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.
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.
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.
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 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
Sometimes. But it, or 90/10, or sometimes 75/25, is understood to main “a large part of the time”/“a significantly smaller but still crucial amount off the time”.
> 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.
Which is exactly the problem. We now have LLMs doing the same thing, flooding everywhere with more of that noise, further hiding what good signal remains. Even if some of that good signal is by chance almost entirely LLM generated too, it appears to be at best a vanishingly small amount.
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?
Saying there is no collaboration is like saying multiple people on a software project can't collaborate with Claude Code because it's really just Claude writing the code.
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 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...
Hence all the AI labs buying up and destroying physical books. Even "yellow press" stuff, pulp fiction, dime novels and whatnot "low quality" literature are a valuable source of how actual humans write.
I wouldn't even have much of a problem with it - if these labs would be fair enough to humanity as a whole to provide the raw scans after the process is completed, and if they would limit themselves to books that have been on the market for more than 20 years.
> A stripped book is a mass market paperback that has been stripped of its cover in order to be recycled. The covers are returned to the publisher as evidence that the books have been destroyed and to obtain a credit on the purchase price.[1] The books are meant to be destroyed by pulping but some find their way to street merchants, sometimes by illegal means, and are resold.[2]
I grew up reading books with this ditty in them:
> If you purchased this book without a cover you should be aware that this book is stolen property. It was reported as “unsold and destroyed” to the publisher and neither the author nor the publisher has received any payment for this “stripped book.”
Those books certainly weren't scanned before being pulped. Would've been illegal. Really, the big thing that destroys books is the copyright term being as long as it is.
AI companies weren't buying up tons of unsold mass-market materials, and I think it's disingenuous to even make the comparison.
What was going on recently was AI companies were specifically seeking out rare — or sometimes irreplaceable — books to supplement their data sets (and hopefully getting a leg up on their competitors). The destruction of the books wasn't the point, it was just a consequence of the business-oriented realization that they could scan the contents of more books faster if they just chopped off the bindings rather than investing the time to care for the books and keep them intact (plus supposedly playing along with copyright law by "only having one copy of the copyrighted material").
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 ;).
I think they were talking about spiral shank nails, not ring shank. It has a twisted grove along the shank of the nail, sort of like an extremely course thread.
I've seen these used to assemble wooden palettes (they are VERY hard to remove). A search on Home Depot reveals they may be used for certain types of siding as well.
I built a house with them. You really want to check twice if you're putting them in where you want them because getting them out is - as you noted - annoyingly difficult. But they're very nice for large surfaces that are going be battered by the wind, they're much longer than your typical screw and working with them is very fast.
> it becomes noisy and sameish at larger scale or the more you read it.
I absolutely understand where you are coming from, and I agree to a point. If you're of an age where you actually read a printed encyclopedia, the tone and voice of the entire set was sameish as well. The difference is that it didn't sound LLMish like LLM text does. I know that printed encyclopedias would have been vetted by editors, and I feel this is the key difference. Editors not only knew grammar rules, but had that sense of good writing practices that's hard to write down as rules. A piece of text passed through a good editorial review will read human while LLM text reads as LLM text.
I think this is exactly what we should do. Send agents to collect evidence and write deep research reports, then train on those reports. DR reports are derived from hundreds of sources and can map out the distribution, what are the opinions on a topic, not necessarily what is the one correct answer. Agents could write one piece about every human, place, topic, event or entity there is under the sun. They could also try to generate the same without sources (closed-book mode) and report on LLM biases on that question.
Please let's not clutter up wikipedia with new articles for every entity in the universe. It would be too much for humans to review. Though it sure would be funny to see an AI-peida as you describe.
What you're describing though is that individual source of content tends to sound like itself. That isn't a problem so much as what we tend to want and expect.
When we say AI sounds same-ish we mean all sources of content can sound the same - fiction and non-fiction, news articles and blog posts, marketing pitches and ai drafted personal messages, all sound kinda the same. That is a different situation, and that's before you get to "and that one sound is LLMish".
A lot of AI content is just wrong - hallucinated lies. Just look at Grok-slop by the right-arm raising billionaire clown. It looks neat on the surface but once you dig in you begin to see more and more errors, thus wasting your time.
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've felt that like tools like Grammarly are harmful for native speakers. I get if it's not your first language you need extra help, but if you are a native speaker these tools only serve to homogenize your way of speaking.
