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.
