IDEAS home Printed from https://ideas.repec.org/a/taf/rcybxx/v5y2020i2p199-217.html
   My bibliography  Save this article

Deepfake news: AI-enabled disinformation as a multi-level public policy challenge

Author

Listed:
  • Christopher Whyte

Abstract

The advent of ‘DeepFake' content that is increasingly difficult for humans and machines to distinguish as artificial portends a number of challenges to democratic societies. In order to effectively respond, policymakers must gain understanding of how DeepFake content might manifest. This paper aims to offer necessary context by exploring AI-enabled multimedia disinformation across different levels: (1) as a mass-produced, regular feature of the information environment in democracies and (2) as a highly tailored instrument used in tandem with cyber operations. I explore the impact of DeepFakes on the ability of populations to determine the origination, credibility, quality and freedom of information. Such macro impacts amplify the potential value of DeepFake content employed alongside targeted cyber activities, a combination that even alone offers belligerent actors new opportunities for enhancing attempts at disinformation and coercion. Nevertheless, I ultimately argue that DeepFakes should be thought of more as an evolution than a revolution in disinformation techniques, the real threat of which emerges from the manner in which new abilities to produce even reasonable fidelity fabrications rapidly and at scale combine the multiform shape of the modern digital information environment to make organized influence efforts much more dynamic than has previously been the case.

Suggested Citation

  • Christopher Whyte, 2020. "Deepfake news: AI-enabled disinformation as a multi-level public policy challenge," Journal of Cyber Policy, Taylor & Francis Journals, vol. 5(2), pages 199-217, May.
  • Handle: RePEc:taf:rcybxx:v:5:y:2020:i:2:p:199-217
    DOI: 10.1080/23738871.2020.1797135
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/23738871.2020.1797135
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/23738871.2020.1797135?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    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:taf:rcybxx:v:5:y:2020:i:2:p:199-217. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/rcyb .

    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.