Having a program constantly suggest "better" ways of phrasing things is stripping your personality from your language. Maybe this is needed if you are writing corporate PR pieces, but you should avoid it for anything else.
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/
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.
Makes sense indeed, but then the quality nor the volume is the underlying problem, but the review process.
Apparently Wikipedia has good reasons to not change this process fundamentally, other than add extra filters at the start to try and detect low quality posts, based on attributes that show a correlation with low quality.
Sounds like a pragmatic, but far from ideal solution to me. Correlation is not causation.
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.
One of the challenging things about sharing knowledge is that it doesn't exist in a vacuum. With certain things there's definitely more complicated and nuanced approaches that may make sense. It's absolutely true that it can swing back too far - and that's usually the case with the most important areas of life, I'd argue. It's the cause of all sorts of seemingly-well-intentioned attempts at sharing information, as well as, of course, intentionally malicious forms of sharing information. That's what all propaganda does, realistically.
To bring it back to the topic, this is certainly a serious concern with AI-generated content. The world changes and evolves and things that are acceptable become unacceptable and vice versa. With training data potentially being stuck in time due to the majority of new data being generated, history could essentially just stop here. Or at least that is an idea that's been proposed. I'll be honest that I have thought that to be a genuine concern. However, objectively, novel ideas have come out of these new technologies. So it's a bit of a pickle to figure out how that relates to the human experience as time marches on.
Those claims you complain about are true? HIV treatment made massive leaps and yes, regular injections in fact make your stop transmitting it. It is manageable chronic health condition at this point. It did NOT used to be so, it used to be deadly. But, medicine made massive improvements.
Also, after you had unsafe sex or accidentally touched infected injection, you can get early anti-hiv drugs - which means you will not get HIV.
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.
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.
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 was living and working in Kokomo, Indiana when the Ryan White situation occurred. There were other kids who got AIDS/HIV from hemophilia meds like Ryan. My coworkers were thrilled that several of these kid's homes were burned to the ground by people who didn't want those kids going to "our" school. Those coworkers were also proud that one of the Grand Wizards of the Klan lived in Kokomo.
I remember Reagan manufacturing AIDS into some sort of plague sent by God to punish brown skinned alongside gay people. I'm not surprised that historians have whitewashed Reagan's racism.
It was Reagan's administration that got the Fairness Doctrine repealed. That single action made the right wing media possible. Fox could never have existed prior.
The HPV vaccine prevents several cancers. Australia, which has mandatory HPV vaccination, is seeing a 95% drop in the cervical cancers that the vaccine prevents compared with pre-vaccine people. In my state, as well as some other red states, want the HPV shot banned or at the very minimum requiring positive parental consent.
I don't follow Wikipedia policies, but I imagine the solution is to break it up into multiple pages, and replace each long section (e.g. Origins) with a 1-2 paragraph summary.
And while I agree it's too long, do note that about 50% is the References section.
> 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.
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.
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
Today is not the day. Especially not regarding the verification.
I would rather be worried about the quality of all the primary and secondary sources going forward.
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.
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.
'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 hallucination era is rapidly ending.
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
Sometimes. But it, or 90/10, or sometimes 75/25, is understood to main “a large part of the time”/“a significantly smaller but still crucial amount off the time”.
> 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.
Which is exactly the problem. We now have LLMs doing the same thing, flooding everywhere with more of that noise, further hiding what good signal remains. Even if some of that good signal is by chance almost entirely LLM generated too, it appears to be at best a vanishingly small amount.
Funny though, as that admission of error makes it more reliable than if it tried to hide this fact.
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?
Latentpedia starts from wikidata, not Wikipedia.
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.
As a result, I don't think LLMs will reach this state easily.
"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
Not just random output of who knows what model, from who knows what prompt.
[1] https://www.youtube.com/watch?v=IU4ByUbDKNc
I wouldn't even have much of a problem with it - if these labs would be fair enough to humanity as a whole to provide the raw scans after the process is completed, and if they would limit themselves to books that have been on the market for more than 20 years.
https://futurism.com/artificial-intelligence/amazon-destroyi...
