This rocky hill in Ebihens, France, is, well, just that — a rocky hill in Ebihens, France. But to pretty much any human observer, the assemblage of meaningless angles takes on a familiar appearance, that of a human face in profile. It has a distinct nose, eyes, lips, and chin, capped off with some foliage as hair. From the perspective pictured above, it’s impossible not to see a man in a mountain.
This is an example of a phenomenon known as pareidolia, the human tendency to read significance into random or vague stimuli (both visual and auditory). […]
Humans are not alone in their quest to “see” human faces in the sea of visual cues that surrounds them. For decades, scientists have been training computers to do the same. And, like humans, computers display pareidolia.
Though there is something basely human about the tendency to see faces in the non-human shapes around us, to anthropomorphize odd pieces of hardware or rocks on a hillside, that computers see humans where there are none should not be all too surprising. Facial-recognition software is a tough technological feat, and in the process, computers are bound to come up with false positives. Does this make the computers more like us? Have they taken on our most human cognitive errors? In a superficial sense, yes, computers do make errors that are similar to pareidolia, and this seems very human. But as you look into these computer false-positives a bit more, you find a different story.