How Real Are Deepfakes?

Pages2-3
Date01 July 2023
AuthorJohn M. McNichols
Subject MatterCivil Law
Published in Litigation News Volume 48, Number 4, Summer 2 023. © 2023 by the Amer ican Bar Association . Reproduced with pe rmission. All rights re served. This info rmation or any porti on thereof may not be c opied or disseminated in an y
form or by any means or sto red in an electronic da tabase or retrieval sy stem without the ex press writt en consent of the Amer ican Bar Associatio n.
By John M. McNichols, L itigation News Associat e Editor
How Real Are Deepfakes?
nological development has led to an array of legal reactions
at both federal and state levels, as well as calls to update the
Federal Rules of Evidence.
What Is a Deepfa ke?
Deepfakes are computer-generated video les that appear to
show a subject person saying or doing particular things that
he or she did not do. Although the subject of the video may
be entirely synthetic—i.e., a made-up person—the more well-
known use of deepfakes is the depiction of real persons in
unreal events and situations. Deepfakes differ from earlier
generations of manipulated photo and video les in that they
are enabled by a form of articial intelligence (AI) known as
“machine learning.”
Using existing video of a particular subject as training
data—say, clips of Tom Cruise from Mission: Impossible—a
computer can be taught to recognize the movements of the
subject’s face and then replicate those movements in an arti-
cial video le that appears to show the subject speaking. The
extraordinary realism of deepfakes stems from the use of a
second computer that, armed with genuine video footage of
the same subject, compares the articial le against the genuine
item attempting to identify any aws that reveal its counterfeit
nature. Over thousands or even millions of iterative rene-
ments, these two “adversarial networks” ultimately generate a
faked le that cannot be distinguished from the genuine item.
Although deepfakes were recently the exclusive domain of
© Getty Image s
Grand Moff Tarkin, the Death Star commander
who destroyed the peaceful planet Alderaan
in 1977’s Star Wars, played perhaps the most
intimidating villain of the movie, setting aside
Darth Vader himself. Fans unsurprisingly called
for his return in the later prequels depicting pre–Death Star
events, and a full 39 years after his debut, the Grand Moff
returned to the franchise in 2016’s Rogue One. For the sake
of franchise continuity, he was portrayed by the same actor,
the accomplished British thespian Peter Cushing. The strange
thing, though, was that Cushing had died in 1994, 22 years
before Rogue One’s release, and thus, all of his “acting” in the
prequel was computer-generated.
A year later, the technology used to resurrect Cushing
received a new name when a Reddit user gained popularity
by creating videos that falsely appeared to show mainstream
celebrities acting in pornographic scenes. His handle: “deep-
fakes.” Unlike the producers of Rogue One, who obtained
consent from Cushing’s family to use his likeness, “deep-
fakes” made no pretense of consent, exposing the technology’s
potential for nefarious uses. Since then, deepfake imagery has
become increasingly difcult to detect, and its potential for
abuse has extended well beyond celebrity parody.
In March 2022, for example, a deepfake circulating on
social media appeared to show Ukrainian President Volodymyr
Zelensky telling Ukrainian soldiers to surrender. The desire
to curb such potential abuses without inhibiting further tech-
SUMMER 2 023 • VOL. 48 NO. 4
2 | A BA LITIGATION SECTION
TECHNOLOGY

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