That does not really make it a law though.
https://en.wikipedia.org/wiki/Stripped_book
> A stripped book is a mass market paperback that has been stripped of its cover in order to be recycled. The covers are returned to the publisher as evidence that the books have been destroyed and to obtain a credit on the purchase price.[1] The books are meant to be destroyed by pulping but some find their way to street merchants, sometimes by illegal means, and are resold.[2]
I grew up reading books with this ditty in them:
> If you purchased this book without a cover you should be aware that this book is stolen property. It was reported as “unsold and destroyed” to the publisher and neither the author nor the publisher has received any payment for this “stripped book.”
Those books certainly weren't scanned before being pulped. Would've been illegal. Really, the big thing that destroys books is the copyright term being as long as it is.
What was going on recently was AI companies were specifically seeking out rare — or sometimes irreplaceable — books to supplement their data sets (and hopefully getting a leg up on their competitors). The destruction of the books wasn't the point, it was just a consequence of the business-oriented realization that they could scan the contents of more books faster if they just chopped off the bindings rather than investing the time to care for the books and keep them intact (plus supposedly playing along with copyright law by "only having one copy of the copyrighted material").
Unfortunately, this would get them an even bigger copyright smackdown than they've already received.
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 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.
I've seen these used to assemble wooden palettes (they are VERY hard to remove). A search on Home Depot reveals they may be used for certain types of siding as well.
I built a house with them. You really want to check twice if you're putting them in where you want them because getting them out is - as you noted - annoyingly difficult. But they're very nice for large surfaces that are going be battered by the wind, they're much longer than your typical screw and working with them is very fast.
I absolutely understand where you are coming from, and I agree to a point. If you're of an age where you actually read a printed encyclopedia, the tone and voice of the entire set was sameish as well. The difference is that it didn't sound LLMish like LLM text does. I know that printed encyclopedias would have been vetted by editors, and I feel this is the key difference. Editors not only knew grammar rules, but had that sense of good writing practices that's hard to write down as rules. A piece of text passed through a good editorial review will read human while LLM text reads as LLM text.
When we say AI sounds same-ish we mean all sources of content can sound the same - fiction and non-fiction, news articles and blog posts, marketing pitches and ai drafted personal messages, all sound kinda the same. That is a different situation, and that's before you get to "and that one sound is LLMish".
Having a program constantly suggest "better" ways of phrasing things is stripping your personality from your language. Maybe this is needed if you are writing corporate PR pieces, but you should avoid it for anything else.
Of course AI can be used to check sources, get critical feedback and translate to languages. But content should be 100% human driven.
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?
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.
Apparently Wikipedia has good reasons to not change this process fundamentally, other than add extra filters at the start to try and detect low quality posts, based on attributes that show a correlation with low quality.
Sounds like a pragmatic, but far from ideal solution to me. Correlation is not causation.
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.)
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.
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".
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.
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)
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. :)
Hope your night works out well in the end.
To bring it back to the topic, this is certainly a serious concern with AI-generated content. The world changes and evolves and things that are acceptable become unacceptable and vice versa. With training data potentially being stuck in time due to the majority of new data being generated, history could essentially just stop here. Or at least that is an idea that's been proposed. I'll be honest that I have thought that to be a genuine concern. However, objectively, novel ideas have come out of these new technologies. So it's a bit of a pickle to figure out how that relates to the human experience as time marches on.
Thank you. The world will keep on spinning. :)
Also, after you had unsafe sex or accidentally touched infected injection, you can get early anti-hiv drugs - which means you will not get HIV.
I mean, what exact bias is there?
“An article should not be a complete presentation of all possible details, but a summary of accepted knowledge regarding its subject“
https://en.wikipedia.org/wiki/Wikipedia:What_Wikipedia_is_no...
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 remember Reagan manufacturing AIDS into some sort of plague sent by God to punish brown skinned alongside gay people. I'm not surprised that historians have whitewashed Reagan's racism.
It was Reagan's administration that got the Fairness Doctrine repealed. That single action made the right wing media possible. Fox could never have existed prior.
The HPV vaccine prevents several cancers. Australia, which has mandatory HPV vaccination, is seeing a 95% drop in the cervical cancers that the vaccine prevents compared with pre-vaccine people. In my state, as well as some other red states, want the HPV shot banned or at the very minimum requiring positive parental consent.
And while I agree it's too long, do note that about 50% is the References section.
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.
Still, 2023-10 is probably the last pure https://en.wikipedia.org/wiki/Low-background_steel