The Myth of America’s “Unprecedented Technological Job Disruption”
 
It has recently become an “article of faith” that workers in advanced industrial nations are experiencing unprecedented levels of labor-market disruption and insecurity. From taxi drivers being displaced by Uber, to lawyers losing their jobs to artificial intelligence-enabled legal-document review, to robotic automation putting blue-collar manufacturing workers on unemployment, popular opinion is that technology is driving a relentless wave of Schumpeterian “creative destruction,” and we are consequently witnessing an unprecedented level of labor market “churn.” One Silicon Valley pundit even predicts that technology will eliminate 80 to 90 percent of U.S. jobs in the next 10 to 15 years.

Yet, despite popular perceptions, an objective analysis of the data says that the U. S. labor market is not experiencing “unprecedented technological disruption.”  In fact, occupational churn in the United States is at a historic low.  And, as we’ll show, it is time to stop worrying and start accelerating productivity growth with more technological innovation.

Consider the facts.

The Information Technology and Innovation Foundation (or ITIF) has documented that the grim assessments of information technology’s impact on jobs are the products of faulty logic and erroneous empirical analysis, making them simply irrelevant to the current policy debate.  For example, techno-pessimists often assume that robots can do most human jobs, when in fact, they can’t. Or they assume that once a job is lost, there are no second-order job-creating effects from increased productivity and spending. But the techno-pessimists’ grim assessments also suffer from being a “misreading of history.“

 
When we carefully examine the last 165 years of American history, statistics show that the U.S. labor market is not currently experiencing particularly high levels of job churn, which is defined as new occupations being created while older occupations are destroyed. In fact, it’s the exact opposite: Levels of occupational churn in the United States?defined as the rates at which some occupations expand while others contract?are now at historic lows. The average level of churn in the last 20 years?a period including the dot-com crash, the financial crisis of 2007 to 2008, the subsequent Great Recession, and the emergence of new technologies that are purported to be more powerfully disruptive than anything in the past?has been just 38 percent of the average level from 1950 to 2000, and 42 percent of the average level from 1850 to 2000.

Other than being of historical interest, why does this matter?  Because if opinion leaders continue to argue that we are in unchartered economic territory and warn that just about anyone’s occupation can be thrown on the scrap heap of history, then the public is likely to sour on technological progress, and society will become overly risk averse, seeking tranquility over churn and the status quo over further innovation. Such concerns are not theoretical: Some jurisdictions ban ride-sharing apps such as Uber because they fear losing taxi jobs, and someone as prominent and respected as Bill Gates has proposed taxing robots like human workers?without the notion being roundly rejected as a terrible idea, akin to taxing tractors in the 1920s.

In fact, the single biggest economic challenge facing advanced economies today is not too much labor market churn, but too little, and thus too little productivity growth.  And that’s bad, because increasing productivity is the only way to improve living standards, with productivity in the last decade growing at the slowest rate in 60 years!

The full analysis by ITIF examined U.S. occupational trends from 1850 to 2015, drawing on Census data compiled by the University of Minnesota’s demographic research program and the Minnesota Population Center, to compare the changes in occupational job levels from decade-to-decade. ITIF assigned a code to each occupation to judge whether increases or decreases in employment in a given decade were likely due to technological progress or other factors. Overall, three main findings emerge from this analysis.
 
First, contrary to popular perception, rather than increasing over time, the rate of occupational churn in recent decades is at the lowest level in American history, at least as far back as 1850.  Occupational churn peaked at over 50 percent in the two decades from 1850 to 1870 which means the absolute value sum of jobs in occupations growing and occupations declining was greater than half of total employment at the beginning of the decade.  On the other extreme, occupational churn fell to its lowest levels in the last 15 years, at around 10 percent. When looking only at absolute job losses in occupations, the last 15 years has also been comparatively tranquil, with just 70 percent as many losses as in the first half of the 20th century, and a bit more than half as many as in the 1960s, 1970s, and 1990s.

Second, many believe that if innovation accelerates more, then new jobs in new industries and occupations will make up for any technology-created losses. But the truth is that growth in already existing occupations is what more than makes up the difference. In no decade has technology directly created more jobs than it has eliminated. Yet, throughout most of the period from 1850 to present, the U.S. economy as a whole has created jobs at a robust rate, and unemployment has been low. This is because most job creation that is not explained by population growth has stemmed from productivity-driven increases in purchasing power for consumers and businesses. Such innovation allows workers and firms to produce more, so wages go up and prices go down, which increases spending, which in turn creates more jobs in new occupations, though more so in existing occupations (ranging from cashiers to nurses and doctors). There is simply NO reason to believe that this dynamic will change in the future for the simple reason that consumer wants are far from satisfied. And,

 
Third, in contrast to the popular view that technology today is destroying more jobs than ever, ITIF’s findings suggest that is not the case. The period from 2010 to 2015 saw approximately 7 technology-related jobs created for every 10 lost, which was the highest ratio?meaning lowest share of jobs lost to technology?of any period since 1950 to 1960.

