As I’m sure many of you are well aware, there are a great many problems with the Computer Vision suggestions for anything except the most common, easily recognisable species. I’m well aware that AI image recognition is still in its infancy, and the iNat AI is really one of the better ones out there, but it still just causes so many problems. This is especially so with new and inexperienced users who don’t really know how to use iNat yet. I’m not entirely sure what a solution to this would be (that’s why I’m discussing it here) but something about the wording and/or the interface just encourages people to pick the CV suggestion even when it’s very clearly wrong. I know that CV is often quite good for common and large species, but as someone who works with insects it just seems like the AI is always against us and is yet another problem without offering much benefit. Apologies if it has been brought up before but I couldn’t find any relevant forum posts.
I think a lot of the problem is that new users are immediately prompted with a CV identification suggestion when they go to upload a sighting, and they pick it thinking that it’s correct. Sometimes I cannot understand why people have chosen something beyond “it’s what the computer suggested so it must be correct” though. I came to iNat directly from another similar citizen science website after it shut down (BowerBird), and I had been identifying observations here for a while before that, so I didn’t really have the experience of joining without understanding how citizen science works and how iNat specifically works. It would be great to get some comments from people who have just joined, or comments from people about their experiences of first joining.
The fact that we do have a serious problem is very obvious to me at the moment - I used to curate and identify a large number of Australian taxa but I was forced to stop last year due to health reasons. I am only just starting to get back into this, reviewing all of the sightings that I missed, and the number of incorrect computer vision-suggested identifications is astounding. Most of these taxa are not groups that other people identify because frequently they do require a lot of technical knowledge and experience, but that means that nobody is there to pick up on the mistakes. Most of these just sit there at Needs ID until I come along and correct them, but sometimes another inexperienced or new user will use the CV suggestion as well and confirm the identification, taking it to research grade. I can only imagine what the situation is like for taxa that have no experts here to help correct mistakes, or to even find mistakes in the first place.
Here are a couple of examples of Orthoptera from inland Australia that help illustrate some of the problems:
Here is a subadult Raspy Cricket (Gryllacrididae), probably something like Hadrogryllacris:
The observer has suggested an ID of Gryllidea (Crickets) without using CV, which is not accurate but is an understandable mistake to make. However, the CV suggestions are very far from accurate:
None of these are even in the correct subfamily (none are in Gryllidea either though), and only one of them has any sightings anywhere near here, and only one other even have any iNat sightings in Australia! Hemiandrus is found in Australia, but we have no sightings of it here yet, so why is the AI so confident?
Here is another, of Macrazelota cervina:
The user initially IDed it as Arphiini, which is what CV suggested, but there are no Arphiini anywhere near Australia. Even now that it has been corrected, the AI continues to suggest Lactista in Arphiini:
Pycnostictus is at least in the same family and is found in this area, but the same could be said of more than 200 other species as well. And why does the AI suggest only nearby top suggestions for this sighting, but not for the other one? I have not changed any settings. Importantly also, why is the ‘pretty sure’ suggestion not a nearby taxon as well?
I think a lot of the problem here comes from the wording of the suggestions, and from how much people overestimate the ability of AI. Plenty of people I know will take Google Lens suggestions as if they are certainly correct, because what reason do they have to doubt it? In essence I strongly believe the wording needs to change. The current “We’re pretty sure this is in the genus [something]” quite drastically overstates the AI’s ability, and because of that people accept it as correct without checking and without even knowing that it’s probably not correct. There are millions of species and we can’t expect the AI to be able to differentiate every single one, but the current wording doesn’t reflect this. There is no indication that the AI can only identify common species, and there is no indication that it is frequently very wrong. This is confusing for new users I’m sure, because if you have a photo of an insect that you have never seen before, and the AI used by such a successful and well-known platform like iNat says that it’s “pretty sure” that your photograph is of something not even found on your continent, why would you doubt it? But even for experienced users it seems to be a problem - e.g. the one who used the CV suggestion of Arphiini in the above sighting has a couple of hundred sightings.
I’m not sure what a better-worded approach would be, but the one we currently have simply doesn’t work. Suggestions for better wording are most welcome!
For a while I thought this was the only problem, but here is a situation that still confuses me. A photograph of Gea heptagon showed up in a spider group on Facebook, and after a bit of discussion everyone was happy with the ID (it was initially IDed as G. theridioides). The exciting thing is that these are the first photographs of the species in Australia (as far as I know), so I asked the person who posted it if they would be happy to put it on iNat. They added the sighting which is fantastic, but, using the CV suggestion, they IDed it as Argiope keyserlingi. Why??? The user knew it was Gea, and they even wrote in the observation description that there was discussion on Facebook as to whether it was G. theridioides or G. heptagon. So why did they ID it as A. keyserlingi?? The two do look similar and they are closely related, and it would be an easy mistake to make for someone who didn’t know what they were looking at. I certainly don’t expect the AI to be able to ID it as G. heptagon, because all of the other iNat sightings of the species are from North America, where they look fairly different (and it’s the other side of the world anyway). Indeed the AI does not really have any other suggestions:
But the user knew what it was before they even made an iNat account, so why did they default to the CV suggestion?? Is there something in the “add observations” page that encourages people to use it even when they know it’s wrong? Even the more experienced users will go against their own gut feeling and choose the CV option, and then when I correct them they tell me that they shouldn’t have trusted the AI.
I’m honestly not sure of a way to remedy this, but it causes so many problems. It needs to explicitly and clearly state somewhere obvious that it’s a suggestion only, that the AI is frequently incorrect, and that users should not think that the computer knows better than they do. Perhaps a little pop-up window for new users the first few times they use the CV suggestion to identify their sightings, or perhaps even completely disable the CV suggestions until users have completed a little tutorial or something. I know that probably sounds a tad extreme, but it’s a huge huge problem. There’s an entire forum wiki devoted to cleaning up CV-suggested misidentifications, and that’s just the ones that we know about. For all those taxa that don’t get regularly checked, there are probably countless misidentifed sightings and nobody who can fix them. Suggestions on how to fix these sorts of problems are welcome, but it just gets very overwhelming continually telling new users that the AI is usually wrong, and that they should check the suggestions before selecting them, and then going back through all of the CV misidentifications repeating the process again and again to try to get things in order (and that’s just in those few groups that I am knowledgeable on).