In a world already saturated with extreme imagery, deepfakes make seeking the truth ever more difficult
SUSAN SONTAG understood that photographs are unreliable narrators. “Despite the presumption of veracity that gives all photographs authority, interest, seductiveness,” she wrote, “the work that photographers do is no generic exception to the usually shady commerce between art and truth.” But what if even that presumption of veracity disappeared? Today, the events captured in realistic-looking or -sounding video and audio recordings need never have happened.
The term first appeared on Reddit, a messaging board, as the username for an account which was producing fake videos of female celebrities having sex. An entire community sprung up around the creation of these videos, writing software tools that let anyone automatically paste one person’s face onto the body of another. Reddit shut the community down, but the technology was out there. Soon it was being applied to political figures and actors.
The production of a deepfake about, say, Barack Obama, starts with lots of pictures of the former president . These photos are fed into a piece of software known as a neural network, which makes statistical connections between the visual appearance of Mr Obama and whatever aspect of him you wish to fake.
To make the imagery more realistic, you can have the software compete with a copy of itself, one version generating imagery, and the other trying to spot fakes. This technique, known as a generative adversarial networks , is the purest form of deepfake, conjuring up images that are entirely unique, not just using machine learning to mash existing photos together.
The consequences of cheap, widespread fakery are likely to be profound, albeit slow to unfold. Plenty worry about the possible impact that believable, fake footage of politicians might have on civil society—from a further loss of trust in media to the potential for electoral distortions. These technologies could also be deployed against softer targets: it might be used, for instance, to bully classmates by creating imagery of them in embarrassing situations.
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