Humans versus machines: a deepfake detection faceoff

Humans versus machines: a deepfake detection faceoff

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...

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Bibliographic Details
Main Authors: Goh Dion Hoe-Lian, Pan, Jonathan, Lee, Chei Sian
Other Authors: Wee Kim Wee School of Communication and Information
Format: Article
Language:English
Published: 2025
Subjects:
Computer and Information Science
Machine learning models
Deepfake detection
Online Access:https://hdl.handle.net/10356/181973
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Institution: Nanyang Technological University
Language: English
Description
Summary: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.

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