Free reading is over, click to pay to read the rest ... pages
0 dollars,0 people have bought.
Reading is over. You can download the document and read it offline
0people have downloaded it
Document pages: 17 pages
Abstract: Two distinct trends can prove the existence of technological unemployment inthe US. First, there are more open jobs than the number of unemployed personslooking for a job, and second, the shift of the Beveridge curve. There havebeen many attempts to find the cause of technological unemployment. However,all of these approaches fail when it comes to evaluating the impact of moderntechnologies on employment future. This study hypothesizes that rather thanlooking into skill requirement or routine non-routine discrimination of tasks,a holistic approach is required to predict which occupations are going to bevulnerable with the advent of this 4th industrial revolution, i.e., widespreadapplication of AI, ML algorithms, and Robotics. Three critical attributes areconsidered: bottleneck, hazardous, and routine. Forty-five relevant attributesare chosen from the O*NET database that can define these three types of tasks.Performing Principal Axis Factor Analysis, and K-medoid clustering, the studydiscovers a list of 367 vulnerable occupations. The study further analyzes thelast nine years of national employment data and finds that over the previousfour years, the growth of vulnerable occupations is only half than that ofnon-vulnerable ones despite the long rally of economic expansion.
Document pages: 17 pages
Abstract: Two distinct trends can prove the existence of technological unemployment inthe US. First, there are more open jobs than the number of unemployed personslooking for a job, and second, the shift of the Beveridge curve. There havebeen many attempts to find the cause of technological unemployment. However,all of these approaches fail when it comes to evaluating the impact of moderntechnologies on employment future. This study hypothesizes that rather thanlooking into skill requirement or routine non-routine discrimination of tasks,a holistic approach is required to predict which occupations are going to bevulnerable with the advent of this 4th industrial revolution, i.e., widespreadapplication of AI, ML algorithms, and Robotics. Three critical attributes areconsidered: bottleneck, hazardous, and routine. Forty-five relevant attributesare chosen from the O*NET database that can define these three types of tasks.Performing Principal Axis Factor Analysis, and K-medoid clustering, the studydiscovers a list of 367 vulnerable occupations. The study further analyzes thelast nine years of national employment data and finds that over the previousfour years, the growth of vulnerable occupations is only half than that ofnon-vulnerable ones despite the long rally of economic expansion.