Many believers in the “fourth industrial revolution” argue that this relative tranquility is just “the calm before a coming storm” of robot- and artificial-intelligence-driven job destruction. But projections based on this view?including from such venerable sources as the World Economic Forum and Oxford University?are either immaterial or inaccurate.

On the other hand, there are at least a dozen reasons to move forward aggressively with AI and robotics before the “demographic winter” we’ve discussed in prior issues creates a manpower shortage:

1. Technology-driven automation is central to the process of increasing our living standards. That is because better “tools” allow us to produce more. It is only by producing more that workers can earn more and companies can lower prices, both of which increase living standards.

2. There are two kinds of technologically driven productivity. The first kind, such as automatic elevators replacing elevator operators, is when technology replaces workers.  The second kind, such as carpenters using pneumatic nail guns instead of hammers, is when technology makes workers more productive. Both are good, and both boost productivity and per-capita GDP.

3. The employment impacts of automation in a particular industry depend on the nature of the industry. Automation lets organizations lower costs and therefore prices. In industries where lower prices don’t lead to significantly more demand for a good or service, automation allows fewer workers to produce the same output. But in industries where lower prices spur more demand, automation allows the same number of workers to produce more output.

4. Automation has differing effects on different occupations. Some, such as travel agents, have seen employment declines because of new technology. Some occupations have seen gains come from increases in standards of living: for example, more people can afford to hire childcare workers today.  Other occupations see increases come when a new technology creates new occupations directly, as in the case of computer scientists.

5. Automation has differing effects on regions. Regions that have a higher share of employment in industries that experience faster productivity gains, as is now the case with manufacturing, will see slower net job growth than regions with a higher share of industries that experience slower productivity growth, such as business services.

6. Automation itself does not necessarily lead to net job gain. Some jobs will be created making new tools, but the use of new tools will always eliminate more jobs. No organization invests in automation if the net-present value costs are greater than the savings. In other words, if it takes 100 hours of work to build a machine that saves 90 hours of work, no company will adopt it.

7. Automation does not necessarily lead to net job loss, either. Even if automation eliminates some of the jobs in a particular industry, it does not typically reduce jobs in the overall economy. The reason is that no organization automates unless it saves money, and most of those savings get passed on to consumers, who in turn use those savings to buy something else. And that spending creates jobs in other parts of the economy.

8. Automation increases net human welfare even if so-called “good” jobs are automated. Some argue that automation should only be for the 3Ds: dumb, dirty, and dangerous jobs. Clearly, automating undesirable jobs is a double win, because there are fewer bad jobs and overall GDP increases. But automating “good” jobs is also a good thing, because it leads to increases in GDP; the original output still exists, but workers are redeployed to produce new and additional output, so society reaps the benefits of more plentiful goods and services.

9. Limiting automation to protect workers would hurt economic growth and the average standard of living.  In some industries where demand doesn’t grow enough from the lower prices automation brings, there will be employment effects. In some cases, workers may be laid off. In other cases, companies may not hire new workers to replace those who leave voluntarily. But either way, there can be fewer jobs in particular industries. It is easy to succumb to the view that we should avoid this outcome at all costs, because it can involve painful dislocation for some workers. But those costs come at considerable benefit to everyone else who enjoys higher living standards than they otherwise would. So, the focus instead should be on easing displaced workers’ transitions into new jobs.

10. As ITIF argues, the rate of automation will never exceed the rate of compensating job creation. Many fear that the pace of change is increasing too fast, even though there is no evidence that the current or expected rate of technological change and productivity will be higher than historical rates. But even if the rate of automation does increase, there is no reason to expect that concurrent job creation (from lower prices and higher wages) will not keep up, especially if macroeconomic policy is calibrated appropriately.

11. Rising productivity benefits average workers today, just as it always has in the past.  It is simply not true that wages have stagnated over the last few decades as productivity has grown. As ITIF, the Congressional Budget Office, and the Federal Reserve Bank of San Francisco have all shown, productivity has translated into wage gains, albeit not as much as they should have because income inequality has increased.  But it is simply not true that productivity gains in the last two decades have not produced gains for workers in all income deciles. As documented in prior issues of Trends, most job and wage losses for the bottom 60% of American workers have been caused by a combination of off-shoring and an oversupply of low-skilled immigrant workers.  And,

12. Regardless of the rate of technological automation, the United States needs to do more to help American workers make transitions between jobs and occupations. The failure to give workers the skills and assistance to move into new jobs or occupations not only contributes to higher structural unemployment, but also breeds resistance to innovation and automation.

