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The countries most (and least) likely to be affected by automation

Today, about half the activities that people are paid to do in the global economy have the potential to be automated by adapting currently demonstrated technology. In all, 1.2 billion full-time equivalents and $14.6 trillion in wages are associated with activities that are technically automatable with current technology. This automation potential differs among countries, with the range spanning from 40% to 55%. Four economies—China, India, Japan, and the United States—dominate the total, accounting for just over half of the wages and almost two-thirds the number of employees associated with activities that are technically automatable by adapting currently demonstrated technologies.
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Automation entering white-collar work

Jobs you may have thought safe from automation, like mortgage brokers or paralegals, may soon be replaced by intelligent software.
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LMI and you

In partnership with Forum Research, LMIC is currently surveying over 20,000 individuals and organizations to better understand what information they use to make their education, workplace, and career decisions, as well as their opinions about the quality – of both content and form – of this information.
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Robot revolution: The economics of automation

This post highlights some of the possible economic implications of the so-called “Fourth Industrial Revolution” — whereby the use of new technologies and artificial intelligence (AI) threatens to transform entire industries and sectors. Some economists have argued that, like past technical change, this will not create large-scale unemployment, as labour gets reallocated. However, many technologists are less optimistic about the employment implications of AI. In this blog post we argue that the potential for simultaneous and rapid disruption, coupled with the breadth of human functions that AI might replicate, may have profound implications for labour markets. We conclude that economists should seriously consider the possibility that millions of people may be at risk of unemployment, should these technologies be widely adopted.