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Transformation to Industrial Artificial Intelligence and Workers' Mental Health: Evidence From China

This study matches data from the China Family Panel Studies (CFPS) with data on the transformation to industrial artificial intelligence (AI) in cities to explore the effect of this transformation on workers' mental health and its underlying mechanisms in China. The findings show the following...

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Autores principales: Yang, Siying, Liu, Kouming, Gai, JiaHui, He, Xiaogang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9171041/
https://www.ncbi.nlm.nih.gov/pubmed/35685756
http://dx.doi.org/10.3389/fpubh.2022.881827
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author Yang, Siying
Liu, Kouming
Gai, JiaHui
He, Xiaogang
author_facet Yang, Siying
Liu, Kouming
Gai, JiaHui
He, Xiaogang
author_sort Yang, Siying
collection PubMed
description This study matches data from the China Family Panel Studies (CFPS) with data on the transformation to industrial artificial intelligence (AI) in cities to explore the effect of this transformation on workers' mental health and its underlying mechanisms in China. The findings show the following (1). The transformation to industrial AI effectively alleviates multiple mental health problems and improves workers' mental health (2). Work intensity and wage income play an intermediary role in the relationship between the industrial AI transformation and workers' mental health (3). Potential endogeneity problems in the relationship between industrial AI and workers' mental health are considered, and robustness tests are conducted (including changing the dependent variables, independent variables and regression models). The main results and impact mechanisms remain robust and reliable. This study extends the research on the relationship between industrial AI and workers' health, which has important theoretical implications. Additionally, based on the Chinese context, this research has important implications for the current AI transformation in developing countries. Transition economies with labor shortages can achieve a win-win situation by promoting industrial AI to fill the labor gap and improve workers' mental health.
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spelling pubmed-91710412022-06-08 Transformation to Industrial Artificial Intelligence and Workers' Mental Health: Evidence From China Yang, Siying Liu, Kouming Gai, JiaHui He, Xiaogang Front Public Health Public Health This study matches data from the China Family Panel Studies (CFPS) with data on the transformation to industrial artificial intelligence (AI) in cities to explore the effect of this transformation on workers' mental health and its underlying mechanisms in China. The findings show the following (1). The transformation to industrial AI effectively alleviates multiple mental health problems and improves workers' mental health (2). Work intensity and wage income play an intermediary role in the relationship between the industrial AI transformation and workers' mental health (3). Potential endogeneity problems in the relationship between industrial AI and workers' mental health are considered, and robustness tests are conducted (including changing the dependent variables, independent variables and regression models). The main results and impact mechanisms remain robust and reliable. This study extends the research on the relationship between industrial AI and workers' health, which has important theoretical implications. Additionally, based on the Chinese context, this research has important implications for the current AI transformation in developing countries. Transition economies with labor shortages can achieve a win-win situation by promoting industrial AI to fill the labor gap and improve workers' mental health. Frontiers Media S.A. 2022-05-24 /pmc/articles/PMC9171041/ /pubmed/35685756 http://dx.doi.org/10.3389/fpubh.2022.881827 Text en Copyright © 2022 Yang, Liu, Gai and He. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Yang, Siying
Liu, Kouming
Gai, JiaHui
He, Xiaogang
Transformation to Industrial Artificial Intelligence and Workers' Mental Health: Evidence From China
title Transformation to Industrial Artificial Intelligence and Workers' Mental Health: Evidence From China
title_full Transformation to Industrial Artificial Intelligence and Workers' Mental Health: Evidence From China
title_fullStr Transformation to Industrial Artificial Intelligence and Workers' Mental Health: Evidence From China
title_full_unstemmed Transformation to Industrial Artificial Intelligence and Workers' Mental Health: Evidence From China
title_short Transformation to Industrial Artificial Intelligence and Workers' Mental Health: Evidence From China
title_sort transformation to industrial artificial intelligence and workers' mental health: evidence from china
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9171041/
https://www.ncbi.nlm.nih.gov/pubmed/35685756
http://dx.doi.org/10.3389/fpubh.2022.881827
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