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Deepfake Doctored Videos Of Politicians, Celebrities Could Soon Be Indistinguishable From The Factual

Technology needed to doctor images and videos is advancing rapidly and getting easier to use, experts have warned.

Government agencies and academics are racing to combat so-called deepfakes, amid the spreading threat that they impose on societies.

Advances in artificial intelligence could soon make creating convincing fake audio and video relatively easy, which the Pentagon fears will be used to sow discord ahead of next year’s US presidential election.

Deepfakes combine and superimpose existing images and videos onto source images or videos using a machine learning technique known as generative adversarial network.

They are used to produce or alter video content so that it presents something that didn’t, in fact, occur.

They began in porn – there is a thriving online market for celebrity faces superimposed on porn actors’ bodies – but so-called revenge porn – the malicious sharing of explicit photos or videos of a person- is also a massive problem.

The video that kicked off the concern last month was a doctored video of Nancy Pelosi, the speaker of the US House of Representatives.

It had simply been slowed down to about 75 per cent to make her appear drunk, or slurring her words.

The footage was shared millions of times across every platform, including by Rudi Giuliani – Donald Trump’s lawyer and the former mayor of New York.

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HOW DOES DEEPNUDE WORK?

It is a downloadable offline app which works on Windows and Linux.

It is believed the software is based on pix2pix, an open-source algorithm developed by University of California, Berkeley researchers in 2017.

Pix2pix uses generative adversarial networks (GANs), which work by training an algorithm on a huge dataset of images.

A picture is inputted to the software and a nude version is then generated at the touch of a button.

The danger is that making a person appear to say or do something they did not has the potential to take the war of disinformation to a whole new level.

The threat is spreading, as smartphones have made cameras ubiquitous and social media has turned individuals into broadcasters.

This leaves companies that run those platforms, and governments, unsure on how to tackle the issue.

‘While synthetically generated videos are still easily detectable by most humans, that window is closing rapidly said Jeffrey McGregor, chief executive officer of Truepic, a San Diego-based startup that is developing image-verification technology told the Wall Street Journal.

‘I’d predict we see visually undetectable deepfakes in less than 12 months,’ said Jeffrey McGregor, chief executive officer of Truepic, a San Diego-based startup that is developing image-verification technology.’

The danger is that making a person appear to say or do something they did not has the potential to take the war of disinformation to a whole new level.

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The threat is spreading, as smartphones have made cameras ubiquitous and social media has turned individuals into broadcasters.

This leaves companies that run those platforms, and governments, unsure on how to tackle the issue.

‘While synthetically generated videos are still easily detectable by most humans, that window is closing rapidly said Jeffrey McGregor, chief executive officer of Truepic, a San Diego-based startup that is developing image-verification technology told the Wall Street Journal.

‘I’d predict we see visually undetectable deepfakes in less than 12 months,’ said Jeffrey McGregor, chief executive officer of Truepic, a San Diego-based startup that is developing image-verification technology.’

Source: Dailymail

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