A couple of things to keep in mind:
- It takes more work to move to a broader ID than to a narrower ID, because of the “do you disagree?” dialogue box.
Personally, I’m usually going through observations identified as a particular genus or species. When I see misIDs I mostly just push them back up to the highest level that I believe is correct, even if they are taxa that I could identify. This is just more mentally efficient for me—if I’m paying attention to genus Alpha, I don’t want to be switching my focus to identifying members of genus Beta or genus Gamma every time those come up in the pile. One mental task at a time is plenty.
So, if your observation is seen by an identifier like me: The more precise ID does increase the likelihood that I will see it and put an ID on it, but I’m probably just going to kick it up to a higher ID, which doesn’t really help you. And if I’m encountering a large number of misIDs I’ll start getting irritated by the “do you disagree?” box.
- Misidentifications can propagate, both by way of the computer vision IDs and by way of other users IDing their observations by looking for other observations that look like the same taxon.
I think this is a larger problem at the species level. In some cases it can result in a feedback loop—as the number of observations of Alpha beta that are misidentified as Alpha delta increases, so does the probability that any new observation of Alpha beta will be misidentified as Alpha delta. It’s rare for this kind of feedback loop to really take off, but when it does it can be a real mess, creating hundreds or thousands of observations with the same misidentification.
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That said, what level of certainty is appropriate before you make an identification is a judgment call that does not have any good, general-purpose answer. There’s a complicated relationship between expertise and uncertainty. A large part of developing expertise in a particular genus is learning which species are likely to be confused with each other, and in which contexts. Without that knowledge, estimating the certainty of an identification is difficult!
Regardless of his other attributes, Rumsfeld’s famous taxonomy of knowledge is helpful here. If you’re learning the genus Astragalus, a particular species like Astragalus emoryanus will first be an unknown unknown (you don’t even know it’s one of the possible identifications for your observation), then a known unknown (you know it’s a possibility but aren’t sure how to identify it), then a known known (you know it’s a possibility and you can identify it reliably). When I visit areas where I don’t know the flora well, a lot of my work in identification is converting the unknown unknowns into known unknowns—figuring out what the possibilities are. My error rates are highest when I jump to an ID based on apparent familiarity without first checking if there are some unknown unknowns that I ought to be worried about.
(Wandering further down this rabbit hole, suppose you’re in an area where there are two species of genus Alpha, and Alpha beta is twenty times more frequently observed than Alpha delta. For observers who haven’t heard of Alpha delta (it is an unknown unknown), the most common misID will be identifying Alpha delta as Alpha beta. For observers who have heard of Alpha delta (it is a known unknown or a known known), the most common misID will be identifying Alpha beta as Alpha delta—if you know there are two species but you’re only seeing one of them, the natural tendency for most people is to try to force the variation within that species to match up with the two options.)