Learn to Code
The Challenges of Creating Mass Employment in Our Digital World
In January 2019 internet trolls took to Twitter to taunt recently fired journalists with some advice: “Learn to Code!” It was a shot at American “elites” who were deemed dismissive of blue-collar workers whose jobs are disappearing. The trolls caustically suggested a more promising future could be found in other fields with more growth potential in the digital era.
“Learn to code” is now a stinging jab, a sick burn that has certainly generated its fair share of LOLs. It is also indicative of a more broadly negative impact the internet has on U.S. politics, one that allows the aggrieved, snarky, and shorthand nature of digital debate to undermine substantive dialogue in favor of efforts to rub salt as deeply as possible into the wounds of a perceived opposition.
But what would happen if the trolling stopped and a good-faith effort to adapt to a changing labor market were made? What would happen if, well, blue-collar workers learned to code?
The Curious Case of Silicon Holler
Living in the rolling emerald hills of southern West Virginia, Billyjack Buzzard came from six generations of coal miners. Since he was a kid listening to his grandfather’s stories, he knew he wanted to make it seven.
Billyjack entered the mines at the age of 20 and worked underground for the better part of the next decade. During boom times he earned more than US$100,000 a year, working precisely the kind of blue-collar job that could provide opportunity for upward mobility and a sustainable living.
His was also the kind of job that is vanishing across the U.S. In 1970, employment based on manual labor (such as that in manufacturing, construction and mining) that often did not require education beyond a high school degree accounted for more than 31 percent of non-farm American jobs. That figure today is below 14 percent. In the same period — Billyjack’s boom years not withstanding — real wages for those with no more than a high school diploma dropped 12 percent while white-collar workers’ paychecks swelled by 14 percent.
What caused this rout on American middle-class jobs? Some blame international trade, arguing that manufacturers left Wayne County, West Virginia for cheaper labor costs in Chongqing, China. Others point to automation as the culprit. The truth lies somewhere in the middle, and the reality is that digital advances have exacerbated the impact of both trends.
In the case of global trade, digital technologies dramatically boosted productivity for suppliers to the world market, increasing importers’ marginal savings from an order of cents to dollars. In other words, if foreign-made televisions were initially somewhat cheaper than their American-made counterparts, they became significantly cheaper through digital advancement.
Such technologies also reduced the costs of trade, from transportation to marketing. In effect, the digital revolution supercharged the effects of free trade, as economic theory had long theorized. With the exaggerated gains of free trade’s winners, however, came the pain suffered by free trade’s losers.
Of course, productivity increased because of automation. And in the coming years, machines are expected to move beyond simply building stuff. McKinsey & Company estimates that half of what people do for a living today is already automatable. The consultancy forecasts that by 2030 more than 30 percent of current work activities will, in fact, be performed by machines.
Back in southern West Virginia, automation is becoming more central to coal mining. While the primary causes of coal’s decline are the arrival of cheaper natural gas alternatives and environmental concerns, increasingly automated rock crushers and shovel swings have replaced humans in the excavation of the black rock. American coal production dropped 40 percent over the last decade, and two-thirds of U.S. coal-mining jobs have disappeared since 1985.
Billyjack lost his job in 2015. His truck and his house were also soon gone, and he had to move his family back into his parents’ home. With pressure mounting alongside the unpaid bills, he confronted the same harrowing question faced by millions of Americans: “What in the world am I supposed to do now?”
In a sense, trade theory also predicted this labor market shift. If the digital age helps, say, China exploit its comparative advantage in manual labor, the U.S. theoretically should be able to do the same with skilled labor. But this back-of-the-envelope economic calculation begs two questions: First, can the No Collar Economy create enough job opportunities in massive, advanced countries such as the U.S.?; and second an the country adequately train its population to succeed in those jobs?
In Billyjack’s case, his lack of computer skills made competing for a new job outside mining seem almost impossible.
At a low point in his life, Billyjack decided to take a risk. He rolled up his sleeves, put on his work boots, and enrolled in a computer coding class, one of the coding boot camps that have popped up across Rust Belt America.
Billyjack joined a free program geared to former coal miners that promised to teach the skills needed to compete in the 21st-century digital economy. States such as Kentucky, Pennsylvania, and West Virginia are welcoming these programs, betting that their residents can work digital jobs and do so at lower wages than programmers in San Francisco or New York. Website design can certainly be done remotely, so why pay Silicon Valley rates when you can get a deal in Silicon Holler?
And lo and behold, Billyjack was good at it. Within a year he finished the Mined Minds boot camp and graduated as the most advanced student in the class. But where were all the jobs the program had promised? The work orders from out of town never materialized; the local pizza joint and Family Dollar supermarket had few tech needs.
The boot camp held on to Billyjack, its star pupil, paying him as a teacher for a while, but soon the camp itself ran out of money and had to close.
The issue at hand was not whether Billyjack had established a strong foundation of coding skills. It was, rather, whether this foundation was enough to prepare him to compete in the digital work force, especially in a region of the country that has yet to develop its own market for digital services.
As more and more traditional jobs become obsolete, the U.S.’s labor force challenges cannot be solved by simply providing retraining opportunities. The country must be able to engage the labor supply by scaling up employment opportunities for this newly trained workforce. The pressing riddle is how to create mass employment in the new digital economy.
Without an answer, the U.S. faces a deepening bifurcation between a small percentage of digital wunderkinds living well and the rest who try to make ends meet by serving these winners, often via the gig economy. By 2018, Uber had nearly 1 million drivers in the US, while Upwork estimates that a majority of American workers will be gig-oriented freelancers by 2027. Barring major reforms to gig-based salaries and the U.S. healthcare system, this paradigm for labor is no more sustainable than coal-powered electricity.
Visit the Bertelsmann Foundation’s No Collar Economy page for more stories from around Our Digital World.