A bigger concern in my mind is where 100% accuracy is needed, like when doing authentication (cf. any login screen that lets you in by looking at your face). A

A bigger concern in my mind is where 100% accuracy is needed, like when doing authentication (cf. any login screen that lets you in by looking at your face). A lot of experiments are done on visual data sets, but I don't see why these techniques need to be strictly for visual inputs. Is a machine learning model making decisions based on the results of its classifier? Then it is at risk of being fooled, and whatever decisions it's making, better be trivial ones. I wrote a document a few months ago that summarizes this and other risks that ML models currently face: https://matt.life/papers/security_privacy_neural_networks.pdf https://matt.life/papers/security_privacy_neural_networks.pd...