication of duty has touched everything from US police interventions in developing nations that it's exploited to its $40 trillion national debt. It's literally fogged the lens through which we see the world.
Its easy to forget all of that now that once-daily HIV treatment pills and bi-monthly preventative injections exist, and we're finally seeing cures on the horizon.
Revisionist history now dominates our political discourse. I write this because the "AIDS is a consequence of bad morals" agenda is not something to be lightly swept under the rug. It's literally a pillar upon which the alternate timeline we're on now stands.
I mean this is good, because AI generated content is explicitly against the guidelines, however I can't help but think there is some utility to be had with AI and online encyclopedias, and we might be missing out on that.
Of course I'd love for this experiment to be done outside of the main site, and only integrated when it's mature, stable, and proven to be actually useful, but other than that implementation concern, I feel this is something that needs to be explored.
You might find grokipedia and latentpedia interesting as two such attempts.
If we leave out environmental (energy, datacenters, coolant) and political arguments (copyright stealing, private data harvesting etc.) even if we agree that those are "bad".
What then, is the problem of AI-Generated Content in Wikipedia?
> Fake or misleading citations have become a major worry.
Why is this not a standalone problem? Humans can fake and mislead in citations too, in fact, this is a major problem and has been so, for literally centuries in science.
> Being a place that was, in theory, free from AI slop has become part of Wikipedia’s identity.
Isn't this a separate issue in itself too? One of "quality". If AI generates poor quality content, than I would think the poor quality is the problem, not the producer of it.
The article mentions several times how hard it is to detect AI content. If it is that hard, then obviously AI is doing a good job and producing content that matches that of humans. Why then insist on one type of producer?
Poor quality is the problem and since the bandwidth of editors doesn't magically grow with the amount of input, rejecting AI content is a very effective way to keep average quality up.
>Isn't this a separate issue in itself too? One of "quality". If AI generates poor quality content, than I would think the poor quality is the problem, not the producer of it.
Yes, but who will review the mountains of slop to determine whether it is of acceptable quality? The main problem AI introduces is high volume at low quality, often overwhelming the human resource bottlenecks these systems have in place.
Good luck with that. I can’t see how it’s even possible, today, let alone in the future.
It isn't possible, in the same way that keeping copyrighted material out of Wikipedia isn't possible: there's probably going to be a backlog spanning years or decades, but some of those investigations will eventually complete and result in an action being decided on.
There will be a point in the future, possibly near future, when AI will be capable of reliably producing encyclopedic content, and we'll have tools to verify that the content produced passes reasonable standards.
Today is not the day. Especially not regarding the verification.
That's really not how probabilistic systems work though. They're great at getting 80% of the way to the goal but the last 20% is always excruciatingly difficult. I really don't intend that a knock because LLMs are useful, but they also aren't magic boxes where anything is possible.
This is the problem that a lot of user-content based sites, and open software projects, are experiencing. The tools make prodiving 80% correct submissions so easy that many people are doing that and thinking that it is fine not to bother verifying for correctness (or not even knowing how to verify correctness). This means those projects are being inundated by submissions that are 20% tosh or worse.
Another problem with user content sites, these numbers are completely pulled from the ass and are a meme that just gets repeated ad nauseam. They mean nothing, but there will be people that take it seriously.
Is 80/20 ever generally correct? Why is it favored over the 90/10 meme? Why would it apply to this? Why wouldn’t the numbers be vastly different for different domains of content generation? Etc.
If you pay attention, so much user content is just repetition of something they read on the same fucking website and uncritically checked into their brain.
Current HN top post is Roblox downloaded 145GB models from us (including adult content) without asking. I fully expect to start seeing comments to the tune of “Roblox is stealing porno to train AI for children” within the day in any discussion Roblox comes up in.
Why would these folk’s contribution to any other user content site be any more thoughtful?
