Automation Disproportionately Affects Latinos’ Jobs
During the last big wave of automation in the 1980s and 1990s, technology produced new jobs and made others obsolete. Laborers who didn’t have much experience beyond their rote jobs were, in turn, hit the hardest, and those laborers tended to be black: “Even before the economic restructuring of the nation’s economy,” wrote William Julius Wilson in his 1996 book When Work Disappears, “Low-skilled African-Americans were at the end of the employment queue.” Who will the biggest victims be in this new age of automation, in which artificial intelligence dominates and tasks such as driving are computerized? Latinos, especially Latino men, are heavily overrepresented in those challenging, and oftentimes repetitive, roles. The 20 most popular occupations among Latinos in the U.S. virtually all involve hard, manual work and are often dangerous, according to the Brookings Institution fellows Mark Muro and Jacob Whiton, citing jobs in agriculture, roofing, and construction specifically. Latinos make up a whopping 63 percent of drywall installers, a dangerous job because of the harmful irritants in drywall dust, while 30 percent are white and 7 percent are African American, according to Muro and Whiton’s calculations. Latinos are also overrepresented in repetitive work that requires few digital skills-such as that in hospitality-and, according to research by the Mckinsey Global Institute, is most susceptible to automation using currently available technologies. The automation of jobs such as drywall installation and roofing is also appealing because the positions are so dangerous: Replacing humans with robots in those jobs could prevent countless injuries and save lives. The problem is that few Latinos seem to have these opportunities. According to the Pew report, Latinos are far more likely than whites and blacks to cite automation as the key cause for why their hours or pay have been reduced, or even why they lost a job. Latinos, the researchers found, face the highest automation potential at close to 60 percent, followed by blacks at 50 percent, Asians at almost 40 percent, and whites at roughly 25 percent. Without digital skills, Latinos can be automated out of jobs that extend far beyond the construction and hospitality sectors: According to Brookings, the share of jobs that don’t require workers to have experience beyond basic digital skills-such as knowing how to use Excel and Word-has fallen from 56 to 30 percent between 2002 to 2012.Proposals to tax robots and automation, among other efforts, seek to curtail the spread of new technologies. Latinos have a higher high-school dropout rate-at 10 percent-than their black, whites, and Asian peers, in large part because they tend to pool their resources together to have one household income, said Jaime Dominguez, a political-science and Latino-studies professor at Northwestern University, alluding to the fact that so many Latino families are low-income. Certain initiatives, such as Pathways 2 Apprenticeship, focus on African-Americans, Latinos, and other disadvantaged people of color namely because they are more likely to be low-income than whites. Automation threatens to exacerbate a pattern in which Latinos are stuck at the bottom of the socioeconomic ladder: In depriving them of jobs-and often pushing them into the devastating cycle of long-term unemployment, the trend will make it increasingly difficult for low-income Latinos to enter the middle class. Doubts about the merits of federal job-training initiatives aside, it’s worth noting that the act does little to explicitly target supports for Latinos.
So which jobs are most vulnerable? In a widely noted study published in 2013, Carl Benedikt Frey and Michael Osborne examined the probability of computerisation for 702 occupations and found that 47% of workers in America had jobs at high risk of potential automation. Economists are already worrying about “Job polarisation”, where middle-skill jobs are declining but both low-skill and high-skill jobs are expanding. “We are just seeing the tip of the iceberg. No office job is safe,” says Sebastian Thrun, an AI professor at Stanford known for his work on self-driving cars. In previous waves of automation, workers had the option of moving from routine jobs in one industry to routine jobs in another; but now the same “Big data” techniques that allow companies to improve their marketing and customer-service operations also give them the raw material to train machine-learning systems to perform the jobs of more and more people. In the past technology has always ended up creating more jobs than it destroys. Rather than destroying jobs, ATMs changed bank employees’ work mix, away from routine tasks and towards things like sales and customer service that machines could not do. The same pattern can be seen in industry after industry after the introduction of computers, says Mr Bessen: rather than destroying jobs, automation redefines them, and in ways that reduce costs and boost demand. In a recent analysis of the American workforce between 1982 and 2012, he found that employment grew significantly faster in occupations that made more use of computers, as automation sped up one aspect of a job, enabling workers to do the other parts better. The net effect was that more computer-intensive jobs within an industry displaced less computer-intensive ones. Only manufacturing jobs expanded more slowly than the workforce did over the period of study, but that had more to do with business cycles and offshoring to China than with technology, he says. Horse-related jobs declined, but entirely new jobs were created in the motel and fast-food industries that arose to serve motorists and truck drivers. An analysis of the British workforce by Deloitte, a consultancy, highlighted a profound shift over the past two decades towards “Caring” jobs: the number of nursing assistants increased by 909%, teaching assistants by 580% and careworkers by 168%. Focusing only on what is lost misses “a central economic mechanism by which automation affects the demand for labour”, notes Mr Autor: that it raises the value of the tasks that can be done only by humans. During previous waves of automation, he argues, workers could switch from one kind of routine work to another; but this time many workers will have to switch from routine, unskilled jobs to non-routine, skilled jobs to stay ahead of automation. So who is right: the pessimists, who say this time is different and machines really will take all the jobs, or the optimists, who insist that in the end technology always creates more jobs than it destroys? The truth probably lies somewhere in between. Despite the wide range of views expressed, pretty much everyone agrees on the prescription: that companies and governments will need to make it easier for workers to acquire new skills and switch jobs as needed.