or has been manipulated,” he says.
“The stakes can be very, very high, and
that’s something we have to worry a
great deal about.”
That is because a growing number
of AI tools are increasing the ability for
fakery to flourish, regardless of how
they are being used. In 2016, Adobe an-
nounced VoCo (voice conversion), es-
sentially a “Photoshop of speech” tool
that lets a user edit recorded speech to
replicate and alter voices.
Face2Face is an AI-powered tool that
can do real-time video reenactment.
The technology lets a user “animate the
facial expressions of the target video by
a source actor and re-render the manipulated output video in a photoreal-istic fashion,” according to its creators
at the University of Erlangen-Nurem-berg, the Max Planck Institute for Informatics, and Stanford University.
When someone moves their mouth
and makes facial expressions, those
movements and expressions will be
tracked and then translated onto
someone else’s face, making it appear
that the target person is making those
On the flip side is software that helps
users take preventative measures
against being duped. One is an AI tool
called Scarlett that was recently intro-
duced by adult dating site Saucy-
Dates, with the goal of reducing fraud
and scams in the dating industry.
Scarlett acts as a virtual assistant and
as people are having live conversa-
tions, it scores users; when the score
reaches a threshold, it is flagged and
was taken, camera settings used, and
While digital forensic techniques
are a promising way to check the au-
thenticity of photos, for now “using
these techniques requires an expert
and can be time-consuming,” Nightin-
gale says. “What’s more, they don’t
100% guarantee that a photo is real or
fake. That said, digital forensic tech-
niques and our work, which is trying to
improve people’s ability to spot fake
images, does at least make it more dif-
ficult for forgers to fool people.”
Farid has developed several tech-
niques for determining whether an
image has been manipulated. One
method looks at whether a JPEG im-
age has been compressed more than
once. Another technique detects im-
age cloning, which is done when try-
ing to remove something from an im-
age, he says. In addition, Schubmehl
cites the development of machine
learning algorithms by researchers at
New York University to spot counter-
The mission of a five-year U.S. De-
fense Advanced Research Projects
Agency (DARPA) program called Medi-
For (media forensics) is to use digital
forensics techniques to build an auto-
mated system that can accurately an-
alyze hundreds of thousands of im-
ages a day, says Farid, who is
participating in the program. “We’re
now in the early days of figuring out
how to scale [the system] so we can do
things quickly and accurately to stop
the spread of viral content that is fake
read by a moderator. To protect the
privacy of the conversation, the moder-
ator can only read the suspected fraud-
ster’s messages, explains David
Minns, founder and CEO of software
developer DM Cubed, which devel-
oped the SaucyDates tool. He adds
the AI tool also warns the potential
victim of fraudulent content.
Farid says we should absolutely be
alarmed by the growth of software that
enables digital media to be manipulated
into fakes for nefarious purposes.
“There’s no question that from the
field of computer vision to computational photography to computer graphics to
software that is commercially available,
we can continue to be able to manipulate digital content in ways that were un-imageable a few years ago,” he says.
“And that trend is not going away.”
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Esther Shein is a freelance technology and business
writer based in the Boston area.
© 2018 ACM 0001-0782/18/3 $15.00
Architecture of a generative adversarial network.