Task Attributes, Technological Change and the Vulnerability of Employment: a State Level Investigation

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2021-06-09

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Abstract

Two distinct trends can prove the existence of technological unemployment in the US. First, there are more open jobs than the number of unemployed persons looking for a job, and second, the shift of the Beveridge curve. There have been many attempts to find the cause of technological unemployment. However, all of these approaches fail when evaluating the impact of modern technologies on the employment future. This study hypothesizes that rather than looking into skill requirement or routine non-routine discrimination of tasks, a holistic approach is required to predict which occupations are going to be vulnerable with the advent of this 4th industrial revolution, i.e., widespread application of AI, ML algorithms, and Robotics. Three critical attributes are considered: bottleneck, hazardous, and routine. Forty-five relevant attributes are chosen from the O*NET database to define these three types of tasks. Performing Principal Axis Factor Analysis and K-medoid clustering, the study discovers a list of 407 vulnerable occupations. The study further analyzes the last ten years (2010 to 2019) of national employment data and finds that the growth of vulnerable occupations is only half than that of non-vulnerable ones despite the long rally of economic expansion. When it comes to state-level impact, the study detects a considerable disparity in job vulnerability. While all the states will experience net job loss, some states are far more vulnerable than others, especially the states that depend on manufacturing and production. On the contrary, education, health care, and IT industries would enjoy hefty growth in the coming years. The study recommends tailor-made industry and education policy for each state based on its current level of exposure to automation. Simultaneously, it touches federal intervention required for the betterment of underemployed and unemployed workers who would be impacted due to technological unemployment.

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Work, Work environment, Job security

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