Weirding is related to uncanniness, as in uncanny valley: a near-subconscious sense of map-territory misregistration. I think there are two varieties, A and B.
Type A uncanniness, which Sarah Perry explored, evokes an “emotion of eeriness, spookiness, creepiness” that you notice instantly, but cannot immediately isolate or explain. Here’s an example:
Human lookalike robot Repliee 2, detail from image by BradBeattie, CC BY-SA 3.0
Type B uncanniness, which Sarah Constantin explored, does not necessarily evoke those emotions, but may provoke a double take. Here are examples from an article on recognizing AI fakes.
Sample faces generated by a GAN, from How to recognize fake AI-generated images by Kyle McDonald
Two increasingly important domains — markets and AI — exhibit both kinds. Free markets and deep learning AIs generate more Type B uncanniness. Markets distorted by regulation, and GOFAI (including humanoid robots) generate more Type A uncanniness.
Kahnemann’s System 1/System 2 model is useful here.
Type A uncanniness is pattern wrongness, detected by System 1, evoking an immediate emotional reaction. If you aren’t fleeing, a slower System 2 response might kick in and supply a satisfactory explanation, and possibly creepiness relief.
Type B uncanniness is logical wrongness (unexpected facial asymmetry or incoherent grammar for example), prompting the double take (and possibly a delayed creeped-out reaction). You have to re-engage System 1 to reconstruct a narrative around the actual prevailing logic rather than the assumed one.
Too-symmetric faces are Type A uncanny. Mismatched earrings on a face are Type B.
Drug prices shooting up 10x suddenly is Type A. Bond markets defying “normal” logic is possibly Type B (I need a better example).
Markets are eating the world, and AIs are eating software. In both, we’re seeing a shift from Type A to Type B. Less creepy, more double-takey. It’s easier to get used to creepy patterns than unexpected logics.
About Venkatesh Rao
