Creating, Using, Misusing, and Detecting Deep Fakes
By Hany Farid. 2022
Synthetic media—so-called deep fakes—have captured the imagination of some and struck fear in others. Although they vary in their form and creation, deep fakes refer to text, image, audio, or video that has been automatically synthesized by a machine-learning system. Deep fakes are the latest in a long line of techniques used to manipulate reality, yet their introduction poses new opportunities and risks due to the democratized access to what would have historically been the purview of Hollywood-style studios. This review describes how synthetic media is created, how it is being used and misused, and if (and how) it can be perceptually and forensically distinguished from reality.
Subfields: Safety, Robustness & Interpretability
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In Safety, Robustness & Interpretability
- Irene Solaiman
- Su Lin Blodgett
- Dylan Baker
- Zeerak Talat
- Marie-Therese Png
- Yacine Jernite
- William Agnew
- Alexandra Sasha Luccioni
Citations in the corpus
- Evaluating the Social Impact of Generative AI Systems in Systems and Society (2023, background): “Mitigation and Interventions Interventions on technical systems include encouraging people to shift their attention to the accuracy of posts they might share [180], using crowd-sourced fact checking [90], and using digital forensics to detect AI-generated content [76].”