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Working Papers | May 20, 2020

Robots, Automation, and Employment: Where We Are

Lukas Wolters
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“Robots will destroy our jobs – and we’re not ready for it” titled The Guardian in early 2017. Headlines like this have become more and more common over the past couple of years, with newspapers and media outlets reporting that “the robots are coming! And they are going to take all our jobs,“ asserting that “sometime in the next 40 years, robots are going to take your job,” and that “robots may steal as many as 800 million jobs in the next 13 years,” and proclaiming gloomy headlines such as “automation threatening 25% of jobs in the US,” and “robots to replace up to 20 million factory jobs by 2030.”

While idea that technology can render human labor obsolete is not new, and concerns about technological unemployment go back at least to Keynes (1930; p. 3) who in 1930 wrote about potential unemployment “due to our discovery of means of economizing the use of labor outrunning the pace at which we can find new uses for labor,” the recent proliferation of reports warning about the potential effect of new technologies, particularly advances in machine learning and robotics, on employment stands out in terms of the number of jobs allegedly under threat of replacement by machines and obsolescence. Different studies mention anywhere from 10 to 800 million jobs globally as in jeopardy over the next decade or so.

How should we think about automation and potential job loss? Where do the predictions of rising automation and job replacement come from? And what does current research say on the effects of technological change on employment? This memo will address these questions by 1) providing a summary of the economic framework of thinking about job displacement and productivity gains, 2) summarizing and analyzing the most influential studies claiming imminent job loss due to automation, 3) surveying recent research in economics on the historical effect of technological change on employment, and 4) summarizing the results and offering avenues for future research on the effect of automation technology on employment.

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