yagoda shares a report from MIT Technology Review: Andreas Rossler at the Technical University of Munich in Germany and colleagues have developed a deep-learning system that can automatically spot Face-swap videos. The new technique could help identify forged videos as they are posted to the web. But the work also has sting in the tail. The same deep-learning technique that can spot face-swap videos can also be used to improve the quality of Face Swaps in the first place -- and that could make them harder to detect. The new technique relies on a deep-learning algorithm that Rossler and co have trained to spot face swaps. These algorithms can only learn from huge annotated data sets of good examples, which simply have not existed until now. In semi-related news, the Screen Actors Guild-American Federation of Television and Radio Artists (SAG-AFTRA) says it's "fighting back" against the dangers posed by new face-swapping technologies that have been used to digitally superimpose the faces of its members onto the bodies of porn stars. "SAG-AFTRA has undertaken an exhaustive review of our collective bargaining options and legislative options to combat any and all uses of digital re-creations, not limited to deepfakes, that defame our members and inhibit their ability to protect their images, voices and performances from misappropriation. We are talking with our members' representatives, union allies, and with state and federal legislators about this issue right now and have legislation pending in New York and Louisiana that would address this directly in certain circumstances. We also are analyzing state laws in other jurisdictions, including California, to make sure protections are in place. To the degree that there are not sufficient protections in place, we will work to fix that..."
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