Artificial intelligence

Graphic ‘deepfake’ porn videos are being weaponised to humiliate women – and everybody is a potential target

  • Disturbingly realistic fakes have been made with the faces of both celebrities and women who don’t live in the spotlight
  • Many of the deepfake tools, built on Google’s artificial-intelligence library, are publicly available and free to use
PUBLISHED : Monday, 31 December, 2018, 12:49pm
UPDATED : Tuesday, 01 January, 2019, 1:04am

The video showed the woman in a pink off-the-shoulder top, sitting on a bed, smiling a convincing smile.

It was her face. But it had been seamlessly grafted, without her knowledge or consent, onto someone else’s body: a young porn actress, just beginning to disrobe for the start of a graphic sex scene. A crowd of unknown users had been passing it around online.

She felt nauseous and mortified: what if her colleagues saw it? Her family, her friends? Would it change how they thought of her? Would they believe it was a fake?

“I feel violated – this icky kind of violation,” said the woman, who is in her 40s and spoke on the condition of anonymity because she worried that the video could hurt her marriage or career.

“It’s this weird feeling, like you want to tear everything off the internet. But you know you can’t.”

Airbrushing and Photoshop long ago opened photos to easy manipulation. Now, videos are becoming just as vulnerable to fakes that look deceptively real.

Supercharged by powerful and widely available artificial-intelligence software developed by Google, these lifelike “deepfake” videos have quickly multiplied across the internet, blurring the line between truth and lie.

But the videos have also been weaponised disproportionately against women, representing a new and degrading means of humiliation, harassment and abuse.

The fakes are explicitly detailed, posted on popular porn sites and increasingly challenging to detect.

Disturbingly realistic fakes have been made with the faces of both celebrities and women who don’t live in the spotlight, and the actress Scarlett Johansson says she worries that “it’s just a matter of time before any one person is targeted” by a lurid forgery.

Johansson has been superimposed into dozens of graphic sex scenes over the past year that have circulated across the web: one video, falsely described as real “leaked” footage, has been watched on a major porn site more than 1.5 million times.

“Nothing can stop someone from cutting and pasting my image or anyone else’s onto a different body and making it look as eerily realistic as desired,” she said.

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“The fact is that trying to protect yourself from the internet and its depravity is basically a lost cause. … The internet is a vast wormhole of darkness that eats itself.”

In September, Google added “involuntary synthetic pornographic imagery” to its ban list, allowing anyone to request the search engine block results that falsely depict them as “nude or in a sexually explicit situation.”

But there’s no easy fix to their creation and spread.

A growing number of deepfakes target women far from the public eye, with anonymous users on deepfakes discussion boards and private chats calling them colleagues, classmates and friends. Several users who make videos by request said there’s even a going rate: about US$20 per fake.

Videos have for decades served as a benchmark for authenticity, offering a clear distinction from photos that could be easily distorted.

Fake video, for everyone except high-level artists and film studios, has always been too technically complicated to get right.

But recent breakthroughs in machine-learning technology, employed by creators racing to refine and perfect their fakes, have made fake-video creation more accessible than ever.

All that’s needed to make a persuasive mimicry within a matter of hours is a computer and a robust collection of photos, such as those posted by the millions onto social media every day.

The result is a fearsome new way for faceless strangers to inflict embarrassment, distress or shame.

“If you were the worst misogynist in the world,” said Mary Anne Franks, a University of Miami law professor and the president of the Cyber Civil Rights Initiative, “this technology would allow you to accomplish whatever you wanted.”

Men are inserted into the videos almost entirely as a joke: a popular imitation shows the actor Nicolas Cage’s face superimposed onto US President Donald Trump’s.

But the fake videos of women are predominantly pornographic, exposing how the sexual objectification of women is being emboldened by the same style of AI technology that could underpin the future of the web.

The media critic Anita Sarkeesian, who has been assailed online for her feminist critiques of pop culture and video games, was inserted into a hard core porn video this year that has been viewed more than 30,000 times on the adult-video site Pornhub.

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“For folks who don’t have a high profile, or don’t have any profile at all, this can hurt your job prospects, your interpersonal relationships, your reputation, your mental health,” Sarkeesian said. “It’s used as a weapon to silence women, degrade women, show power over women, reducing us to sex objects. This isn’t just a fun-and-games thing. This can destroy lives.”

The AI approach that spawned deepfakes began with a simple idea: two opposing groups of deep-learning algorithms create, refine and recreate an increasingly sophisticated result.

A team led by Ian Goodfellow, now a research scientist at Google, introduced the idea in 2014 by comparing it to the duel between counterfeiters and the police, with both sides driven “to improve their methods until the counterfeits are indistinguishable”.

The system automated the tedious and time-consuming drudgery of making a photorealistic face-swapping video: finding matching facial expressions, replacing them seamlessly and repeating the task 60 times a second.

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Many of the deepfake tools, built on Google’s artificial-intelligence library, are publicly available and free to use.

Last year, an anonymous creator using the online name “deepfakes” began using the software to create and publish face-swapped porn videos of actresses such as Gal Gadot onto the discussion-board giant Reddit, winning widespread attention and inspiring a wave of copycats.

The videos range widely in quality, and many are glitchy or obvious cons.

But deepfake creators say the technology is improving rapidly and see no limit to whom they can impersonate.

Not all fake videos targeting women rely on pornography for shock value or political points. This spring, a doctored video showed the Parkland school shooting survivor Emma Gonzalez ripping up the US Constitution.

Conservative activists shared the video as supposed proof of her un-American treachery; in reality, the video showed her ripping up paper targets from a shooting range.

But deepfakes’ use in porn has skyrocketed. One creator on the discussion board 8chan made an explicit four-minute deepfake featuring the face of a young German blogger who posts videos about make-up; thousands of images of her face had been extracted from a hair tutorial she had recorded in 2014.

Reddit and Pornhub banned the videos this year, but new alternatives quickly bloomed to replace them. Major online discussion boards such as 8chan and Voat, whose representatives didn’t respond to requests for comment, operate their own deepfake forums, but the videos can also be found on stand-alone sites devoted to their spread.

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The creator of one deepfakes site said his 10-month-old site received more than 20,000 unique viewers every day and relied on advertising to make a modest profit.

Celebrities are among the biggest draws for traffic, he said, adding that he believes their fame – and the wealth of available public imagery – has effectively made them fair game.

The victims of deepfakes have few tools to fight back. Legal experts in the United States say deepfakes are often too untraceable to investigate and exist in a legal grey area: built on public photos, they are effectively new creations, meaning they could be protected as free speech.

Defenders are pursuing untested legal manoeuvres to crack down on what they’re calling “nonconsensual pornography”, using similar strategies employed against online harassment, cyberstalking and revenge porn.

Lawyers said they could employ harassment or defamation laws, or file restraining orders or takedown notices in cases where they knew enough about the deepfake creators’ identity or tactics.

Google representatives said that the company took its ethical responsibility seriously, but that restrictions on its AI tools could end up limiting developers pushing the technology in a positive way.

But Hany Farid, a Dartmouth College computer-science professor who specialises in examining manipulated photos and videos, said Google and other tech giants needed “to get more serious about how weaponised this technology can be”.

“If a biologist said: ‘Here’s a really cool virus; let’s see what happens when the public gets their hands on it’, that would not be acceptable. And yet it’s what Silicon Valley does all the time,” he said.

“It’s indicative of a very immature industry. We have to understand the harm and slow down on how we deploy technology like this.”