Huo Qingqing, Ruan Jing, Cui Yan
School of Statistics, Capital University of Economics and Business, Beijing, China.
School of Data Science, Capital University of Economics and Business, Beijing, China.
Front Artif Intell. 2024 Mar 6;7:1337264. doi: 10.3389/frai.2024.1337264. eCollection 2024.
Artificial intelligence (AI), as an important engine for promoting high-quality economic development, should not be overlooked in terms of its impact on the employment of the labor force while promoting the digital and intelligent transformation of industries. In the face of the complex international environment and non-systemic shocks, it is of great significance to explore whether it is "machine replacement" or "job creation" in the process of the integration of AI and industry, as well as the impact of technological progress on the employment pattern of the labor force, in order to promote the economic development, respond to and solve the employment problem. It is of great significance to promote economic development and cope with and solve the employment problem. Based on the task model, this paper analyses the mechanism of the impact of AI on the employment pattern of manufacturing industry. Meanwhile, based on the provincial panel data of China's manufacturing industry from 2011 to 2020, it empirically examines the impact of AI on the total employment, employment structure and employment quality of the labor force, and analyses the multiple responses of AI on the employment pattern of the manufacturing industry. The study shows that: Firstly, the level of development of AI and the total amount of employment is a positive U-shaped relationship, the short term is dominated by the substitution effect, and the long term is dominated by the creation effect; Secondly, with regard to the employment structure, low-skilled labor is more likely to be replaced. The financial, accommodation and catering industries are relatively less affected by the spillover effects of the manufacturing industry; Third, with regard to the employment quality, the gap between urban and rural incomes has eased, with per capita net income of rural residents rising to a higher degree than per capita disposable income of urban residents. Thus, in order to further address the impact of AI on the employment patterns of the labor force, the level of AI development should be increased while expanding employment channels, paying attention to labor force skills training, reinforcing the leading role of developed regions, and accelerating regional integration and urban-rural integration, so as to share the dividends of technological progress.
人工智能（AI）作为推动高质量经济发展的重要引擎，在推动产业数字化、智能化转型的同时，其对劳动力就业的影响不容忽视。面对复杂的国际环境和非系统性冲击，探究人工智能与产业融合过程中究竟是“机器换人”还是“创造就业”，以及技术进步对劳动力就业格局的影响，对于促进经济发展、应对和解决就业问题具有重要意义。这对于推动经济发展以及应对和解决就业问题意义重大。本文基于任务模型分析了人工智能对制造业就业格局的影响机制。同时，基于2011—2020年中国制造业省级面板数据，实证检验了人工智能对劳动力总就业、就业结构和就业质量的影响，并分析了人工智能对制造业就业格局的多重反应。研究表明：一是人工智能发展水平与就业总量呈正U型关系，短期内以替代效应为主，长期以创造效应为主；二是就业结构方面，低技能劳动力更易被替代，金融、住宿餐饮行业受制造业溢出效应影响相对较小；三是就业质量方面，城乡收入差距有所缓和，农村居民人均纯收入提升幅度高于城镇居民人均可支配收入。因此，为进一步应对人工智能对劳动力就业格局的影响，应在提高人工智能发展水平的同时，拓宽就业渠道，注重劳动力技能培训，强化发达地区的引领作用，加快区域一体化和城乡一体化进程，以共享技术进步红利。
