FAKE VIDEOS AND DISINFORMATION BEFORE THE IA: DEEPFAKE AS A POST-TRUTH VEHICLE
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Abstract
Introduction: The use of Artificial Intelligence in the generation of audiovisual content and narratives, although it represents an opportunity in many fields such as art or visual and graphic creation, also becomes a powerful tool to generate false stories and representations. Methodology: The Exploratory Systematic Review (ESR) is applied, providing references that show with empirical evidence the image of post-truth. Results: A critical review of the latest studies and trends in image creation through artificial intelligence related to disinformation is provided. This is part of the contemporary audiovisual ecosystem, threatening citizens' trust in the media, social or institutional environment. Discussion: Users, through social networks, generate false or distorted images, which once viralized are again reinterpreted by other users. Fake videos can ruin both an individual's reputation and trust in social actors. These effects could be moderated by visual and digital literacy. Conclusions: The deep learning of artificial neural networks generates new forms of deepfake, disconcerting for their realism and verisimilitude, and which begin to question the media, delegitimizing the representation of reality and truthful information as the basis of a democratic society.
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