This provocation summarizes recent advances in machine learning and artificial intelligence (AI) as they relate to the emergence of “deepfakes”—manufactured videos of people saying and doing things they never did. Although audio/visual fakes online are nothing new, recent technological and software advances have enabled cheap, fast generation of practically undetectable video fakery by consumer-level users. The provocation traces the appearance and evolution of deepfakes over the winter of 2017–18 from their beginnings as a stunt on amateur porn-sharing sites to their spread to other digital-media exchange venues. In concert with a range of tech scholars and critics, it lays out some of the more troubling paradigm shifts that deepfakes represent in terms of both AI development and post-digital media circulation. It calls for performance scholars generally (and not merely those who focus on digital/online media) to attend to how deepfakes and the ever-advancing technology underlying them are transforming assumptions of seeing, representing, verifying, and performing online and beyond.


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pp. 455-471
Launched on MUSE
Open Access
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