Fooled twice: People cannot detect deepfakes but think they can

Nils Köbis, Barbora Doležalová, Ivan Soraperra

iScience · 2021 · 144 citations · 47 references

DOIFull text

Open access

Concepts

Abstract

= 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.

References

47