This is the second post of the Future of Work blog series.
Automation—the replacement of human labor with robotics or artificial intelligence—is poised to radically reshape our economy. This process is highly disruptive. Many jobs, even whole industries, may look completely different in the near future. For workers with the resources and information needed to keep up, automation can open up new jobs and increased economic opportunities. But for low-income workers, weathering the storm is going to be much harder. This is in no small part because the systems they rely on for retraining in the face of economic disruption—the public workforce system, community colleges, and trade schools—do not have the information they need to understand the future impact of automation and aren’t structured to react accordingly. The system isn’t ready, and low-income workers may be left behind.
This lack of preparedness is particularly troubling given the fact that wide-scale automation is already happening. In some sectors, like mining and manufacturing, new technologies have driven enormous gains in productivity, while simultaneously eliminating more than a million jobs. New research on manufacturing jobs data has recently confirmed that the regional effects of automation were negative—in other words, introducing robots into factories eliminated more jobs than they created, and reduced wages. This same research found that automation, not overseas competition or offshoring, was the primary driver of job loss in the manufacturing sector between 1990 and 2007. Now automation is poised to widely impact new sectors as well, particularly jobs with work activities that are repetitive and predictable, require physical labor, or include collecting and processing data. These include entry-level occupations that employ millions of salespeople, clerks and receptionists, food preparation workers, customer service representatives, and machine operators, to name just a few.
What differentiates the current effect of automation on the labor market from that of previous generations is the rate of change. As MIT professors Erik Brynjolfsson and Andrew McAfee have argued, technological innovation is tied to computing power, and since computing power grows on a logarithmic scale (Moore’s law), so too does the rate of change technology produces. This means that newer technologies are exponentially more powerful than earlier technologies and can take on increasingly complicated tasks at a faster and faster rate. Gone are the 20-year economic cycles of the past. New technologies have the potential to radically impact millions of jobs in just a few short years.
In order to help low-income workers weather the economic storm of automation, a number of changes to the education and workforce retraining systems are needed:
1. Better data must be provided so that practitioners and policymakers can predict and measure the impact of automation and adjust their training programs accordingly. These resources need to be highly detailed, locally applicable, and specifically tailored to the realities faced by their users.
2. Education systems need to reinvent curriculum content and development timelines to reflect accelerated changes in society.
3. Policy and financial incentives need to be implemented that encourage the education and workforce systems to react proactively, not reactively, to the changes underway as a result of automation.
4. We need to promote innovative responses to automation, including the development of new tools and applications and more nimble educational program designs.
Automation is transforming the economy. The education and workforce systems must transform as well if we want to have any chance of allowing low-income workers to keep up.
Read President and CEO Maria Flynn’s blog on the future of work in our ongoing series.