Deepfake

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Deepfakes (a portmanteau of 'deep learning' and 'fake'^[1]) are images, videos, or audio that have been edited or generated using artificial intelligence, AI-based tools or AV editing software. They may depict real or fictional people and are considered a form of synthetic media, that is media that is usually created by artificial intelligence systems by combining various media elements into a new media artifact.^[2][3]

While the act of creating fake content is not new, deepfakes uniquely leverage machine learning and artificial intelligence techniques,^[4][5][6] including facial recognition algorithms and artificial neural networks such as variational autoencoders (VAEs) and generative adversarial networks (GANs).^[5][7] In turn, the field of image forensics develops techniques to detect manipulated images.^[8] Deepfakes have garnered widespread attention for their potential use in creating child sexual abuse material, celebrity pornographic videos, revenge porn, fake news, hoaxes, bullying, and financial fraud.^{[9][10][11][12]}

Academics have raised concerns about the potential for deepfakes to promote disinformation and hate speech, as well as interfere with elections. In response, the information technology industry and governments have proposed recommendations and methods to detect and mitigate their use.

From traditional entertainment to gaming, deepfake technology has evolved to be increasingly convincing^[13] and available to the public, allowing for the disruption of the entertainment and media industries.^[14]