In particular, know how to identify the common and deadly species (eg: much of the genus Amanita) yourself, and get multiple trustworthy field guides for your part of the world.

  • GlitterInfection@lemmy.world
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    8 months ago

    While I would not advocate anyone taking up amateur mycology under any circumstances, let alone with an app, or book, to guide them, it’s important to note that this article is biased and makes false or misleading claims.

    The main issue is that it is talking about AI and meaning LLM-based algorithms. But it uses a study that showed that apps which identify mushrooms are inaccurate in which all of the apps predate, and do not use, LLMs as part of their identification process.

    Countering misinformation with misinformation isn’t generally the best option in my opinion so I just wanted to point that out.

    • conciselyverbose@sh.itjust.works
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      8 months ago

      LLMs have literally zero value in any context vaguely related to any kind of advanced computer vision project. It is fundamentally impossible for them to improve the capability of a mushroom recognition app in any way.

      It’s not misinformation to state the fact that it’s an absolute certainty that anyone claiming to use an LLM to identify a mushroom is a scammer.

      • spujb@lemmy.cafe
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        8 months ago

        true to your name you kind of put my comment into less words, nice 👍

      • GlitterInfection@lemmy.world
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        8 months ago

        I read the article and its linked sources in a few cases. How else would I have been able to directly address them?

        When Australian scientists tested the accuracy of popular mushroom ID apps last year after a spike in poisonings, they found the most precise one correctly identified dangerous mushrooms 44 percent of the time.

        Notice this paragraph which links to https://pubmed.ncbi.nlm.nih.gov/36794335/

        The extract for which talks about the following apps:

        Picture Mushroom (Next Vision Limited©), Mushroom Identificator (Pierre Semedard©), and iNaturalist (iNaturalist, California Academy of Sciences©)

        None of which use LLMs and predate the issue that the article is talking about. I checked, before my comment, all of their pages on the iOS App store, at least. They’re all 4+ years old and none use LLMs.

        Amusingly enough, the Public Citizen article linked earlier in OP’s article calls out iNaturalist as something they’ve been working with to positively improve the experience of identifying mushrooms:

        https://www.citizen.org/article/mushroom-risk-ai-app-misinformation/

        The Fungal Diversity Survey, a project devoted to correcting the many gaps in understanding regarding fungal biodiversity, partners with iNaturalist to document and verify mushroom observation

        But ultimately there were no apps ACTUALLY TESTED that use OpenAI or LLMs for their identification.

        • JoBo@feddit.uk
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          8 months ago

          Where does the article say the problem started with AI? It doesn’t even mention LLMs, just the explosion in grifter apps since it became easier to produce a grifter app.

          If you read the article, you did not read it properly.

          • GlitterInfection@lemmy.world
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            8 months ago

            And they didn’t test any of them, and linked to an actual test which ALSO didn’t test any of them as if it supported the claim that these apps are, as you (but not the article) say, are grifter apps.

    • spujb@lemmy.cafe
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      8 months ago

      you have sort of a weird take on this? like here are our premises, what we know with certainty:

      • all mycology apps tested to date are known to be poor (highest accuracy less than 50%)
      • all LLMs are known to be fairly poor

      and the author is deriving the conclusion:

      • mycology apps that happen to be LLM-based have a high likelihood of being poor, so be careful

      like yes, it’s not an empirical conclusion because someone still needs to do the work of testing the LLM mycology apps. i’d call it maybe an evidence based hypothesis that the average consumer should heed rather than find out the hard way and get poisoned.

      but i think you condeming it as “biased,” “misinformation” or “misleading” is unnecessarily harsh. to me this looks like basic pattern recognition and forming hypotheses based on real evidence.

      maybe i am missing a hole in the logic here and if so let me know.