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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

"But the answer to how he was chosen is actually an algorithm, a computer program that crunched through reams of data, looking at how much each passenger had paid for their ticket, what time they checked in, how often they flew on United, and whether they were part of a rewards program. The algorithm likely determined that Dr. Dao was one of the least valuable customers on the flight at the time."

""No-limit Texas Hold'em is a game of incomplete information where the AI must infer a human player's intentions and then act in ways that incorporate both the direct odds of winning and bluffing behaviour to try to fool the other player." The designers said their computer didn't "bluff" the human players. But by learning from its mistakes and practising its moves at night between games, the AI was working out how to defeat its human opponents."

"Generally, it questions the advance of computing in the absence of a deeper knowledge of how the human brain perceives the world to be computed. We want computers to have perception, yet we know little about the workings of our own human perception."

"From a computer science perspective, learning the behaviour of a single user is tough. This is the small data problem; unlike big data, where patterns and trends easily emerge, individual human beings can be unpredictable and can change behaviour, which is not helpful for pattern-hunting algorithms."

"It might not sound like much, but the success of the Minwa supercomputer, which can sort a million images into a thousand predefined categories with an error rate less than the typical human, makes it the latest secret weapon of the company known as "China's Google", Baidu."