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Deep fakes / edited by Michael Filimowicz.

By: Contributor(s): Material type: TextTextSeries: Algorithms and societyPublisher: London ; New York : Routledge, Taylor & Francis Group, 2022Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781003173397
Other title:
  • Deepfakes
Subject(s): Additional physical formats: Print version:: Deep fakesDDC classification:
  • 302.23/1 23/
LOC classification:
  • HM1206
Summary: "Deep Fakes: Algorithms and Society focuses on the use of artificial intelligence technologies to produce fictitious photorealistic audiovisual clips that are indistinguishable from traditional video media. For over a century, the indexical relationship of the photographic image, and its related media of film and video, to the scene of capture has served as a basis for truth claims. Historically, the iconicity of these images has featured a causal traceback to actual light rays in a particular time and space, which were fixed by chemical reactions or digital sensors to the resultant image. Today, photorealistic audiovisual media can be generated from deep learning networks which sever any connection to an actual event. Should society instantiate new regimes to manage this new challenge to our sense of reality and the traditional evidential capacities of the 'mechanical image?' How do these images generate information disorder while also providing the basis for legitimate tools used in entertainment and creative industries? Scholars and students from many backgrounds, as well as policy makers, journalists and the general reading public will find a multidisciplinary approach to questions of privacy and encryption encompassing research from Communication, International Studies, Writing and Rhetoric"-- Provided by publisher.
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Includes bibliographical references and index.

"Deep Fakes: Algorithms and Society focuses on the use of artificial intelligence technologies to produce fictitious photorealistic audiovisual clips that are indistinguishable from traditional video media. For over a century, the indexical relationship of the photographic image, and its related media of film and video, to the scene of capture has served as a basis for truth claims. Historically, the iconicity of these images has featured a causal traceback to actual light rays in a particular time and space, which were fixed by chemical reactions or digital sensors to the resultant image. Today, photorealistic audiovisual media can be generated from deep learning networks which sever any connection to an actual event. Should society instantiate new regimes to manage this new challenge to our sense of reality and the traditional evidential capacities of the 'mechanical image?' How do these images generate information disorder while also providing the basis for legitimate tools used in entertainment and creative industries? Scholars and students from many backgrounds, as well as policy makers, journalists and the general reading public will find a multidisciplinary approach to questions of privacy and encryption encompassing research from Communication, International Studies, Writing and Rhetoric"-- Provided by publisher.

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