Oh wow, that’s fantastic! Certainly puts me in my place; apologies that my little test was not very accurate :P
I still think we have a problem though - as you say that’s only with records that are Research Grade. More than half of the records I looked at in my little non-representative search were Needs ID. I suppose this balances out with the fact that the Needs ID sightings don’t really matter too much for accuracy if someone is there to correct them, but still it is frustrating and time-consuming to have to go correct them all.
I also think it has a lot to do with the fact that most of the records are from North America and Europe. Overall this is the opposite of a problem, because if the CV is trained for them it will recognise them better, and they are the majority of sightings. Over all sightings, that’s fantastic. But it’s not great for areas where there aren’t many sightings. As is obvious, this isn’t a problem for the majority of sightings but it is a problem for sightings in those areas. E.g. Australia makes up only 3% of the sightings in your test, because it only makes up around 3% of all the sightings on iNat. But it’s way, way worse for sightings here because a) there are fewer records to train with and b) there are far more species here (e.g. Australia has about 5 times the number of described species compared to the US). So it’s still a huge problem for us here. A change of wording of some sort would be really beneficial to places where the AI is not so good, but it doesn’t have to be a global change. I’m not sure if I’m getting my point across right but hopefully it makes sense.