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Yes, Robots Really Are Going To Take Your Job And End The American Dream

Now that machines can diagnose cancer, trade stocks, and write symphonies, they’re not just going to make humans more efficient as they have in the past—they are replacing them entirely and wrecking the economy along the way.

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.

However, there’s reason to be believe that, unlike those previous times, we really are entering an age when people will work less. As author Martin Ford puts it in his recent book Rise of the Robots, “this time is different.” New artificially intelligent machines, he says, are not so much tools to improve the efficiency of workers but really are tools to replace workers themselves.

This is an important distinction. Economists tend to dismiss robotization as just another form of “creative destruction.” That is, robots may displace some workers for a while before they also create new kinds of jobs, such as a job market for people who can build robots themselves. Ford says that’s a mistake. It’s true that economies go through cycles of boom and bust and that companies rise and fall. But what’s happening now, he argues, is more like the invention of the aircraft. Before Kitty Hawk, humans didn’t fly; afterwards they did.
“The question of whether smart machines will someday eclipse the capability of average people to perform much of the work demanded by the economy will be answered by the nature of the technology that arrives in the future—not by lessons gleaned by economic history,” he writes.

Surveying all the fields now being affected by automation, Ford makes a compelling case that this is an historic disruption—a fundamental shift from most tasks being performed by humans to one where most tasks are done by machines. That includes obvious things like moving boxes around a warehouse, but also many “higher skill” jobs as well, such as radiology and stock trading. And don’t kid yourself about your own importance: that list almost certainly includes your job.

We really could be headed for an economy with many fewer jobs in it and a severely eroded middle class, he argues. Together with other important trends like wealth inequality and globalization, new technology threatens to produce more unemployment and slow the main motor of the U.S. economy—consumer demand.

Here are some things robots can already do:

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.

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.

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