80/20 doesn’t mean literally 80% and 20%
It’s just a rough way to say “mostly this with a decent bit of that” because 20% seems like a medium-small percent that could or could not matter depending on the context
That’s all anyone means when they say 80/20
To your second point, the 80% could be lots of basic things and the 20% could be the important facts, so it’s not always meant as a dismissal that the 20 doesn’t matter
Coding and math are easily verifiable, language and prose is not.
As a result, I don't think LLMs will reach this state easily.
Even putting aside accuracy, if the plan is for the tools that verify the written content to be in any shape or form outside of the human loop, then this feels like it glosses over the issues of both passive bias in data & active bias (e.g data filtering etc. ) when training such models that you'd be poisoning this information sources with.
Even subtle bias can manifest in significant ways. Given that the predominant market leaders in producing such models are currently : A country that's attempting to squeeze the word "america" in any geographic formation possible + rewriting history to put itself first, and a country that has perfected censorship en-mass and already actively doctors its own history.
I'm not convinced giving LLMs carte blanche to write authoritative sources on topics that - often are ideologically sensitive/controversial isn't just needlessly reckless and short-sighted. It's not a far reach to imagine such models reflecting the current views of administrations in these countries and becoming reluctant to mention certain colonial ambitions, environmental damage, political corruption, etc. where it might be relevant to authoritative content.
Wikipedia already struggles with issues in idealogical bias from authors - human validation (somewhat)helps mitigate that. You could argue that human validation is still prone to same bias - but you can always draw on a more diverse pool of editors with little ideological overlap. With LLM validation you're pretty much at the mercy of a pretty incestuous pool of data & a handful of self-serving corporates & governments.
Latentpedia.org will not have these problems. The content is human produced, but the extraction of a graph and creating the latent space is AI driven.
Grokipedia serves as an existence proof that it is possible.
I don't think anyone's arguing against whether or not it's possible, the question is whether it's valuable, correct, and A Good Thing.
I have access to a number of LLMs and can order it to build me a wiki site with all knowledge of the world, just like everyone else with the same access. What would make mine any more valuable or better than another?
Grokipedia's mistake is that it generates text statically instead of dynamically from a machine curated data structure in latent space.
Latentpedia starts from wikidata, not Wikipedia.
Funny, I wanted to mention grokipedia as an example of why a pile of slop that’s subtly wrong about many details is a bad idea.
So is Wikipedia, but with grokipedia you can at least correct it even if there is not a journalist pointing out the obvious.
Grokipedia lacks the fundamental quality that makes WP great, collaboration.
https://en.wikipedia.org/wiki/Grokipedia#:~:text=that%20arti... It literally states itself on the frontpage that it's bad.
Funny though, as that admission of error makes it more reliable than if it tried to hide this fact.
A parrot can be never a true source of information.
Wikipedia is a tertiary source. Its editors are parroting secondary sources. (No disrespect intended.) There's no reason why LLMs couldn't be good at that.
I would rather be worried about the quality of all the primary and secondary sources going forward.
There is a reason why LLMs can not be good at this: They don't know what they are quoting or citing. A different kind of model with factoid provenance could do it?
>They don't know what they are quoting or citing.
What do you mean by this? I have passed very large documents into LLMs and they are able to accurately extract quotes and identify their location in the source documents. I don’t see any reason to think that they couldn’t accurately quote from and cite existing literature.
LLMs cook up new sentences based on probability, based on everything in their training and their context. There's just nothing in their model that traces provenance of facts, they physically don't store that information. Once they have written a sentence, they can't tell you from which work they got this information.
There are tools where they try to retroactively add references, the LLM interfaces try to do this, but it's usually inaccurate.
I think of the way a scientific article works. "The sky is blue (Pearson, 1992)." The writer is fully aware what the factual statement is and which publication supports it (not just that, but which kind of publication - primary, secondary source, peer reviewed?). An LLM can try to imitate this, but the actual information to support this does not exist in its training.
