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.
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.
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.
You didn’t read the article.
I read the article and its linked sources in a few cases. How else would I have been able to directly address them?
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/
But ultimately there were no apps ACTUALLY TESTED that use OpenAI or LLMs for their identification.
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.
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.
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.
true to your name you kind of put my comment into less words, nice 👍
you have sort of a weird take on this? like here are our premises, what we know with certainty:
and the author is deriving the conclusion:
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.