A.I. is already better than human doctors at diagnosing skin and breast cancer. A.I. is beginning to revolutionize medicine, and allowing us to see into the future of our bodies...but can we ever know too much about ourselves? What will happen when machine learning lets us open our own black boxes?

Facebook took down more than 600 accounts tied to the pro-Trump conspiracy website The Epoch Times for using identities created by artificial intelligence to push stories about a variety of topics including impeachment and elections. The network was called "The BL" and was run by Vietnamese users posing as Americans, using fake photos generated by algorithms to simulate real identities. The Epoch Media group, which pushes a variety of pro-Trump conspiracy theories, spent $9.5 million on ads to spread content through the now-suspended pages and groups. "What's new here is that this is purportedly a U.S.-based media company leveraging foreign actors posing as Americans to push political content. We've seen it a lot with state actors in the past," Facebook's head of security policy, Nathaniel Gleiche, said in an interview.

AI is set out to kill most of the remaining newsroom jobs. But it can never replace how Errol Morris, Bob Woodward, or Michael Barbaro construct long-form affective narratives -- which is the future of journalism.

Samuel Greengard is an author and journalist based in West Linn, OR, USA.

The Epoch Media Group denied in an email sent to The New York Times that it was linked to the network targeted by Facebook, and said that Facebook had not contacted the company before publishing its conclusions. The people behind the network used artificial intelligence to generate profile pictures, Facebook said. They relied on a type of artificial intelligence called generative adversarial networks. These networks can, through a process called machine learning, teach themselves to create realistic images of faces, even though they do not belong to a real person. Nathaniel Gleicher, Facebook's head of security policy, said in an interview that "using A.I.-generated photos for profiles" has been talked about for several months, but for Facebook, this is "the first time we've seen a systemic use of this by actors or a group of actors to make accounts look more authentic."

The era of disinformation driven by artificial intelligence is here. For years, pundits have warned that the dawn of smarter software in the form of artificial intelligence would make it easier. Propaganda campaigns driven entirely by robotic trolls are still a long ways off but researchers at the disinformation-tracking firm found that a far-right media group used AI-generated profile pictures to build up a network of fake Facebook users and pages found in one of the largest troll takedowns in Facebook history. On Friday, Facebook pulled down a network of 700 pages with 55 million followers run by The Beauty of Life, a media outlet linked to the Epoch Media Group. Researchers at the disinformation-tracking groups Graphika and the Atlantic Council's Digital Forensic Research Lab found that "dozens" of the fake accounts found in the network taken down by Facebook had avatars that had been generated by AI software as part of a campaign Graphika dubbed Operation Fake Face Swarm.

Deep convolutional neural networks are known to specialize in distilling compact and robust prior from a large amount of data. We are interested in applying deep networks in the absence of training dataset. In this paper, we introduce deep audio prior (DAP) which leverages the structure of a network and the temporal information in a single audio file. Specifically, we demonstrate that a randomly-initialized neural network can be used with carefully designed audio prior to tackle challenging audio problems such as universal blind source separation, interactive audio editing, audio texture synthesis, and audio co-separation. To understand the robustness of the deep audio prior, we construct a benchmark dataset \emph{Universal-150} for universal sound source separation with a diverse set of sources. We show superior audio results than previous work on both qualitative and quantitative evaluations. We also perform thorough ablation study to validate our design choices.