Humans Versus Machines: A Deepfake Detection Faceoff
Dion Hoe‐Lian Goh, Jonathan Pan, Chei Sian Lee · Proceedings of the Association for Information Science and Technology · 2024
ABSTRACT Machine learning (ML) models for deepfake detection are important for countering the threat of such videos. However, human detection is also critical because automated approaches may not always be available to people online. This study compares ML models versus humans for deepfake detection. Results surprisingly showed that humans performed better. Implications of our work are discussed.