Katie Jones was supposed to be a thirty-something redhead who worked at a leading think tank and had serious connections.

Connections included people with political weight like a deputy assistant secretary of state, to groups ranging from the centrist Brookings Institution to the right-wing Heritage Foundation. It’s the connections not on Miss Jones’ profile, however, that people should be concerned about.

The Associated Press (AP) found the profile was entirely fake and typical of espionage campaigns on the networking site. “It smells a lot like some sort of state-run operation,” said Jonas Parello-Plesner, program director at Denmark-based think tank Alliance of Democracies Foundation.

Parello-Plesner was targeted in an espionage attack over LinkedIn a few years ago, showing it’s not a new phenomenon. However, advancements in AI are making the creation of convincing fake profiles easier than ever.

A closer examination of Jones’ alleged profile pic conducted by AP’s Raphael Satter highlighted there are still some telltale signs of a fake image:

The issue of deepfakes is becoming ever more apparent. Earlier this week, AI News reported Facebook CEO Mark Zuckerberg had become the victim of a deepfake video just a month after the social media site refused to remove a deepfake video of House Speaker Nancy Pelosi.

In the deepfake of Zuckerberg, he is portrayed to say: “Imagine this for a second: One man, with total control of billions of people’s stolen data, all their secrets, their lives, their futures.”

While many people are learning not to believe all they read, it will take some time for people not to trust their eyes. In a world where politicians can be convincingly made to say anything using just a computer, that has major ramifications for society.

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Last month, Facebook refused to remove a deepfake video of House Speaker Nancy Pelosi. Rather than making Pelosi appear to say things she never did, the video aimed to portray her as being intoxicated.

Deepfakes have the potential to spread misinformation and damage the reputation of individuals. Particularly in the world of politics and increasingly sophisticated state disinformation campaigns, it’s easy to imagine the danger they pose.

Pelosi later told California’s KQED: “I think they have proven — by not taking down something they know is false — that they were willing enablers of the Russian interference in our election.”

Governments and activists have called on social networks to assist in the detection and deletion of such videos. Now it seems that campaigners are targeting social network executives with deepfakes in a bid to make them take such videos more seriously.

In the deepfake of Zuckerberg, the Facebook CEO is portrayed to say: “Imagine this for a second: One man, with total control of billions of people’s stolen data, all their secrets, their lives, their futures.”

Fortunately for Zuckerberg, the deepfake is not malicious and most people will know it’s not real. The video both helps to make social networks assist more in tackling deepfakes while also raising public awareness.

Society is going through a period of serious change when it comes to knowing what’s real and fake. Many now question what they read because anyone could have written it and the issue of fake news is well-publicised. Most people, however, are still accustomed to believing that someone is saying what they are when they can see them doing it.

Zuckerberg’s deepfake was created Israeli startup Canny AI. The firm has also debuted fake videos with the likes of President Trump and Kim Kardashian as part of a commissioned art installation called Spectre that was on display at the Sheffield Doc/Fest in the UK.

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The website, WhichFaceIsReal.com, is created by Jevin West of the Information School and Carl Bergstrom of the biology department at the University of Washington.

West and Bergstrom gained some degree of fame after presenting a class titled ‘Calling Bullshit in the Age of Big Data’ back in 2017.

Their website continues along these lines and tasks visitors with, as you probably guessed, picking the real face over the fake (I was quietly confident, but I’d put my success rate around 50 percent).

In a post explaining their website, West and Bergstrom wrote:

“While we’ve learned to distrust user names and text more generally, pictures are different. You can’t synthesize a picture out of nothing, we assume; a picture had to be of someone. Sure a scammer could appropriate someone else’s picture, but doing so is a risky strategy in a world with google reverse search and so forth. So we tend to trust pictures. A business profile with a picture obviously belongs to someone. A match on a dating site may turn out to be 10 pounds heavier or 10 years older than when a picture was taken, but if there’s a picture, the person obviously exists.

No longer. New adverserial machine learning algorithms allow people to rapidly generate synthetic ‘photographs’ of people who have never existed.”

The pair did not develop the technology behind it but wanted to bring attention to a serious problem in a fun way. “Our aim is to make you aware of the ease with which digital identities can be faked, and to help you spot these fakes at a single glance,” they claim.

Software engineers from NVIDIA developed the impressive algorithm for generating realistic faces. You may have already seen it at work on ThisPersonDoesNotExist.com.

The algorithm is trained on a ‘General Adversarial Network’ where two neural networks compete against each other; one creating fake images, the other attempting to spot the difference.

Currently, people are spotting the real person around 70 percent of the time. Some inconsistencies to look out for is the background of the photo and how things such as glasses and hair are rendered.

If attempting to determine whether a pic is real or not that you’ve come across, the duo advise looking for images of the same person from different angles. That, as of writing, is not possible for an AI to do.

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