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Digital Skills, STEM Occupation, and Job Automation Risks among the Older Workers in the United States

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Bibliographic Details
Title: Digital Skills, STEM Occupation, and Job Automation Risks among the Older Workers in the United States
Language: English
Authors: Takashi Yamashita (ORCID 0000-0003-2325-126X), Donnette Narine, Runcie C. W. Chidebe, Jenna W. Kramer, Rita Karam, Phyllis A. Cummins, Thomas J. Smith
Source: Grantee Submission. 2024.
Peer Reviewed: Y
Page Count: 36
Publication Date: 2024
Sponsoring Agency: Institute of Education Sciences (ED)
Contract Number: R305A200261
Document Type: Reports - Research
Descriptors: Digital Literacy, STEM Careers, Automation, Older Workers, Risk, Labor Market, Problem Solving
Geographic Terms: United States
Assessment and Survey Identifiers: Program for the International Assessment of Adult Competencies (PIAAC)
DOI: 10.1093/geront/gnae069
Abstract: Background and Objective: Advancing automation technologies are replacing certain occupations such as those involving simple food preparation more than occupations such as those in STEM fields (e.g., engineering, health care). Older workers generally face higher job automation risks in part due to their lower levels of digital skills. A better understanding of the associations between job automation risk, digital skills, and type of occupation (e.g., STEM vs. non-STEM) can facilitate preparations for job automation and workforce population aging. Research Design and Methods: We analyzed a nationally representative sample (N = 1,560) of middle-aged and older U.S. workers aged 50 to 74 years from the 2012/2014/2017 Program for International Assessment of Adult Competencies (PIAAC) restricted-use file. The estimated job automation risks (i.e., percentage of jobs to be automated in the next decades) were derived from the previous studies. PIAAC digital problem-solving skills proficiency (measured on a scale of 0-500 points) was assessed based on a series of practical digital tasks (e.g., finding a job research website that does not require registration). Results: Linear regression analysis showed that greater digital skill proficiency (b = -0.04, p < 0.05) and STEM occupations (b = -17.78, p < 0.001) each were associated with lower job automation risks, even after adjusting for a series of demographic, socioeconomic, and civic engagement characteristics. Discussion and Implications: Education and labor policy interventions to promote digital skills among older workers and non-STEM workers may better prepare an aging workforce for the dynamic labor market needs in the United States. [This paper was published in "The Gerontologist" v64 n8 Article gnae069 2024.]
Abstractor: As Provided
IES Funded: Yes
Entry Date: 2025
Accession Number: ED676193
Database: ERIC
Description
Abstract:Background and Objective: Advancing automation technologies are replacing certain occupations such as those involving simple food preparation more than occupations such as those in STEM fields (e.g., engineering, health care). Older workers generally face higher job automation risks in part due to their lower levels of digital skills. A better understanding of the associations between job automation risk, digital skills, and type of occupation (e.g., STEM vs. non-STEM) can facilitate preparations for job automation and workforce population aging. Research Design and Methods: We analyzed a nationally representative sample (N = 1,560) of middle-aged and older U.S. workers aged 50 to 74 years from the 2012/2014/2017 Program for International Assessment of Adult Competencies (PIAAC) restricted-use file. The estimated job automation risks (i.e., percentage of jobs to be automated in the next decades) were derived from the previous studies. PIAAC digital problem-solving skills proficiency (measured on a scale of 0-500 points) was assessed based on a series of practical digital tasks (e.g., finding a job research website that does not require registration). Results: Linear regression analysis showed that greater digital skill proficiency (b = -0.04, p < 0.05) and STEM occupations (b = -17.78, p < 0.001) each were associated with lower job automation risks, even after adjusting for a series of demographic, socioeconomic, and civic engagement characteristics. Discussion and Implications: Education and labor policy interventions to promote digital skills among older workers and non-STEM workers may better prepare an aging workforce for the dynamic labor market needs in the United States. [This paper was published in "The Gerontologist" v64 n8 Article gnae069 2024.]
DOI:10.1093/geront/gnae069