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      Deepfakes and Disinformation: Exploring the Impact of Synthetic Political Video on Deception, Uncertainty, and Trust in News

      1 , 1
      Social Media + Society
      SAGE Publications

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          Abstract

          Artificial Intelligence (AI) now enables the mass creation of what have become known as “deepfakes”: synthetic videos that closely resemble real videos. Integrating theories about the power of visual communication and the role played by uncertainty in undermining trust in public discourse, we explain the likely contribution of deepfakes to online disinformation. Administering novel experimental treatments to a large representative sample of the United Kingdom population allowed us to compare people’s evaluations of deepfakes. We find that people are more likely to feel uncertain than to be misled by deepfakes, but this resulting uncertainty, in turn, reduces trust in news on social media. We conclude that deepfakes may contribute toward generalized indeterminacy and cynicism, further intensifying recent challenges to online civic culture in democratic societies.

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          Most cited references32

          • Record: found
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          Social Desirability Bias in CATI, IVR, and Web Surveys: The Effects of Mode and Question Sensitivity

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            • Record: found
            • Abstract: not found
            • Article: not found

            The Nature and Origins of Misperceptions: Understanding False and Unsupported Beliefs About Politics

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              • Record: found
              • Abstract: not found
              • Article: not found

              How Conditioning on Posttreatment Variables Can Ruin Your Experiment and What to Do about It

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                Author and article information

                Journal
                Social Media + Society
                Social Media + Society
                SAGE Publications
                2056-3051
                2056-3051
                January 2020
                February 19 2020
                January 2020
                : 6
                : 1
                : 205630512090340
                Affiliations
                [1 ]Loughborough University, UK
                Article
                10.1177/2056305120903408
                79d40005-9a81-41f6-9b76-0f93659bff1c
                © 2020

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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