They can. I had one doing original OCR of a scanned piece yesterday. It found relevant page numbers and understood the context. It read the whole book to find the relevant cites. Even went though the genealogy table and found ground breaking references no one noticed before. Total cost under 5 dollars and time was less than 20 mins.
The hallucination era is rapidly ending.
People reading a source can't know if it's true just by reading it either (though they could be fairly sure if it's false sometimes)
That's not how academic literature works. The structure is like this: Statement (Citation). The citation is not an affirmation of truth but a content declaration; this statement is supported by this publication. The receipts are there, so that you can trace the argumentation and make your own conclusions if necessary.
'Knowledge' formed this way is a living, evolving graph, and sometimes links are broken (findings are reevaluated or disproven); having the content declaration so clearly in the open makes it easier to deal with this evolving landscape.
Sure they can, as long as they can access online resources they can give you an exact list of sources they're using in their responses.
Then what you've said isn't true: it parrots an existing talking point, adding nothing.
the thing is: if AI-Generated Content (if correct, obviously) is just some topics learnt from humans, what's the difference between something correct written by a machine and something correct written by a human?
You can always read Grokipedia if this feels like a lost opportunity to you.
Why to multiply instead of going to the same place for knowledge? It is almost like you want to make a different Wikipedia for conservatives and liberals because one cannot tolerate a tone or style of the other. Probably we should dedicate dozens of sites for the same topic depending on the writing styles of the humans too. There are a few out there.
In worst case we might have an 'AI language' (or languages) instead, so the sensitive souls could find a safe heaven from it elsewhere, choosing something else. Perhaps one along the idea of 'simple English', have it 'AI English'. Or something else satisfies those looking for a specific way of delivery they can handle exclusively.
I think knowledge is the important here, not the tone.
> Why to multiply instead of going to the same place for knowledge?
Why write more than a book instead of just putting everything into one book?
This is a way of thinking from which it is hard to get out, I have no idea how to point it to you.
LLMs can't know things. They have no concept of veracity. In a place for knowledge they'd better be left out.
In case you were not aware, Grokipedia is not merely "conservative", but literally AI generated.
There is already a different Wikipedia for conservatives, https://www.conservapedia.com
Honestly Wikipedia is just fine being written by humans. It's not the lack of copy that is holding Wikipedia back.
However,
> Perhaps one along the idea of 'simple English', have it 'AI English'.
That's actually an interesting idea. It could work, but I don't personally think it would be better than the English Wikipedia.
Also, are you expecting that humans would still be on the loop by deciding what gets added to AI English Wikipedia, or you think that LLMs should get to decide that too?
Yes, why even put the slop on Wikipedia when you can get it directly from the source.
> It is almost like you want to make a different Wikipedia for conservatives and liberals because one cannot tolerate a tone or style of the other.
Many conservative worldview elements such as climate change denialism, creationism or anti LGBT view (e.g. LGBT being "unnatural") are not backed by reality because they run counter to scientifical consensus. And that's before we go into the outlandish bullshit conspiracy crap like "ZOG/zionist occupied government", "flat earth", "9/11 was faked", "the moon landing was faked" and the likes that gains more and more momentum among "conservative" people.
You cannot make a Wikipedia appealing to conservatives.
"if correct, obviously" - please elaborate. I do not see how this is obvious. Or how being correct is obvious.
Not to mention this exact question is being discussed in the article.
Not sure what question you're supposing he asked which was in the article. OP's point seemed to be that correct words written by a human could be effectively the same as correct words written by a machine, supposing the machine managed to be correct by learning from human content. The 'obvious' part is this wouldn't be true if the AI content was incorrect. At least that is what I got.
If restaurant asks to only eat the food you bought there at their tables, the question is not "but what if food from other places also is good"?
Can't wikipedia ask who and it what way writes content on their pages?
Ironically enough I just started an "Encylopedia of AI" project, and I've decided to generate all of the content with DeepSeek, with me being an editor/reviewer. I'm not really doing it for anyone except myself but I'm quite enjoying it so far. https://enkuklios.com/