Policymakers and managers should take away three key points from this analysis:

1. Take a deep breath, and calm down. Labor market disruption is not abnormally high; it’s at a 170-year low, and predictions that human labor is just one tech “unicorn” away from redundancy are vastly overstated, as they always have been.

2. If there is a genuine risk to our future, it is that technological change and resulting productivity growth will be too slow, not too fast. Therefore, rather than try to slow down change, policymakers should do everything possible to speed up the rate of creative destruction. Otherwise, it will be impossible to raise living standards faster than the current snail’s pace of progress. Among other things, this means not giving in to the interests of incumbent companies or workers who simply want to resist disruption.  And,

3. Policymakers should do more to smooth labor-market transitions for workers who lose their jobs. That is true regardless of the rate of churn or whether policy seeks to retard or accelerate it. Likewise, it doesn’t matter whether the losses stem from short-term business-cycle downturns or from trends that lead to natural labor-market churn.

Given this trend, we offer the following forecasts for your consideration.

First, over the next eight to twelve years, U. S. government policy will favor maximizing productivity and economic growth.

The Trump administration is already sowing the seeds of an enormous automation boom in four ways.

1. Regulatory burdens are being eased raising the ROI on capital investments.

2. Reducing corporate tax rates ensures that more of the gains flow to the bottom line.

3. New trade agreements are almost certain to make off-shoring less attractive.  And,

4. Restrictions on immigration will make maximizing the productivity of U. S. workers even more important and ensure that wages rise along with productivity.

Second, through 2035, AI-based automation will accelerate annual U.S. growth to an amazing level as high as 4.6% per year average; that is 40% higher than growth from 2009 to 2016.

The analysis by Accenture supporting this forecast was summarized in the January 2017 issue of Trends.  In a world where many experts question sustained growth at over 3%, this is certainly encouraging.  And, the policy trends cited earlier simply make us more certain that this forecast is realistic.
 
Third, the deployment of AI in the manufacturing sector will accelerate the trend toward reshoring.

As productivity rises and costs plunge, American companies will be able to afford to move their production back to the U.S., which will help to offset any job losses in other sectors.  However, according to a report from the Pardee Center for International Futures prepared for the U.S. National Intelligence Council, this means that developing countries will no longer be able to simply follow the path to modernization of their economies by developing cheap manufacturing capabilities for export markets.  Why? Because it now costs the same amount to deploy a manufacturing robot as it does to outsource a manufacturing job to the average Chinese laborer.  Boston Consulting Group found that more than one-third of companies with revenues above $1 billion are considering reshoring.  As a result, developing countries will need to find another way to boost economic growth, and according to the Pardee Center report, there is no clear roadmap for them to follow.

Fourth, to minimize job losses, employers and educators will work together to close the “skills gap.”

As long as employees have the right skills to work with AI and robotics, their roles will expand and their jobs will become more meaningful as they focus on activities that add value, while offloading routine tasks to machines and software.  According to The Economist, “AI will not so much replace workers directly as require them to gain new skills to complement it.”  Workers will be given opportunities to master new skills through online learning, courses at community colleges and business schools, and on-the-job training.  And,
 
Fifth, universal basic income is an essentially wrong-headed solution that will never be adopted in the United States.

In response to hypothetical fears that automation will lead to mass joblessness, some have called for universal basic income (or UBI), where the state provides income to all adults, working or not. This is a bad idea. Automation does not raise unemployment rates, but UBI will, because it will encourage people not to work and divert spending from activities that would create more jobs for people without jobs.

References
1. D. Atkinson and John Wu. May 2017. False Alarmism: Technological Disruption and the U.S. Labor Market, 1850?2015 (Information Technology and Innovation Foundation)

https://itif.org/publications/2017/05/08/false-alarmism-technological-disruption-and-us-labor-market-1850-2015

2. D. Atkinson. May 2017. Robots, Automation, and Jobs: A Primer for Policymakers (Information Technology and Innovation Foundation)

https://itif.org/publications/2017/05/08/robots-automation-and-jobs-primer-policymakers

3. Accenture Institute for High Performance, September 2016, “Why Artificial Intelligence Is the Future of Growth,” by Mark Purdy and Paul Daugherty. ⓒ 2016 Accenture.  All rights reserved.

http://www.accenture.com/us-en/insight-artificial-intelligence-future-growth

4. To access the Analysis Group report estimating the economic impacts of artificial intelligence, visit their website at:

http://www.analysisgroup.com/news-and-events/news/analysis-group-team-issues-report-estimating-projected-global-economic-impacts-of-artificial-intelligence/

5. Trends Magazine. January 2017. Harnessing AI-Driven Growth.

http://audiotech.com/trends-magazine/harnessing-ai-driven-growth/