IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/cb7rw.html
   My bibliography  Save this paper

Deepfake Detection With and Without Content Warnings

Author

Listed:
  • Lewis, Andrew
  • Vu, Patrick
  • Duch, Raymond

    (University of Oxford)

  • Chowdhury, Areeq

Abstract

The rapid advancement of ‘deepfake’ video technology — which uses deep learning artificial intelligence algorithms to create fake videos that look real — has given urgency to the question of how policymakers and technology companies should moderate inauthentic content. We conduct an experiment to measure people’s alertness to and ability to detect a high-quality deepfake amongst a set of videos. First, we find that in a natural setting with no content warnings, individuals who are exposed to a deepfake video of neutral content are no more likely to detect anything out of the ordinary (32.9%) compared to a control group who viewed only authentic videos (34.1%). Second, we find that when individuals are given a warning that at least one video in a set of five videos is a deepfake, only 21.6% of respondents correctly identify the deepfake as the only inauthentic video, while the remainder erroneously select at least one genuine video as a deepfake.

Suggested Citation

  • Lewis, Andrew & Vu, Patrick & Duch, Raymond & Chowdhury, Areeq, 2023. "Deepfake Detection With and Without Content Warnings," OSF Preprints cb7rw, Center for Open Science.
  • Handle: RePEc:osf:osfxxx:cb7rw
    DOI: 10.31219/osf.io/cb7rw
    as

    Download full text from publisher

    File URL: https://osf.io/download/652c418e164d32058ea5e3a4/
    Download Restriction: no

    File URL: https://libkey.io/10.31219/osf.io/cb7rw?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Nathan F. Dieckmann & Robin Gregory & Ellen Peters & Robert Hartman, 2017. "Seeing What You Want to See: How Imprecise Uncertainty Ranges Enhance Motivated Reasoning," Risk Analysis, John Wiley & Sons, vol. 37(3), pages 471-486, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:cup:judgdm:v:16:y:2021:i:2:p:363-393 is not listed on IDEAS
    2. Galvao, Ana Beatriz & Mitchell, James & Runge, Johnny, 2019. "Communicating Data Uncertainty: Experimental Evidence for U.K. GDP," EMF Research Papers 30, Economic Modelling and Forecasting Group.
    3. repec:wrk:wrkemf:22 is not listed on IDEAS
    4. Toshio Fujimi & Masahide Watanabe & Hirokazu Tatano, 2021. "Public trust, perceived accuracy, perceived likelihood, and concern on multi-model climate projections communicated with different formats," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 26(5), pages 1-20, June.
    5. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    6. Carissa Bonner & Lyndal J. Trevena & Wolfgang Gaissmaier & Paul K. J. Han & Yasmina Okan & Elissa Ozanne & Ellen Peters & Daniëlle Timmermans & Brian J. Zikmund-Fisher, 2021. "Current Best Practice for Presenting Probabilities in Patient Decision Aids: Fundamental Principles," Medical Decision Making, , vol. 41(7), pages 821-833, October.
    7. Ana Beatriz Galvão & James Mitchell, 2024. "Communicating Data Uncertainty: Multiwave Experimental Evidence for UK GDP," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 56(1), pages 81-114, February.
    8. David R. Mandel & Daniel Irwin, 2021. "Facilitating sender-receiver agreement in communicated probabilities: Is it best to use words, numbers or both?," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 16(2), pages 363-393, March.
    9. Shoots-Reinhard, Brittany & Goodwin, Raleigh & Bjälkebring, Pär & Markowitz, David M. & Silverstein, Michael C. & Peters, Ellen, 2021. "Ability-related political polarization in the COVID-19 pandemic," Intelligence, Elsevier, vol. 88(C).
    10. Branden B. Johnson, 2019. "Experiments in Lay Cues to the Relative Validity of Positions Taken by Disputing Groups of Scientists," Risk Analysis, John Wiley & Sons, vol. 39(8), pages 1657-1674, August.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:osfxxx:cb7rw. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.