Humans Versus Machines: A Deepfake Detection Faceoff

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...

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Veröffentlicht in:Proceedings of the ASIST Annual Meeting 2024-10, Vol.61 (1), p.917-919
Hauptverfasser: Goh, Dion Hoe‐Lian, Pan, Jonathan, Lee, Chei Sian
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container_title Proceedings of the ASIST Annual Meeting
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creator Goh, Dion Hoe‐Lian
Pan, Jonathan
Lee, Chei Sian
description 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.
doi_str_mv 10.1002/pra2.1139
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identifier ISSN: 2373-9231
ispartof Proceedings of the ASIST Annual Meeting, 2024-10, Vol.61 (1), p.917-919
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subjects Accuracy
Deception
Deepfake detection
Human detection
Machine learning
Machine learning models
title Humans Versus Machines: A Deepfake Detection Faceoff
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