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"The other day I noticed that the little green light next to the camera built into my computer screen was on. It's perfectly possible that I had recently used some app that required the camera, and forgotten about it; but I couldn't find a way to turn it off. It's unlikely anyone was really watching me pretend to work, but my computer definitely was."

"Facebook and Twitter reported to have been blocked in run-up to protests, with people turning to VPNs to broadcast content"

"Such powerful software is still several years away from being fully developed, if at all, and raises all sorts of ethical questions. But the potential applications-such as masterfully translating foreign languages, identifying objects in photos and directing self-driving cars through busy intersections-are so compelling that technology giants like Facebook and Google Inc. are investing heavily in artificial intelligence"

"The new tools appear to allow Twitter users to share images with text overlays, stickers, and other modifications. Twitter's existing tools merely allow people to crop images or run them through filters that greatly change their appearance, whether it's by upping the contrast or making them look like old Polaroid shots."

Do we think that public is the new social norm, and anonymity is dead?

"Unskilled manual laborers have felt the pressure of automation for a long time - but, increasingly, they're not alone. The last few years have been a bonanza of advances in artificial intelligence. As our software gets smarter, it can tackle harder problems, which means white-collar and pink-collar workers are at risk as well. Here are eight jobs expected to be automated (partially or entirely) in the coming decades. Call Center Employees call-center Telemarketing used to happen in a crowded call center, with a group of representatives cold-calling hundreds of prospects every day. Of those, maybe a few dozen could be persuaded to buy the product in question. Today, the idea is largely the same, but the methods are far more efficient. Many of today's telemarketers are not human. In some cases, as you've probably experienced, there's nothing but a recording on the other end of the line. It may prompt you to "press '1' for more information," but nothing you say has any impact on the call - and, usually, that's clear to you. But in other cases, you may get a sales call and have no idea that you're actually speaking to a computer. Everything you say gets an appropriate response - the voice may even laugh. How is that possible? Well, in some cases, there is a human being on the other side, and they're just pressing buttons on a keyboard to walk you through a pre-recorded but highly interactive marketing pitch. It's a more practical version of those funny soundboards that used to be all the rage for prank calls. Using soundboard-assisted calling - regardless of what it says about the state of human interaction - has the potential to make individual call center employees far more productive: in some cases, a single worker will run two or even three calls at the same time. In the not too distant future, computers will be able to man the phones by themselves. At the intersection of big data, artificial intelligence, and advanced

"Going from small data analytics to Big Data analytics or to predictive and prescriptive analytics is trickier. Expanding in both dimensions is human capital intensive, requiring talented data scientists. A McKinsey report (2011) estimates that by 2018, there will be a shortage of 140,000 to 190,000 workers with "deep analytical" experience and a further 1.5 million data-literate managers in the US. Technology giants such as Google, Facebook and Amazon, and large investment banks and top hedge funds can afford such employees, however even now the competition is fierce, as is evidenced by the ongoing talent war in Silicon Valley. The data scientist is indeed a sexy job in the 21st century."

"FOLLOW US Twitter / Facebook / RSS Machine learning image classifiers use context clues to help understand the contents of a room, for example, if they manage to identify a dining-room table with a high degree of confidence, that can help resolve ambiguity about other objects nearby, identifying them as chairs. The downside of this powerful approach is that it means machine learning classifiers can be confounded by confusing, out-of-context elements in a scene, as is demonstrated in The Elephant in the Room, a paper from a trio of Toronto-based computer science academics."

"Facebook is mired in a series of controversies about the curation of its news feed, from its broadcasting live killings, to editing out an iconic photo of the Vietnam war, to accusations of political bias. It recently tried to smooth the process out by firing its human editors … only to find the news feed degenerated into a mass of fake and controversial news stories."

" The observations made at Facebook are the latest in a long line of similar cases. In each instance, an AI being monitored by humans has diverged from its training in English to develop its own language. The resulting phrases appear to be nonsensical gibberish to humans but contain semantic meaning when interpreted by AI "agents." "

"Yet these blueprints may also alarm free speech advocates concerned about Facebook's de facto role as the world's largest censor. Both sides are likely to demand greater transparency."

"And now, 10 years later, the impact of reckless, subjective and inflammatory misinformation served up on the web is being felt like never before in the digital era."

"When Google's algorithms result in men on the Internet seeing better-paying job advertisements than women, it's worth looking under the hood at the assumptions that the algorithms, and the people behind it, have made. "

"There's just one problem: the liking was fake, done by a team of low-paid workers in Dhaka, Bangladesh, whose boss demanded just $15 per thousand "likes" at his "click farm". Workers punching the keys might be on a three-shift system, and be paid as little as $120 a year."