A lot of users here seem to be under the misconception that these are 100% AI generated images.
The problem isn’t really with that as the article states that this is an issue with using AI in the editing process:
Outright hoaxes remain rare and are often easy to spot, said Lees – nobody is falling for a toucan sighting in Siberia – but he says birders often use AI to edit and improve an image, and the algorithm can then introduce parts from different bird species to create the new image.
It’s also worth noting that some phones allow you to zoom in beyond your camera’s normal capabilities by using AI to enhance the picture. With some algorithms this might not be an issue, but if it’s using a model that’s been trained by some animal/object database then this can introduce innaccuracies that would cause problems for researchers trying to keep their database clean.
For “AI editing”, I don’t have much of a problem if a model was trained to tweak the settings in something like Darktable to achieve a good baseline to start with. However, for contributing to research like this, I draw the line when models start generating their own pixels and overwriting the original image.
Hopefully iNaturalist and other similar groups start to look at the metadata of submitted images to help warn/educate end users about this problem. That would at least help with the AI literacy issue. Those metadata tags are already being placed there by the most popularly used tools.