Is there much in the way of datasets of things that are recognizable but triggering incorrect something-or-other (what is it exactly? Semantic sensations?)

When we as humans see a face in a cookie or something we quite often spend some time gazing at it noting what it is about the the arrangement of features that triggers the pareidolia. I have wondered if that urge to contemplate the similarity difference is an instinctive response to gather more data for future accuracy.

I guess in a similar vein there would be merit in collecting a data set of all of those quirks that generative AI produces to provide a point of comparison. Notably when most image generators produce artifacts it's because the local image generation is accurate but at odds with the global image. So fingers are beside fingers accurately but there are too many, or a swirl near some hair becomes hair but doesn't actually connect to the top of the head.