>instead, it seems to be finding the closest match in an existing dataset under the assumption that anybody who's ever been photographed by the police is perman

>instead, it seems to be finding the closest match in an existing dataset under the assumption that anybody who's ever been photographed by the police is permanently a criminal suspect. So is a witness, for the most part, they're just logistically challenged. Which is why photo lineups are, in my alternate universe where everybody understands probability and causal inference (because we require 4-year degrees in the science of criminology), a specific tool to discover specific things rather than an instantaneous indictment. There are myriad things wrong with using them, and if the detective doesn't understand that or worse wants to exploit that, the detective should be regarded no differently than the beat cop shooting their gun into the crowd to scare it off. https://lawcomic.net/guide/?page_id=5 https://lawcomic.net/guide/?page_id=5 Similarly: A detective's hunch about whether the person being interrogated committed a crime is a powerful tool. We just don't throw people in prison based on that alone. We're getting to the point that we could train an AI to develop such hunches, and that could be valuable. But we can't just throw people in prison based on that alone. We need to confirm such things with external evidence. Just like we need to confirm a single-eyewitness recollection or a rough photo, rather than just measure that recollection & numerically characterize that photo without any indication (or more commonly, with a 100% fraudulent indication) of probability of matching.