Facebook's new plan to integrate WhatsApp, Instagram and Facebook Messenger will lead to more data about users being shared between them, a new report warns. The effort to make it easier for people to participate in conversations across its various messaging platforms sounds harmless, but it raises issues about how data will be shared across the platforms, and with third parties. The good news is that the apps will all be required to use end-to-end encryption. MIT Technology Review reports: Facebook says it wants to make it easier for people to communicate across its "ecosystem" of apps. But the real driver here is a commercial one. By making it easier to swap messages, Facebook can mine even more data to target ads with, and come up with more money-spinning services. There's another potential benefit: by integrating its messaging apps more tightly, Facebook can argue it would be harder to spin one or more of them off, as some antitrust campaigners think it should be forced to do.

An anonymous reader quotes a report from The New York Times: Over the last two years, Amazon has aggressively marketed its facial recognition technology to police departments and federal agencies as a service to help law enforcement identify suspects more quickly. Now a new study from researchers at the M.I.T. Media Lab has found that Amazon's system, Rekognition, had much more difficulty in telling the gender of female faces and of darker-skinned faces in photos than similar services from IBM and Microsoft. The results raise questions about potential bias that could hamper Amazon's drive to popularize the technology.

In the study, published Thursday, Rekognition made no errors in recognizing the gender of lighter-skinned men. But it misclassified women as men 19 percent of the time, the researchers said, and mistook darker-skinned women for men 31 percent of the time. Microsoft's technology mistook darker-skinned women for men just 1.5 percent of the time. For the latest study, [co-author of the study, Ms. Buolamwini, said] she sent a letter with some preliminary results to Amazon seven months ago. But she said that she hadn't heard back from Amazon, and that when she and a co-author retested the company's product a couple of months later, it had not improved. "It's not possible to draw a conclusion on the accuracy of facial recognition for any use case -- including law enforcement -- based on results obtained using facial analysis," Matt Wood, general manager of AI at Amazon Web Services, said. He added that the researchers had not tested the latest version of Rekognition, which was updated in November.

"Amazon said that in recent internal tests using an updated version of its service, the company found no difference in accuracy in classifying gender across all ethnicities," the NYT reports. The new study is scheduled to be presented Monday at an artificial intelligence and ethics conference in Honolulu.

Wave723 writes: To make its developers' jobs more rewarding, Facebook is now using two automated tools called Sapienz and SapFix to find and repair low-level bugs in its mobile apps. Sapienz runs the apps through many tests to figure out which actions will cause it to crash. Then, SapFix recommends a fix to developers, who review it and decide whether to accept the fix, come up with their own, or ignore the problem.