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記事

15 1月 2017

著者:
James Manyika, Michael Chui, Mehdi Miremadi, Jacques Bughin, Katy George, Paul Willmott, and Martin Dewhurst, McKinsey Global Institute

Harnessing automation for a future that works

"Recent developments in robotics, artificial intelligence, and machine learning have put us on the cusp of a new automation age. Robots and computers can not only perform a range of routine physical work activities better and more cheaply than humans, but they are also increasingly capable of accomplishing activities that include cognitive capabilities once considered too difficult to automate successfully...

Automation will change the daily work activities of everyone, from miners and landscapers to commercial bankers, fashion designers, welders, and CEOs. But how quickly will these automation technologies become a reality in the workplace? And what will their impact be on employment and productivity in the global economy?

[...]The activities most susceptible to automation are physical ones in highly structured and predictable environments, as well as data collection and processing...And it’s not just low-skill, low-wage work that could be automated; middle-skill and high-paying, high-skill occupations, too, have a degree of automation potential...

Still, automation will not happen overnight. Even when the technical potential exists, we estimate it will take years for automation’s effect on current work activities to play out fully. The pace of automation, and thus its impact on workers, will vary across different activities, occupations, and wage and skill levels...Our scenarios suggest that half of today’s work activities could be automated by 2055, but this could happen up to 20 years earlier or later depending on various factors, in addition to other economic conditions.

[...]While much of the current debate about automation has focused on the potential for mass unemployment, people will need to continue working alongside machines to produce the growth in per capita GDP to which countries around the world aspire. Thus, our productivity estimates assume that people displaced by automation will find other employment. Many workers will have to change, and we expect business processes to be transformed. [O]ur analysis shows that humans will still be needed in the workforce: the total productivity gains we estimate will only come about if people work alongside machines. That in turn will fundamentally alter the workplace, requiring a new degree of cooperation between workers and technology."

 

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