Which Workers Suffer Most When New Technology Arrives? – Kellogg Insight

But which workers, exactly, are most likely to suffer lost jobs or reduced income when new technologies arrive?

Bryan Seegmiller, an assistant professor of finance at Kellogg, along with Kellogg finance professor Dimitris Papanikolaou and their colleagues, sought to better understand which types of workers were historically vulnerable to being rendered obsolete by technology, and how career disruptions caused by technology affected their future earnings. They developed a novel way to measure workers’ exposure to emerging technology by identifying similarities between the tasks associated with different occupations and the descriptions in new patents. That allowed them to track how breakthrough technologies impacted the exposure of workers in relevant occupations over time.

As one might expect, they found that manual laborers had the highest exposure to emerging technologies, especially from 1850 to 1970. But other patterns were more surprising. In the 1970s, occupations in which people performed routine “cognitive” tasks, such as clerks, technicians, and programmers, also began to face much larger exposures to technology. And when new inventions showed up, workers who earned the highest salaries within the affected occupations—that is, those with the most advanced skills—saw the biggest slowdowns in their wages.

“The more-skilled workers have the most to lose,” Seegmiller says. They tend to “get hit the hardest in terms of their income.”

Winners and Losers

In general, technology improves productivity and standards of living. But gains and losses aren’t distributed equally. Each advance might help everyone on average, “but there might be a very particular subset of people that just get absolutely hammered by it,” Seegmiller says.

To better understand which workers have been affected by technological advances historically, Seegmiller and Papanikolaou, along with Leonid Kogan and Lawrence Schmidt at the MIT Sloan School of Management, devised a new way to measure how people’s exposure to technology—that is, their risk of being displaced by new inventions—changed over time.

The researchers gathered descriptions of tasks performed in more than 13,000 types of jobs from the Dictionary of Occupation Titles database. Then they developed an algorithm using tools from natural language processing to compare the task descriptions with the text of patents from 1840 to 2010, focusing on breakthrough advances. Based on text similarities, the team could identify patents that were highly related to job tasks associated with specific occupations.

For instance, the algorithm matched a 19th-century patent for a knitting machine to occupations such as textile workers and sewers. A patent for a system to manage financial accounts was matched to financial managers, credit analysts, …….

Source: https://news.google.com/__i/rss/rd/articles/CBMiZmh0dHBzOi8vaW5zaWdodC5rZWxsb2dnLm5vcnRod2VzdGVybi5lZHUvYXJ0aWNsZS93aGljaC13b3JrZXJzLXN1ZmZlci1tb3N0LXdoZW4tbmV3LXRlY2hub2xvZ3ktYXJyaXZlc9IBAA?oc=5

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