Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Wikipedia: WikiProject AI Cleanup

en.wikipedia.org

Post reply on HN
Print view View original

41–50 of 99 posts

Re: Wikipedia: WikiProject AI Cleanup

#41

Post by PurpleRamen »

PlatoIsADisease wrote: post #36

Isn't having a source the only thing that should be required. Why is AI speak bad? I'm a embarrassed to be associated with US Millennials who are anti AI. No one cares if you tie your legs together and finish a marathon in 12 hours. Just finish it in 3. Its more impressive. EDIT: I suppose people missed the first sentence: >Isn't having a source the only thing that should be required. >Isn't having a source the only…

There is usually no quality-control on AI-output, because people are lacking time and/or competence doing it, which are also the reasons why they are using AI.

And AI still can make up things, which might be fine in some random internet-comment, or some irrelevant article about something irrelevant happening somewhere in the world, but not with a knowledge-vault like Wikipedia.

And, we are talking here about Wikipedia. They are not just checking for AI, they are checking everything from everyone and have many many rules to ensure a certain level of quality. They can't check everything at once and fetch all problems immediately, but they are working step by step and over time.

> I'm a embarrassed to be associated with US Millennials who are anti AI.

You should be embarrassed for making such a statement.

Re: Wikipedia: WikiProject AI Cleanup

#43

Post by Tiberium »

vintermann wrote: post #33

There was a paper recently about using LLMs to find contradictions in Wikipedia, i.e. claims on the same page or between pages which appear to be mutually incompatible. https://arxiv.org/abs/2509.23233 I wonder if something more came out of that. Either way, I think that generation of article text is the least useful and interesting way to use AI on Wikipedia. It's much better to do things like this paper did.

You can easily do this with normal GPT 5.2 in ChatGPT, just turn on thinking (better if extended) and web search, point a Wikipedia page to the model and tell it to check the claims for errors. I've tried it before and surprisingly it finds errors very often, sometimes small, sometimes medium. The less popular the page you linked is, the more likely it'll have errors.

This works because GPT 5.x actually properly use web search.

Re: Wikipedia: WikiProject AI Cleanup

#44

Post by mrweasel »

jcattle wrote: post #11
Antibabelic wrote: post #4

I found the page Wikipedia:Signs of AI Writing[1] very interesting and informative. It goes into a lot more detail than the typical "em-dashes" heuristic. [1]: https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing

An interesting observation from that page: "Thus the highly specific "inventor of the first train-coupling device" might become "a revolutionary titan of industry." It is like shouting louder and louder that a portrait shows a uniquely important person, while the portrait itself is fading from a sharp photograph into a blurry, generic sketch. The subject becomes simultaneously less specific and more exaggerated."

To me that seems like we're mistaken in mixing fiction and non-fiction in AI training data. The "a revolutionary titan of industry" makes sense if you where reading a novel where something like 90% of a book is describing the people, locations, objects and circumstances. The author of a novel would want to use exaggeration and more colourful words to underscore a uniquely important person, but "this week in trains" would probably de-emphasize the person and focus on the train-coupler.

Re: Wikipedia: WikiProject AI Cleanup

#45

Post by Amorymeltzer »

jcattle wrote: post #11
Antibabelic wrote: post #4

I found the page Wikipedia:Signs of AI Writing[1] very interesting and informative. It goes into a lot more detail than the typical "em-dashes" heuristic. [1]: https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing

An interesting observation from that page: "Thus the highly specific "inventor of the first train-coupling device" might become "a revolutionary titan of industry." It is like shouting louder and louder that a portrait shows a uniquely important person, while the portrait itself is fading from a sharp photograph into a blurry, generic sketch. The subject becomes simultaneously less specific and more exaggerated."

I particularly like (what I assume is) the subtle paean to Ted Chiang's "Blurry Jpeg of the Web" in there.

https://www.newyorker.com/tech/annals-of-technology/chatgpt-...>

Re: Wikipedia: WikiProject AI Cleanup

#46

Post by nottorp »

robertjwebb wrote: post #15
jcattle wrote: post #11

Earlier quoted context omitted.

An interesting observation from that page: "Thus the highly specific "inventor of the first train-coupling device" might become "a revolutionary titan of industry." It is like shouting louder and louder that a portrait shows a uniquely important person, while the portrait itself is fading from a sharp photograph into a blurry, generic sketch. The subject becomes simultaneously less specific and more exaggerated."

The funny thing about this is that this also appears in bad human writing. We would be better off if vague statements like this were eliminated altogether, or replaced with less fantastical but verifiable statements. If this means that nothing of the article is left then we have killed two birds with one stone.

What do you think the LLMs were trained on? 90% of everything is crap, and they trained on everything.

Re: Wikipedia: WikiProject AI Cleanup

#47

Post by nottorp »

Tiberium wrote: post #43
vintermann wrote: post #33

There was a paper recently about using LLMs to find contradictions in Wikipedia, i.e. claims on the same page or between pages which appear to be mutually incompatible. https://arxiv.org/abs/2509.23233 I wonder if something more came out of that. Either way, I think that generation of article text is the least useful and interesting way to use AI on Wikipedia. It's much better to do things like this paper did.

You can easily do this with normal GPT 5.2 in ChatGPT, just turn on thinking (better if extended) and web search, point a Wikipedia page to the model and tell it to check the claims for errors. I've tried it before and surprisingly it finds errors very often, sometimes small, sometimes medium. The less popular the page you linked is, the more likely it'll have errors. This works because GPT 5.x actually properly use…

Have you verified those errors?

Re: Wikipedia: WikiProject AI Cleanup

#49

Post by kingstnap »

paradite wrote: post #23
Antibabelic wrote: post #4

I found the page Wikipedia:Signs of AI Writing[1] very interesting and informative. It goes into a lot more detail than the typical "em-dashes" heuristic. [1]: https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing

Ironically this is a goldmine for AI labs and AI writer startups to do RL and fine-tuning.

Seems more like the kind of thing you would make prompts using.

I can totally see someone taking that page and throwing it into whatever bot and going "Make up a comprehensive style guide that does the opposite of whatever is mentioned here".

Re: Wikipedia: WikiProject AI Cleanup

#50

Post by JimDabell »

vintermann wrote: post #33

There was a paper recently about using LLMs to find contradictions in Wikipedia, i.e. claims on the same page or between pages which appear to be mutually incompatible. https://arxiv.org/abs/2509.23233 I wonder if something more came out of that. Either way, I think that generation of article text is the least useful and interesting way to use AI on Wikipedia. It's much better to do things like this paper did.

That’s super interesting. I had a similar idea about 18 months ago.

I think the biggest opportunity is building a knowledge graph based on Wikipedia and then checking against the graph when new edits are made. Detect any new assertions in the edit, check for conflicts against the graph, and bring up a warning along with a link to all the pages on Wikipedia that the new edit is contradicting. If the new edit is bad, it shows the editor why with citations, and if the new edit is correcting something that Wikipedia currently gets incorrect, then it shows all the other places that also need to be corrected.

https://www.reddit.com/r/LocalLLaMA/comments/1eqohpm/if_some...

Post reply on HN