Concern, not Panic, Over Jobs Sustainability, Part 1

The discussion about future jobs sustainability continues to heat up. On one side are prognosticators who predict artificial intelligence (AI), automation, and robotics will eliminate human jobs and create massive unemployment. The inevitable result will be social unrest, increased poverty, and ultimate chaos. On the other side are those who admit jobs will be eliminated but who predict more jobs will be created to replace them. Both sides continue to marshal their arguments. Interestingly, neither side wants to see a future characterized by massive unemployment and social unrest to be the one that actually emerges. One side wants to mitigate the effects of AI, automation, and robotics, while the other side wants to help foster an environment where humans and machines work side-by-side. Their perspectives are obvious. Prognosticators of a dark future see us in a battle against machines whereas proponents of a brighter future see us in a journey with machines. Ultimately, humans will decide which future ultimately emerges.

MIT’s Andrew McAfee (@amcafee) and Erik Brynjolfsson (@erikbryn) ask, “So shouldn’t we be preparing ourselves for massive AI-induced technological unemployment?”[1] Why would they ask that question? They explain, “A widely cited 2015 analysis by Carl Frey and Michael Osborne of Oxford University found that 47% of current jobs in the US were susceptible to computerization. And some jobs look especially ripe for automation. As self-driving technology advances it seems likely that many of America’s approximately 3.5 million truck drivers could find themselves out of a job.” In an earlier article, McAfee admits a world of unemployment is certainly possible but wonders if it would really be such a bad thing. He wrote, “Imagine a world where the robots did all the work. They tend the crops, sew the clothes, cook the food, drive the trucks, and work on all the assembly lines in all the world’s factories. In this world, everything would be a lot cheaper because labor costs would drop to zero. In fact, there’d be a startling abundance of stuff. And people would be freed up to do things other than work. We could use our time to explore, create, perform, craft, mingle, and so on because we wouldn’t have to work to produce the necessities or luxuries of life; the robots would be taking care of that.”[2] That’s a rosy picture, but mayors of cities suffering from high unemployment can attest people out of work are not spending their time exploring, creating, performing, or crafting. To be fair, McAfee knows a rosy, jobless future will only be possible if people have money. But that’s a topic for another article.

Working with Machines

In their latest article, McAfee and Brynjolfsson conclude a future characterized by unemployment might not be inevitable. “Despite these scary statistics and scenarios,” they write, “there’s no need to panic. For one thing, previous predictions about losses and gains over time in specific jobs have almost always been way off, and there’s little reason to believe the current crop will be any better. … A look at recent economic data clearly shows that the demand for good old-fashioned human labor keeps growing, even as AI and other science fiction technologies keep advancing.” Tucker Davey asks another important question, “How do we make sure that everybody can make a living?”[3] He’s concerned. “From the Luddite movement to the rise of the internet,” he writes, “people have worried that advancing technology would destroy jobs. Yet despite painful adjustment periods during these changes, new jobs replaced old ones and most workers found employment. But humans have never competed with machines that can outperform them in almost anything. AI threatens to do this, and many economists worry that society won’t be able to adapt.” Harry Holzer, the LaFarge SJ Professor at the McCourt School of Public Policy at Georgetown, admits, “A great deal of anxiety now exists in the U.S. over the future of jobs in an era of automation. Indeed, there are widespread fears that robots and artificial intelligence will increasingly perform the tasks currently performed by most Americans, rendering human workers increasingly obsolete over time.”[4]

Like McAfee and Brynjolfsson, Holzer looks to the past for answers. He explains, “The worst fears expressed by critics of automation have never come true; indeed, there has been no long-term trend whatsoever towards higher unemployment over time as automation has increased. As economists frequently explain, automation creates new jobs while eliminating older ones, in patterns that have held up again and again over time.” Critics of that thinking say this time things will be different. Holzer admits the latest technical revolution could be “somewhat different.” But, like McAfee and Brynjolfsson, he believes humans are likely to find gainful employment for many years. He’s just not sure society is prepared for the disruption technology will create. Jobs will be lost and unemployed workers will need to be retrained and reskilled (and, often, relocated). Holzer’s not sure our current system is up to the task. Davey agrees. He asks, “For workers whose skills are no longer needed — how will they keep up?” He explains there are at least six current issues within technology and labor requiring careful consideration. They are: education and training, community impact, job polarization, contingent labor, shared prosperity, and economic concentration. In the remainder of this article, I want to focus on the first issue — education and training. In Part 2 of the article, I’ll delve more deeply into the other areas of concern.

