What ‘deepfakes’ are and how they may be dangerous

[Herran]

Anybody who has a computer and access to the internet can technically produce a “deepfake” video, says John Villasenor, professor of electrical engineering at the University of California, Los Angeles.

The technology can be used to make people believe something is real when it is not,” said Peter Singer, cybersecurity and defense focused strategist and senior fellow at New America.

Camera apps have become increasingly sophisticated. Users can elongate legs, remove pimples, add on animal ears and now, some can even create false videos that look very real. The technology used to create such digital content has quickly become accessible to the masses, and they are called “deepfakes.”

Deepfakes refer to manipulated videos, or other digital representations produced by sophisticated artificial intelligence, that yield fabricated images and sounds that appear to be real.

John Villasenor, nonresident senior fellow of governance studies at the Center for Technology Innovation at Washington-based public policy organization, the Brookings Institution. “Deepfakes are raising a set of challenging policy, technology, and legal issues.”

What are deepfakes?

The word deepfake combines the terms “deep learning” and “fake,” and is a form of artificial intelligence.

In simplistic terms, deepfakes are falsified videos made by means of deep learning, said Paul Barrett, adjunct professor of law at New York University.

Deep learning is “a subset of AI,” and refers to arrangements of algorithms that can learn and make intelligent decisions on their own.

But the danger of that is “the technology can be used to make people believe something is real when it is not,” said Peter Singer, cybersecurity and defense-focused strategist and senior fellow at New America think tank.

How do deepfakes work?

A deep-learning system can produce a persuasive counterfeit by studying photographs and videos of a target person from multiple angles, and then mimicking its behavior and speech patterns.

Barrett explained that “once a preliminary fake has been produced, a method known as GANs, or generative adversarial networks, makes it more believable. The GANs process seeks to detect flaws in the forgery, leading to improvements addressing the flaws.”

And after multiple rounds of detection and improvement, the deepfake video is completed, said the professor.

How to detect manipulated videos?

While AI can be used to make deepfakes, it can also be used to detect them, Brookings’ Villasenor wrote in February. With the technology becoming accessible to any computer user, more and more researchers are focusing on deepfake detection and looking for a way of regulating it.

Large corporations such as Facebook and Microsoft have taken initiatives to detect and remove deepfake videos. The two companies announced earlier this year that they will be collaborating with top universities across the U.S. to create a large database of fake videos for research, according to Reuters.

“Presently, there are slight visual aspects that are off if you look closer, anything from the ears or eyes not matching to fuzzy borders of the face or too smooth skin to lighting and shadows,” said Singer from New America.

Read more : https://www.cnbc.com/2019/10/14/what-is-...erous.html