Work

Humans Versus Machines: A Deepfake Detection Faceoff

Year: 2024

Type: article

Abstract: 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.

Source: Proceedings of the Association for Information Science and Technology

DOI: 10.1002/pra2.1139

Authors: Dion Hoe‐Lian Goh, Jonathan Pan, Chei Sian Lee

Institution: Nanyang Technological University

Language: English

Topic: Digital Media Forensic Detection

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funders: Ministry of Education - Singapore, Ministry of Education, India

Award: G6854926366