Education and Training

Holzer writes, “Some analysts urge educators to mostly focus on teaching a range of general skills — especially those that are technical, social/communicative or creative — that will make workers much less easily replaceable in a highly automated world.” Davey agrees. “As the labor market changes,” he asserts, “schools must teach students skills for future jobs, while at-risk workers need accessible training for new opportunities.” Moshe Vardi, a computer science professor at Rice University, told Davey, “Adapting to and training for new jobs will become more challenging as AI automates a greater variety of tasks.” To bolster this argument, Holzer cites New York Times‘ columnist Thomas Friedman, “who argues that we have entered an ‘age of acceleration’ where the speed and spread of automation and globalization now greatly outpace our individual and public capacities to adapt to them.” Friedman writes, “Every middle class job today … requires more skill or can be done by more people around the world or is being buried — made obsolete — faster than ever.” Holzer continues, “On a different occasion, Friedman writes ‘If you want a decent job that will lead to a decent life today, you have to work harder to regularly reinvent yourself’ or to ‘reinvent, re-engineer and reimagine that job.’ In other words, every worker will need to become a serial entrepreneur and a major self-promoter to remain employed.”

Holzer asserts, if people like Friedman are correct, “The implications of their views for any specific kinds of occupational or sectoral training are rarely acknowledged. In such a situation, general skills training — especially for tasks that the new robots will not be able to do anytime soon — make the most sense. According to many educators or workforce analysts, the skills in which students should invest (often referred to as ’21st Century skills’) include technical literacy, critical thinking and problem-solving, adaptability to new work environments, and social/communication skills.” I contend project-based STEM education can help students develop these skills. Holzer, however, worries that general skill training will be insufficient. He suggests public/private education programs might provide part of the solution. “We know from several rigorous evaluation studies,” he writes, “that sector-based workforce training — where community colleges (or other providers) create partnerships with employers or associations in specific industries and train workers for high-demand jobs in those sectors — generate quite large and lasting impacts on earnings for participating workers.”

Summary

Clearly, jobs sustainability remains a concern — and it should be a concern. However, Holzer concludes, “Rising productivity and falling prices associated with automation should increase workers’ real wages and generate new consumer spending, for other goods and services as well as the ones being automated. This new demand should raise employment and/or wages, at least in those other markets. And, as long as labor markets are flexible, there are no reasons why the new jobs created in all of these sectors shouldn’t be sufficient to return us to employment levels enjoyed before the automation began.” The challenge, as noted above, is ensuring displaced workers have a chance to be retrained, reskilled, and relocated to take advantage of new job opportunities. Holzer offers three recommendations:

“First, students should receive strong general training in ’21st century skills’ whenever they receive occupation — or industry-specific training. … Second, if and when these displacements do occur, we should have more robust models of ‘lifelong learning’ available to such workers to provide them with better retraining options than now exist. … Third, for displaced workers for whom retraining is not a realistic or appealing option, temporary income supports in the form of unemployment and especially wage insurance are more sensible policy options than the public provision of a universal basic income.”

McAfee and Brynjolfsson also conclude on an optimistic note. “The right policies, we believe, can give us the best of both worlds: all the benefits that come from the AI breakthroughs of today and tomorrow and jobs that provide people both dignity and a good paycheck.” In Part 2 of this article, I’ll look at the other areas of concern raised by Davey — community impact, job polarization, contingent labor, shared prosperity, and economic concentration.

Footnotes
[1] Andrew McAfee and Erik Brynjolfsson, “Why ‘How many jobs will be killed by AI?’ is the wrong question,” LinkedIn, 24 June 2017.
[2] Andrew McAfee, “Why I For One Welcome Our New Robot Underlings,” Andrew McAfee.org.
[3] Tucker Davey, “Artificial Intelligence And The Future Of Work,” The Huffington Post, 15 June 2017.
[4] Harry J. Holzer, “Will robots make job training (and workers) obsolete? Workforce development in an automating labor market,” The Brookings Institution, 19 June 2017.

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