confusable-vision takes the 1,418 TR39 confusable pairs that map a non-Latin character to a Latin target (a-z, 0-9), renders both characters across every available system font, and computes SSIM for each pairing. The output is a scored JSON artifact: one continuous similarity score per pair, per font.
The history of gesture, in other words, bears directly upon the question of AI alignment. Humans across cultures and times intuitively maintain a set of semantic and ethical judgements rooted in our physicality, our learned and instinctive gestures, and the affordances of the natural world. There is just something “knockable” about wood. LLMs don’t have childhood memories of jumping over cracks in pavement or their grandmother teaching them gestures. Moreover, such things are not really in their training data either.
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