By Anuja Ketan
The Next Web, March 2, 2018 —
By 2030, 14 percent of the global workforce — 375 million individuals — may need to switch occupations as a result of increased automation. This phenomenon, what economists term ‘labor switching’ has been lauded by technologists as the simple solution to the looming problem of mass displacement from automation.
But as innovations such as autonomous vehicles, cashierless checkout, algorithmic stock trading, and drone delivery become increasingly tangible, not only is there a notable lack of any institutionalized retraining to address the issue, but there’s very little attention being given to how this switch will affect the most disenfranchised members of our society.
Women, blacks, and latinos are left behind in an automated future
A recent study found that in the EU a disproportionate share of workers with at most secondary education and below median income are likely to be impacted by technology-driven labor loss. The job family that is most in decline is ‘Office and Administrative’ while the job family that is most accelerating is ‘Architecture and Engineering’ — both job families that contain a large gender disparity.
It’s no surprise that the World Economic Forum found in a 2018 study that women are more likely to lose jobs than men as automation increases, considering that traditionally female jobs are being lost at the highest rate.
It’s not just women who are being disproportionately impacted — it’s also people of color. In fact, the Brookings Institution assessed the automation potential of 20 occupations in which racial groups are most concentrated, and then compared that to the number of workers in each occupation to assess the impact of automation on race.
Unsurprisingly, they found that Latinos face the highest automation potential, at almost 60 percent, closely followed by blacks at 50 percent. And it’s worth noting that already in low-skilled jobs, white workers out-earn black workers by $3.00 an hour.
To make matters worse, low-income populations are less likely to participate in retraining as compared to middle and high income populations. In the EU, lower-skilled workers have been shown to be half as likely to participate in learning activities as the general EU population — and this gap increased from 2012 and 2015. Not only are minorities’ jobs more likely to be taken by automation, but these populations are also less likely to engage in traditional retraining programs.
As a female technologist of color, I know first-hand how rare it is for minority populations to be highly technologically literate, and within these populations, how much rarer it is for women to become technologically literate. If ‘retraining’ programs emphasize computer literacy and tech-heavy tasks, it’s likely that these populations will be left even further behind — particularly the middle-aged and up sector of these communities.
It’s imperative that education programs for unskilled laborers take into account factors such as digital literacy, time, and fiscal resources, and how to motivate and encourage workers to change their career paths.
How to maintain equality in an automated world
I have long advocated for minority-facing STEM programs. But while these will do well in training a new generation of female technologists of color, they don’t address the immediate problem of job loss for minority populations. In the immediate, we need union-backed educational programs that meet laborers where they are.
Consider that adult learners who access MOOCS are disproportionately people who already have college and graduate degrees. The Internet may democratize information, but for those who weren’t raised living and breathing Google, retraining needs to be taken offline.
Automation is a necessary force for our society to move forward, and in many ways it benefits and will continue to benefit our society as a whole. But as we face the ‘fourth industrial revolution,’ we must consider how to ensure that the benefits of automation are equitably distributed in order to give greater opportunity to all members of our society.
