Comment on How AI and Wikipedia have sent vulnerable languages into a doom spiral

chloroken@lemmy.ml ⁨4⁩ ⁨days⁩ ago

• HereIAm@lemmy.world ⁨4⁩ ⁨days⁩ ago

  I understand you’re trying to be nice to minority languages, but if you write research papers you either limit your demographic to your own country, or you publish in English (I guess Spanish is pretty world wide as well). If you set out to read a new paper in your field, I doubt you’d pick up something in Mongolian.

  Even in Sweden I would write a serious paper in English, so that more of the world could read it. Yes, we have text books for our courses that are in Swedish, but i doubt there are many books covering LLMs being published currently for example.

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  • chloroken@lemmy.ml ⁨4⁩ ⁨days⁩ ago

    I’m not “trying to be nice to minority languages”, I’m directly pushing back against the chauvinistic idea that Wikipedia is so important that those without it are somehow inferior.

    As for scientific papers, it’s called a translation. One can write academic literature in one’s native langaue and have it translated for more reach. That isnt the case with Wikipedia which is constantly being edited.

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    • HereIAm@lemmy.world ⁨4⁩ ⁨days⁩ ago

      No one is saying those who can’t access or reqd English wikipedia is inferior. The issue here is when what is on a non-english wikipedia article is misleading or flat out harmful (like the article says about growing crops), because of juvenile attempts at letting machine translations getting it very wrong. So what Greenland did was shut down its poorly translated and maintained wiki site instead of letting it fester with misinformation. And this issue compounding when LLMs scrape Wikipedia as a source to learn new languages.

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    • Alaknar@sopuli.xyz ⁨4⁩ ⁨days⁩ ago

      I’m not “trying to be nice to minority languages”, I’m directly pushing back against the chauvinistic idea that the English Wikipedia is so important that those without it are somehow inferior. There is no “doom spiral”.

      I think you missed the problem described here.

      The “doom spiral” is not because of English Wiki, it has nothing to do with anything.

      The problem described is that people who don’t know a “niche” language try to contribute to a niche Wiki by using machine translation/LLMs.

      As per the article:

      Virtually every single article had been published by people who did not actually speak the language. Wehr, who now teaches Greenlandic in Denmark, speculates that perhaps only one or two Greenlanders had ever contributed. But what worried him most was something else: Over time, he had noticed that a growing number of articles appeared to be copy-pasted into Wikipedia by people using machine translators. They were riddled with elementary mistakes—from grammatical blunders to meaningless words to more significant inaccuracies, like an entry that claimed Canada had only 41 inhabitants. Other pages sometimes contained random strings of letters spat out by machines that were unable to find suitable Greenlandic words to express themselves.

      Now, another problem is Model Collapse (or, well, a similar phenomenon in strictly in terms of language itself).

      We now have a bunch of “niche” languages’ Wikis containing such errors… that are being used to train machine translators and LLMs to handle these languages. This is contaminating their input data with errors and hallucinations, but since this is the training data, these LLMs consider everything in there as the truth, propagating the errors/hallucinations forward.

      I honestly have no clue where you’re getting anything chauvinistic here.

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      • AA5B@lemmy.world ⁨4⁩ ⁨days⁩ ago

        Is it even getting misused? Spreading knowledge via machine translation where there are no human translators available, had to be better than not translating. As long as there is transparency so people can judge the results ……

        And ai training trusting everything it reads is a larger systemic issue, not limited to this niche.

        Perhaps part of the solution is machine readable citations. Maybe a search engine or ai could provide better results if it knew what was human generated vs machine generated. But even then you have huge gaps on one side with untrustworthy humans (like comedy) and on the other side with machine generated facts such as from a database

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