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Proceedings of the 3rd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2024, March 29–31, 2024, Wuhan, China

Research Article

Quantifying the Impact of Artificial Intelligence Technology on High Quality Employment

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  • @INPROCEEDINGS{10.4108/eai.29-3-2024.2347436,
        author={Fu  Xian},
        title={Quantifying the Impact of Artificial Intelligence Technology on High Quality Employment},
        proceedings={Proceedings of the 3rd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2024, March 29--31, 2024, Wuhan, China},
        publisher={EAI},
        proceedings_a={ICBBEM},
        year={2024},
        month={6},
        keywords={artificial intelligence technology high quality employment},
        doi={10.4108/eai.29-3-2024.2347436}
    }
    
  • Fu Xian
    Year: 2024
    Quantifying the Impact of Artificial Intelligence Technology on High Quality Employment
    ICBBEM
    EAI
    DOI: 10.4108/eai.29-3-2024.2347436
Fu Xian1,*
  • 1: Sichuan University Jinjiang College
*Contact email: xianfu800@163.com

Abstract

The labor market has been particularly impacted by the rapid development of artificial intelligence technology. This impact on employment has a variety of characteristics that will not only cause changes in the quantity of employment but also open up opportunities to raise the quality of employment. This study, which is based on the current state of AI and China's employment development, focuses on the effect of the level of AI development on the quality of employment, uses a sample of China's provincial data from 2010 to 2019 and empirically investigates the relationship between the level of AI development and the quality of employment in China using multiple regression analysis. The findings demonstrate that the quality of employment is significantly positively impacted by the state of artificial intelligence development.

Keywords
artificial intelligence technology high quality employment
Published
2024-06-07
Publisher
EAI
http://dx.doi.org/10.4108/eai.29-3-2024.2347436
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