Deepfake detection by human crowds, machines, and machine-informed crowds
The recent emergence of deepfake videos raises theoretical and practical questions. Are humans or the leading machine learning model more capable of detecting algorithmic visual manipulations of videos? How should content moderation systems be designed to detect and flag video-based misinformation? We present data showing that ordinary humans perform in the range of the leading machine learning model on a large set of minimal context videos. While we find that a system integrating human and mode...
Alicia Guo Kim Jong Un Vladimir Putin Massachusetts Institute Of Technology Committee Media Lab Deepfake Detection Challenge
Source: pnas.org