Directions: Fill in
each blank with a proper word chosen from the box. Each word can be used only
once. Note that there is one word more than you need.
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A.
massively B. potential C. figures D. fake E. manually F. sprang
G. captured H. paste I. extreme J. generated K. profound
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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.
