Deepfakes and image manipulation: criminalisation and control
Tyrone Kirchengast
Abstract
Deepfakes are a form of human image synthesis where an existing picture or image is superimposed into a video to change the identity of those depicted in the video. The technology relies on machine learning or artificial intelligence to map an existing image, usually a photo of a person's face, to transfer that image to an existing video image. The technology emerged into the latter part of 2017, and has since given rise to apps and other programmes that allow users to create their own deepfakes. We already use filters and emojis to alter images by consent, however, deepfakes are particularly problematic because they allow for production of videos that are highly convincing, taken to be a real video of the person depicted. Deepfakes provide for the manipulation of all manner of video, but particular risks include videos produced to incite political deception, voter manipulation, commercial fraud, and ‘revenge porn’. The production of deepfake ‘revenge porn’ presents as especially insidious given the ability to transfer the face of any person onto an already existing pornographic video. Harm is exacerbated where that video is then disseminated, via the internet or by social media.