University of Limerick
Browse

Face/Off: changing the face of movies with deepfakes

Download (778.32 kB)
journal contribution
posted on 2024-03-04, 14:29 authored by Gillian Murphy, Didier Ching, John Twomey, Conor Linehan

There are growing concerns about the potential for deepfake technology to spread misinformation and distort memories, though many also highlight creative applications such as recasting movies using other actors, or younger versions of the same actor. In the current mixed-methods study, we presented participants (N = 436) with deepfake videos of fictitious movie remakes (such as Will Smith staring as Neo in The Matrix). We observed an average false memory rate of 49%, with many participants remembering the fake remake as better than the original film. However, deepfakes were no more effective than simple text descriptions at distorting memory. Though our findings suggest that deepfake technology is not uniquely placed to distort movie memories, our qualitative data suggested most participants were uncomfortable with deepfake recasting. Common concerns were disrespecting artistic integrity, disrupting the shared social experience of films, and a discomfort at the control and options this technology would afford. 

History

Publication

PLoS ONE 18(7), e0287503

Publisher

Public Library of Science

Other Funding information

LERO Award (PP5004)

Also affiliated with

  • LERO - The Science Foundation Ireland Research Centre for Software

Department or School

  • School of Engineering

Usage metrics

    University of Limerick

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC