Technological Disruption in the US Labor Market

This paper explores past episodes of technological disruption in the US labor market, with the goal of learning lessons about the likely future impact of artificial intelligence (AI). The authors measure changes in the structure of the US labor market going back over a century in two ways. First, they examine the relative frequencies of occupations from 1880-2020. Over that period, the structure of the US labor market underwent two large shifts: 

They also find that the pace of change, as measured by occupational churn , has slowed over time: the years spanning 1990 to 2017 were less disruptive than any prior period we measure, going back to 1880. This comparative decline is not because the job market is stable today but rather because past changes were so profound. 

These changes were caused by general-purpose technologies (GPTs), like steam power and electricity, which dramatically disrupted the twentieth-century labor market over the course of several decades. The authors argue that AI could be a GPT on the scale of prior disruptive innovations and suggest that there are two patterns in the data that might indicate that AI is leading to labor market disruptions along the lines of past GPTs. First, increased investment in new technologies and a J-curve pattern of productivity growth in AI-exposed sectors. Second, large but steady declines in employment share for AI-exposed jobs, especially jobs in sectors where consumers don’t increase consumption with rising income. They present early evidence of such signs in four stylized facts:

Leave a Comment