There’s nothing new about fears of technological unemployment. The idea goes back to the Luddites in 18th-century England and John Maynard Keynes in the 1930s. Union bosses have long railed against factory automation, and governments have even resisted technology to maintain higher job levels. Yet predictions that machines would put humans out of work on a significant societal scale have never quite materialized.

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Write sports articles: Computers can now write sentences like, “Things looked bleak for the Angels when they trailed by two runs in the ninth inning, but Los Angeles recovered thanks to a key single from Vladimir Guerrero to pull out a 7-6 victory over the Boston Red Sox at Fenway Park on Sunday.” Which sounds a lot like a newspaper account of a baseball game written by a non-robot. Momentum Machines Flickr user Steve Jurvetson Flip burgers: A company called Momentum Machines is developing a machine that shapes burgers from ground meat, grills them, then toasts a bun and adds chopped tomatoes, onions and pickles. Co-founder says Alexandros Vardakostas says the device isn’t meant to make workers’ lives easier. “It’s meant to completely obviate them.” Perform complex office tasks: WorkFusion makes software that automatically assesses a project to see what parts can be fully automated, which parts can be crowdsourced to a freelance network like Elance, and what still needs to be handled by humans. All the while, it analyzes performance, for instance by asking freelancers questions it already knows the answers to, so that it can test their capabilities. The platform reduces the need for in-house staff by making use of freelancers, but then it looks to do away with them as well. “Even as the freelancers work under the direction of the system, they are simultaneously generating the training data that will gradually lead to their replacement,” Ford writes. London Symphony Orchestra Flickr user MITO SettembreMusica Write music: In 2012, the London Symphony Orchestra performed Transits–Into an Abyss, a composition created entirely by Iamus, a system designed at the University of Malaga. One reviewer called it “artistic and delightful.” Replace Wall Street: At the turn of the century, Wall Street employed 150,000 people. Today, that number is less than 100,000, even though transaction volumes and profits have continued to grow. Trading algorithms are now making many of the financial decisions that used to be made by humans. Diagnose cancer: The BD FocalPoint GS Imaging System scans slides for more than 100 signs of disease. And, according to Ford, it does a “significantly better job” of finding cancers than humans do (though doctors do still make the final decision–for now).

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Flickr user Kārlis Dambrāns Ford thinks some of the biggest disruptions will take place in industries that are currently bloated and expensive for consumers–industries like higher education and health care. For instance, he forecasts that MOOCs (online courses), automated grading algorithms (which mark essays as well as multiple choice tests) and adaptive learning systems offer a path away from unsustainable college costs. But, again, these technologies may be bad for employment rates in the sector. Of course, those people doing the automating may stand to do well financially–but perhaps not for long. Ultimately, Ford argues, complete automation will be bad for the economy because machines don’t consume goods and services the way human beings do. The “powerful symbiosis between rising incomes and robust, broad-based consumer demand is now in the process of unwinding,” he says. “It’s possible that at some future point, rapid technological innovations might shift the expectations of consumers about the likelihood and duration of unemployment, causing them to aggressively cut their spending,” he adds. “If such an event occurred, it’s easy to see how that could precipitate a downward economic spiral that would impact even those workers whose jobs are not directly susceptible.” The standard response to automation among economists has been to call for more education, so low-paid workers can move up the food chain. But Ford doesn’t think that will help ultimately. Many people are already over-educated for what they do–just look at all the college graduates serving coffee in Starbucks. Ford says cramming everyone into jobs requiring more skills is “analogous to believing that, in the wake of the mechanization of agriculture, the majority of displaced farm workers would be able to find jobs driving tractors.” Nor, can we hope to stop the automation wave, he says. There’s an inevitability to these technologies, and it’s inevitable that businesses will take advantage. Whatever employers might say publicly, they don’t really want to hire more people than they need. This leads Ford to make the case for a basic income guarantee–a government payment to all citizens so they can live to a reasonable level. His version would be tied to educational accomplishment. People who get at least a high school diploma would get slightly more money, on the thinking that not having at least a diploma in the future economy will make people even less employable than they are today. He suggests $10,000 per person (which is lower than many other proposals), which would cost about $1 trillion overall, provided the payment was means-tested at the top-end.

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This might become an economic necessity, he says, if work is no longer an option for large numbers of people. “If we look into the future and assume that machines will eventually replace human labor to a substantial degree, then I think some form of direct redistribution of purchasing power becomes essential if economic growth is to continue.”