Fooled twice: People cannot detect deepfakes but think they can

Nils C Köbis; Barbora Doležalová; Ivan Soraperra

doi:10.1016/j.isci.2021.103364

Fooled twice: People cannot detect deepfakes but think they can

iScience. 2021 Oct 29;24(11):103364. doi: 10.1016/j.isci.2021.103364. eCollection 2021 Nov 19.

Authors

Nils C Köbis¹, Barbora Doležalová², Ivan Soraperra²

Affiliations

¹ Center for Humans and Machines, Max Planck Institute for Human Development, 14195 Berlin, Germany.
² Amsterdam School of Economics, University of Amsterdam, 1001 NJ Amsterdam, The Netherlands.

Abstract

Hyper-realistic manipulations of audio-visual content, i.e., deepfakes, present new challenges for establishing the veracity of online content. Research on the human impact of deepfakes remains sparse. In a pre-registered behavioral experiment (N = 210), we show that (1) people cannot reliably detect deepfakes and (2) neither raising awareness nor introducing financial incentives improves their detection accuracy. Zeroing in on the underlying cognitive processes, we find that (3) people are biased toward mistaking deepfakes as authentic videos (rather than vice versa) and (4) they overestimate their own detection abilities. Together, these results suggest that people adopt a "seeing-is-believing" heuristic for deepfake detection while being overconfident in their (low) detection abilities. The combination renders people particularly susceptible to be influenced by deepfake content.

Keywords: Artificial intelligence; Artificial intelligence applications; Behavioral neuroscience; Cognitive neuroscience; Neuroscience; Psychology; Social sciences.