Entire jobs and specific work activities will (continue to) be automated.

— Gil Press / Forbes

Treasury Secretary Steve Mnuchin declared last week that the threat of artificial intelligence taking over American jobs “is not even on my radar screen.” Mnuchin is “not worried at all,” at least not for the next 50 to 100 years. This was in sharp contrast to the attitude of the previous administration. President Obama, for example, opined that “We’ve been seeing specialized AI in every aspect of our lives, from medicine and transportation to how electricity is distributed, and it promises to create a vastly more productive and efficient economy… But it also has some downsides that we’re gonna have to figure out in terms of not eliminating jobs. It could increase inequality. It could suppress wages.”

How good or bad AI will be for employment and how soon its beneficial or detrimental effects will manifest themselves have been debated—loudly and persistently—over the last few years. Here’s a somewhat random collection of recent quantitative and qualitative assessments.

Entire jobs and specific work activities will (continue to) be automated

38% of jobs in the United States, 35% of jobs in Germany, 30% of UK jobs and 21% of jobs in Japan could be at potential risk of automation by the early 2030s–PwC

More than 85% of customer interactions will be managed without a human by 2020—Gartner

Automated vehicles could threaten or alter 2.2 million to 3.1 million existing U.S. jobs, including 1.7 million truck drivers—Executive Office of the President, December 2016

The world’s largest asset manager, BlackRock Inc., is entrusting more of its $5.1 trillion in assets to robot stock pickers to decide what to buy and sell. Seven portfolio managers are expected to leave—The Wall Street Journal.

A future in which human workers are replaced by machines is about to become a reality at an insurance firm in Japan, where more than 30 employees are being laid off and replaced with an artificial intelligence system that can calculate payouts to policyholders—The Guardian

Putting all new legal technology in place immediately would result in an estimated 13% decline in lawyers’ hours. A more realistic adoption rate would cut hours worked by lawyers by 2.5% annually over five years—Dana Remus and Frank S. Levy

Given currently demonstrated technologies, very few occupations—less than 5%—are candidates for full automation. However, almost every occupation has partial automation potential, as a proportion of its activities could be automated. We estimate that about half of all the activities people are paid to do in the world’s workforce could potentially be automated by adapting currently demonstrated technologies. That amounts to almost $15 trillion in wages—McKinsey Global Institute

More than 15% of global HR leaders say that robotics completely transformed their businesses in 2016, and more than double that number (31%) expect automation to have an even greater influence in 2017. Nearly two-thirds (65%) of HR leaders see artificial intelligence and robotics as having a positive impact on their businesses over the next three to five years—Randstad Sourceright

The role of radiologists will evolve from doing perceptual things that could probably be done by a highly trained pigeon to doing far more cognitive things. Take any old classification problem where you have a lot of data, and it’s going to be solved by deep learning. There’s going to be thousands of applications of deep learning—Geoffrey Hinton

New jobs and type of jobs will rise

In Accenture’s global study of more than 1,000 large companies already using or testing AI and machine-learning systems, we identified the emergence of entire categories of new, uniquely human jobs. These roles are not replacing old ones. They are novel, requiring skills and training that have no precedents–Accenture

Computer use is associated with a 1.7% increase in jobs in those computer-using occupations per year, and 0.45% employment growth overall—James Bessen, Boston University

A re-post from Forbes–AI and automation by the numbers: predictions, perceptions, and proposals by Gil Press

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