Facial recognition technology has advanced swiftly in the last five years. As University of Texas at Dallas researchers try to determine how computers have gotten as good as people at the task, they are also shedding light on how the human brain sorts information. UT Dallas scientists have analyzed the performance of the latest echelon of facial recognition algorithms, revealing the surprising way these programs -- which are based on machine learning -- work. Their study, published online Nov. 12 in Nature Machine Intelligence, shows that these sophisticated computer programs -- called deep convolutional neural networks (DCNNs) -- figured out how to identify faces differently than the researchers expected. "For the last 30 years, people have presumed that computer-based visual systems get rid of all the image-specific information -- angle, lighting, expression and so on," said Dr. Alice O'Toole, senior author of the study and the Aage and Margareta Møller Professor in the School of Behavioral and Brain Sciences.
Everything we know about the face recognition systems the FBI and police use suggests the software has a built-in racial bias. That isn't on purpose--it's an artifact of how the systems are designed, and the data they are trained on. Law enforcement agencies are relying more and more on such tools to aid in criminal investigations, increasing the risk that something could go wrong. Law enforcement agencies haven't provided many details on how they use facial recognition systems, but in June the Government Accountability Office issued a report saying that the FBI has not properly tested the accuracy of its face matching system, nor that of the massive network of state-level face matching databases it can access. And while state-of-the-art face matching systems can be nearly 95 percent accurate on mugshot databases, those photos are taken under controlled conditions with generally coöperative subjects.
More than 100 UK millionaires have been identified as tax dodgers after hiding their wealth using offshore schemes. Documents in the Paradise Papers leak show the identities of taxpayers who moved assets worth tens of millions of pounds into companies in Mauritius. The tax avoidance schemes involve them claiming to no longer own property, cash and investments in order to keep their fortunes out of reach of HMRC. It appears many of them use the companies like personal bank accounts. This allows them to continue to enjoy the benefit of their hidden riches.
On John Bailey's first day as the new president of the Academy of Motion Picture Arts and Sciences, Reebok president Matt O'Toole wrote him an open letter, shared via Twitter. The message was not a congratulatory note from one head honcho to another, but instead a passionate proposal for creating a new Academy Award to honor the unsung heroes behind the silver screen: fitness trainers. Mr. Bailey: Let's celebrate the work that takes place BEFORE the cameras roll w/ a new award: Best Fitness Trainer. Noting that Oscars have long been given for Best Makeup and Hairstyling as well as Best Sound Mixing, O'Toole makes a provocative argument for celebrating "the craft of fitness" through the individuals who guide actors into "fighting, flying and filming shape." They've crafted their expertise on the playing field, in their garage gyms and even defending our country," O'Toole said.