AI-driven job losses may not just make it harder for affected workers to find employment in the short term but also could leave a yearslong “scarring,” marked by depressed income, delayed homeownership and even the lower probability of marriage, according to a new research report from Goldman Sachs.
And those outcomes are even worse if they happen during a recession, Goldman Sachs economists wrote Monday.
The latest analysis comes as economists, policymakers, academics and workers across industries are trying to assess how fast-rising artificial intelligence technologies could affect people, sectors and societies at large. Goldman Sachs previously estimated that 6% to 7% of US workers (about 11 million people) could have their jobs displaced by AI.
Monday’s note explored the potential longer-run effects of AI-related job displacement.
To do so, economists turned to the recent past: They identified occupations usurped by various technological innovations since 1980, and they then tracked the labor market outcomes of workers by applying data from the National Longitudinal Surveys, a federal research effort to gather information at multiple times in people’s lives.
In doing so, the economists came to four conclusions:
“Overall, these patterns suggest that AI-driven displacement could impose lasting costs on affected workers, with substantially larger effects when job losses coincide with a recession,” economists Pierfrancesco Mei and Jessica Rindels wrote.
However, they noted, while a lot of attention has been focused on the potential negative impact that AI is having on new graduates, past research shows that younger workers who switched jobs or upgraded their skills had better outcomes.
Mei and Rindels highlighted retraining programs as a potential solution in mitigating the negative effects of technology displacement.
“Retrained workers tend to move up the occupational ladder into roles with higher abstract content – positions requiring advanced skills and greater complementarity with information and communication technology – thereby reducing their exposure to future automation,” they wrote.
Source: edition.cnn.com
