@article{ref1,
title="Examining public perception and cognitive biases in the presumed influence of deepfakes threat: empirical evidence of third person perception from three studies",
journal="Asian journal of communication",
year="2023",
author="Ahmed, Saifuddin",
volume="33",
number="3",
pages="308-331",
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.<p /> <p>Language: en</p>",
language="en",
issn="0129-2986",
doi="10.1080/01292986.2023.2194886",
url="http://dx.doi.org/10.1080/01292986.2023.2194886"
}