It seems strange to me that the authors of paper seem to have made no attempt to determine which factors the model is using to differentiate between images. Or

It seems strange to me that the authors of paper seem to have made no attempt to determine which factors the model is using to differentiate between images. Or even to ask the human comparisons how they obtained their greater than chance results. Instead, both the humans and the computer model seem to be considered to be considered perfect "black boxes", which give entirely inscrutable answers. It's not that it's always trivial to figure out what's happening inside a model like this, but I'm surprised that no attempt seems to have been made: modifying images and seeing which increases the scores, bringing in a co-author who actually understands what the model is doing, seeing if they can obtain similar results with a more interpretable model. Am I wrong, and in fact fining out what's actually happening is impossible, or of no benefit?