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Transformation in Occupational Task Content in the 21st Century (306736)*Thao Tran, Federal Reserve Bank of Kansas City
Didem Tuzemen, Federal Reserve Bank of Kansas City
Keywords: Occupations, Task Content, Employment, ONET, Machine Learning, Automation
In 1967, automated teller machine was invented, and since then, it has replaced many cashier positions and helped businesses lower overhead costs. Since 1995, the commercial release of the video conference software, CU-SeeMe, has permanently changed the way workers communicate and reduced the need for travel in a job. These examples illustrate how technology and automation replaced workers in the labor force and how innovations led to major changes in the task content of occupations. While existing studies documented the former extensively, the latter has not yet been studied. In this paper, we document how tasks within occupations and the demand for them have changed between 2000 and 2019 using the Occupational Information Network (O*NET) database. Our findings show that occupations, on average, have significantly higher complex problem solving skills requirements now than two decades ago. We also find occupations with stronger focus on coordinating, managing, and advising activities are more desirable in the current labor market. Using machine learning algorithms, we predict the future demand for each occupation based on their attributes and characteristics.