AI could generate faces that match the expressions of anonymous subjects to grant them privacy—without losing their ability to express themselves....

The news: A new technique uses generative adversarial networks (GANs), the technology behind deepfakes, to anonymize someone in a photo or video.

How it works: The algorithm extracts information about the person’s facial expression by finding the position of the eyes, ears, shoulders, and nose. It then uses a GAN, trained on a database of 1.5 million face images, to create an entirely new face with the same expression and blends it into the original photo, retaining the same background.

Glitch: Developed by researchers at the Norwegian University of Science and Technology, the technique is still highly experimental. It works on many types of photos and faces, but still trips up when the face is partially occluded or turned at particular angles. The technique is also very glitchy for video.

Other work: This isn’t the first AI-based face anonymization technique. A paper in February from researchers at the University of Albany used deep learning to transplant key elements of a subject’s facial expressions onto someone else. That method required a consenting donor to offer his or her face as the new canvas for the expressions.

Why it matters: Face anonymization is used to protect the identity of someone, such as a whistleblower, in photos and footage. But traditional techniques, such as blurring and pixelation, run the risk of being incomplete (i.e., the person’s identity can be discovered anyway) or completely stripping away the person’s personality (i.e., by removing facial expressions). Because GANs don’t use the subject’s original face at all, they eliminate any risk of the former problem. They can also re-create facial expressions in high resolution, thus offering a solution to the latter.

Not always the bad guy: The technique also demonstrates a new value proposition for GANs, which have developed a bad reputation for lowering the barrier to producing persuasive misinformation. While this study was limited to visual media, by extension it shows how GANs could also be applied to audio to anonymize voices.

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France and Germany have formed a united front against Libra, Facebook’s proposed digital currency....

The news: In a joint statement issued late last week after a meeting of eurozone finance ministers, France and Germany said that Facebook’s plan for Libra “fails to convince” them that risks related to security, investor protection, money laundering and terrorist financing, and “monetary sovereignty” will be adequately dealt with. “We believe that no private entity can claim monetary power, which is inherent to the sovereignty of nations,” the statement reads.

Backlash at home and abroad: Facebook’s bold plan to issue global digital currency next year has been met with significant skepticism and resistance from policymakers in the US, including the president. Facebook has responded by bolstering its lobbying forces in Washington, DC. This joint statement suggests that the political challenges Libra faces in Europe could be more serious.

A wake-up call: The joint statement from France and Germany concludes, “We encourage European central banks to accelerate work on issues around possible public digital currency solutions.” What is this referring to? Apparently, the European Central Bank has been quietly working on its own digital currency project. 

Now Facebook seems to have inspired the bank to pick up the pace. At a news conference after the meeting of finance ministers, ECB board member Benoit Coeure called Libra a “wake-up call.” He said it would fuel efforts to expand access to real-time payment capability in Europe. “We also need to step up our thinking on a central bank digital currency,” Coeure said.

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