Computer vision AI systems present one of the most radical technical transformations of our time. Such systems are given unparalleled epistemic power to impose meaning on visual data despite their inherent ambiguity. This becomes particularly evident in computer vision AI that interprets the meaning of human faces in face recognition or emotion expression systems. Despite scientific, social and political concerns, facial analysis AI systems are widely deployed also in Japan, for example, for training employees to show certain facial expressions. This talk presents findings from a study of public perceptions of facial analysis AI across Argentina, Kenya, Japan, and the USA. It reveals similarities in justification patterns but also significant intra-country and inter-country diversity in response to different facial inferences. The study suggests that there is no “common sense” facial classification that accords with a general, homogeneous “human intuition”. Details and registration here