The Deepfakes We Missed: We Built Detectors for a Threat That Didn't Arrive

ArXi:2605.12075v1 Announce Type: cross Nearly a decade of Machine Learning (ML) research on deepfake detection has been organized around a threat model inherited from 2017--2019, revolving around face-swap and talking-head manipulation of public figures, motivated by concerns about large-scale misinformation and video-evidence fraud. This position paper argues that the threat the field prepared for did not arrive, and the threats that did arrive are substantially different.