Robot Workers! Machines Could Replace Half Of U.S. Occupations

March 14, 2014  |  

Can machines really replace humans on the job? Yes. According to a new study done at the University of Oxford in the U.K., nearly half of all work in the United States is at risk of being lost to machines.

With new tech advances, such as artificial intelligence that can duplicate human reasoning and mobile robots, it is “likely that occupations employing almost half of today’s U.S. workers, ranging from loan officers to cab drivers and real estate agents, become possible to automate in the next decade or two,” reports Bloomberg.

And we’re not just talking about factory work.

According to Carl Benedikt Frey, co-author of the study and a research fellow at the Oxford Martin Programme on the Impacts of Future Technology, advances in machine learning can make it easier for machines to do the job of humans. Machine learning is a kind of artificial intelligence that makes software “learn” how to make decisions by examining patterns in those humans have made. This evolution means machines can replace jobs from typists to travel agents.

Frey and colleague Michael Osborne looked at 702 U.S. occupations and determined 47 percent of occupations could be automated “perhaps over the next decade or two,” their analysis showed.

Top of the list of jobs at risk was loan officers with a 98 percent probability. One online company called Daric Inc. already uses an algorithm that determines who was a safe borrower in the past as well as who is creditworthy.The company doesn’t have one loan officer.

There is even software that could possibly eliminate lawyers, especially when it comes to researching documents. It took one law firm 600 hours to pour through 1.3 million evidence documents using such software. Without it, it would have taken 13,000 hours if humans had to do the reading.

Smart software is pushing self driving cars into reality, which means taxi drivers and heavy truck drivers could be replaced too.

But machines can’t replace humans in all vocations. They are unable to interact and improvise. “Neither can machines come up with novel and creative solutions or learn from a couple examples the way people can,” reports Bloomberg. Still, workers should broaden their knowledge and move into jobs that demand more cognitively complex tasks, warns Frey. “It’s a race between technology and education,” he says.

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