Today, the events {#blank#}1{#/blank#} in realistic-looking or-sounding video and audio recordings need never have happened. They can instead be {#blank#}2{#/blank#} automatically, by powerful computers and machine-learning software. The catch-all term for these computational productions is "deepfakes".

    The term first appeared on Reddit, a messaging board, as the username for an account which was producing {#blank#}3{#/blank#} videos. An entire community {#blank#}4{#/blank#} up around the creation of these videos, writing software tools that let anyone automatically {#blank#}5{#/blank#} 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 {#blank#}6{#/blank#} and actors.

    Tools for editing media {#blank#}7{#/blank#} have existed for decades—think Photoshop. The power and peril of deepfakes is that they make fakery cheaper than ever before. Before deepfakes, a powerful computer and a good chunk of a university degree were needed to produce a realistic fake video of someone. Now some photos and an Internet connection are all that is required.

    The consequences of cheap, widespread fakery are likely to be {#blank#}8{#/blank#}, 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 {#blank#}9{#/blank#} 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. In a world that was already saturated with {#blank#}10{#/blank#} imagery, deepfakes make it plausible to push that even further.