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"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

"Oliver also pointed to a Finnish man who once found "one of the most severe security flaws ever discovered in a voting system" in US machines and alerted their manufacturers, who released a patch to fix the problem in 2006. The state of Georgia, however, never installed it, and the Senate report noted their machines hadn't been updated since at least 2005. "They'd essentially been hitting the 'remind me tomorrow' button on a critical security update for over a decade," Oliver explained, "meaning Georgia's election systems operate on the same level of technical proficiency as Every Dad"."

"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."

"Neural networks can find telltale patterns in a person's gait that can be used to recognize and identify them with almost perfect accuracy, according to new research published in IEEE Transactions on Pattern Analysis and Machine Intelligence. The new system, called SfootBD, is nearly 380 times more accurate than previous methods, and it doesn't require a person to go barefoot in order to work. It's less invasive than other behavioral biometric verification systems, such as retinal scanners or fingerprinting, but its passive nature could make it a bigger privacy concern, since it could be used covertly."

""When you have a fully digital system you have no weapon to defend yourself if someone turns it off," he says. "If Putin invades Gotland [Sweden's largest island] it will be enough for him to turn off the payments system. No other country would even think about taking these sorts of risks, they would demand some sort of analogue system.""

"The system is called as"Intelligent Classroom Behavior Management System" and it is being used at Hangzhou No. 11 High School. With scanning facial expressions the system has the ability to even analysis six types of behaviors by the students such as standing up, reading, writing, hand raising, listening to the teacher, and leaning on the desk."

"The platform's automated tools may have mistaken the visuals of the burning building for 9/11 footage, according to Vagelis Papalexakis, an assistant professor of computer science and engineering at the University of California, Riverside who studies machine learning used in similar systems."

"Customers will be able to use a "Smile to Pay" facial recognition system at the tech-heavy, health-focused concept store, part of a drive by Yum China Holdings Inc to lure a younger generation of consumers. "

""The problem," Leveson wrote in a book, "is that we are attempting to build systems that are beyond our ability to intellectually manage.""

"The unique approach to 'deception detection' analyses the micro-gestures of travellers to figure out if the interviewee is lying."