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The Rise of the Robots: Mass Unemployment or Redeployment?
The robots are rising, but probably not as fast as you think. That is one of the takeaways from a lengthy new McKinsey Global Institute report, “Harnessing automation for a future that works.”
This is the headline finding: “While less than 5% of all occupations can be automated entirely using demonstrated technologies, about 60% of all occupations have at least 30% of constituent activities that could be automated. More occupations will change than will be automated away.”
Or as Michael Chui, one of the report’s authors, told the Wall Street Journal: “Given that we will need the machines working and the people working to get economic growth, we should be worrying about mass redeployment rather than mass unemployment.”
But if we are going to successfully “race with the machines” rather than against them — and ensure a world of higher productivity and gobs of good-paying jobs — there is a big role for policy. Right now. And that’s what politicians should be tweeting about, not reworking old trade deals. A key section from the report:
While some governments may be tempted to look for ways to slow automation adoption, out of concern for possible employment effects, such moves could prove counterproductive, holding back productivity without protecting jobs durably.
Automation could exacerbate a skills gap, even as it touches all occupations. There is already a growing divide in income advancement and employment opportunities between high-skill workers and those who are low- and medium-skill. In the past two decades, there has been a clear pattern of consistent job growth for high-skill workers and little or no growth for low- and middle-skill ones. For example, in 1981, college-educated workers in the United States earned a 48 percent wage premium over high school graduates. By 2005, that premium had risen to 97 percent—in other words, an American college graduate earns almost twice as much as a high school graduate.
The growing gap between productivity and wages is not new, but automation could accelerate the process. In its 2016 report on automation, the White House noted that the trend toward skill-biased change brought about by computerization and communications innovations is likely to continue in the decade ahead as a result of artificial intelligence’s effects on the labor market. To address this gap, policy makers could work with education providers to improve basic skills through the schools system and put a new emphasis on capabilities that are among the most difficult to automate, including creativity, understanding human emotions, and managing and coaching others.
For people who are already in the workforce, they could intervene to help workers develop skills best suited for the automation age. For example, many economies are already facing a shortage of data scientists and business translators. Governments working with the private sector could take steps to ensure that such gaps are filled, with new education and training possibilities established rapidly and prioritized. They could also foster the growth of technology-enabled solutions for the labor market that improve matching and access to jobs, such as online talent platforms.
As automation reshapes the workplace, independent work could become increasingly important, and policy makers will want to address issues such as benefits and variability that these platforms can raise
Published in Economics, Science & Technology
Chief Executives? I wonder what part of the role of President could be 10-30% automated.
Before I sign onto any such “race with the machines,” we need something approaching an answer to a crucial question, one that Imperial Silicon Valley refuses to contemplate:
Can Moore’s Law ever intersect or run into the Law of Diminishing Returns? Get an answer toward this, and we may have the outlines of our economic policies for at least the next 20-30 years.
Blah Blah Blah Blah Blah Blah. This topic has been so over discussed since the industrial revolution its ad-nosiem. Human being of below average intelligence that actually bother to use their mind will always figure out and be able to due jobs no computer program will ever be able to due. Machine learning is really overrated and I have been following the subject in quite detail lately and am someone who deals with manufacturing, accounting, and business processes on a daily bases. Its just such a silly discussion the only unemployment that this results in is people having to change career paths and retool. However changing career paths is way more common in the 21st century than it has ever been. Therefor automation causes the lest amount of long-term unemployment than it ever has.
Moore’s law is over i.e. cost per transistor. The last two nodes (major changes changes in cmos processes) are more expensive per transistor than the one before it. The extra expense has been justified based on power efficiency. The next node (7 nm cmos process) is the last on Intel’s roadmap.
Psychiatrists not threatened by automation?
Not so. There are already advances in the use of software to diagnose and treat some mental illnesses, with the advantage of not having to hire unstable humans to try and fix other unstable humans.
Machine learning is both really good and overrated. The recent work on image catagorization is more accurate (not just faster) than humans – radiologists beware. Other jobs that will be under the gun will be any job with the words “analyst” in the title. However, machine learning is based on having good training data, so many jobs in the future will be in producing and checking training data. These jobs will be very lucrative because once the training data is loaded into the machine learning algorithm their expertise can be repeated endlessly and cheaply. So what we will see is that many more occupations will become like professional athletics – only a select few will make a career of it and their income will be fantastic. However the vast majority of people will fail to make a career of it.
Except for drivers, almost all the low skilled manual labor jobs that can be automated already have been. However, the revolution now will be that many of the white collar and professional jobs based on repetitive application of expertise will be at risk.
” To address this gap, policy makers could work with education providers to improve basic skills through the schools system and put a new emphasis on capabilities that are among the most difficult to automate, including creativity, understanding human emotions, and managing and coaching others.”
Does anyone *really* believe that ‘the schools system’ is going to be able to effectively teach ‘creativity, understanding human emotions, and managing and coaching others’?
I think a lot of the estimates for “driver” automation are pretty overblown. A high percentage of jobs with “driver” in the job description are really “delivery and inventory management” jobs, where someone loads a truck, drives to a dozen different locations, drops off inventory, and removes the old inventory. The additional level of automation to manage that is just too far out for the near future.
Long-haul trucking is the big target for replacing drivers, for the most part.
(I’m a tech, so I’m pretty lucky. At worst, I’ll be fixing the automation that puts most people out of work.)
The great courses and churches could do that.