Examining public perception and cognitive biases in the presumed influence of deepfakes threat: empirical evidence of third person perception from three studies

ABSTRACT

Deepfakes have a pernicious realism advantage over other common forms of disinformation, yet little is known about how citizens perceive deepfakes. Using the third-person effects framework, this study is one of the first attempts to examine public perceptions of deepfakes. Evidence across three studies in the US and Singapore supports the third-person perception (TPP) bias, such that individuals perceived deepfakes to influence others more than themselves (Study 1–3). The same subjects also show a bias in perceiving themselves as better at discerning deepfakes than others (Study 1–3). However, a deepfakes detection test suggests that the third-person perceptual gaps are not predictive of the real ability to distinguish fake from real (Study 3). Furthermore, the biases in TPP and self-perceptions about their own ability to identify deepfakes are more intensified among those with high cognitive ability (Study 2-3). The findings contribute to third-person perception literature and our current understanding of citizen engagement with deepfakes.

KEYWORDS:

• Deepfakes
• deep fakes
• third-person perception
• first-person perception
• cognitive ability

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Nanyang Technological University: [Start Up Grant].

Notes on contributors

Saifuddin Ahmed

Saifuddin Ahmed (Ph.D., University of California-Davis) is an Assistant Professor at the Wee Kim Wee School of Communication and Information at Nanyang Technological University, Singapore.