Jiyuan Zheng, Bertha Rohenkohl, Mauricio Barahona, Jonathan M Clarke
{"title":"Automation risk and subjective wellbeing in the UK","authors":"Jiyuan Zheng, Bertha Rohenkohl, Mauricio Barahona, Jonathan M Clarke","doi":"10.1101/2024.01.18.24301484","DOIUrl":null,"url":null,"abstract":"The personal well-being of workers may be influenced by the risk of job automation brought about by technological innovation. Here we use data from the Understanding Society survey in the UK and a fixed-effects model to examine associations between working in a highly automatable job and life and job satisfaction. We find that employees in highly automatable jobs report significantly lower job satisfaction, a result that holds across demographic groups categorised by gender, age and education, with higher negative association among men, higher degree holders and younger workers. On the other hand, life satisfaction of workers is not generally associated with the risk of job automation, a result that persists among groups disaggregated by gender and education, but with age differences, since the life satisfaction of workers aged 30 to 49 is negatively associated with job automation risk. Our analysis also reveals differences in these associations across UK industries and regions.","PeriodicalId":501555,"journal":{"name":"medRxiv - Occupational and Environmental Health","volume":"76 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Occupational and Environmental Health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.01.18.24301484","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The personal well-being of workers may be influenced by the risk of job automation brought about by technological innovation. Here we use data from the Understanding Society survey in the UK and a fixed-effects model to examine associations between working in a highly automatable job and life and job satisfaction. We find that employees in highly automatable jobs report significantly lower job satisfaction, a result that holds across demographic groups categorised by gender, age and education, with higher negative association among men, higher degree holders and younger workers. On the other hand, life satisfaction of workers is not generally associated with the risk of job automation, a result that persists among groups disaggregated by gender and education, but with age differences, since the life satisfaction of workers aged 30 to 49 is negatively associated with job automation risk. Our analysis also reveals differences in these associations across UK industries and regions.