| 王林辉,冯彤,曹宇彤.数字技术对不同类型职业技能的非对称性冲击——基于人工智能与非人工智能技术比较的视角[J].数量经济技术经济研究,2026,(5):79-104 | | 数字技术对不同类型职业技能的非对称性冲击——基于人工智能与非人工智能技术比较的视角 | | The Asymmetric Effects of Digital Technologies on Different Types of Occupational Skills: Evidence from a Comparison between AI and Non-AI Technologies | | | | DOI： | | 中文关键词: 人工智能技术 非人工智能类数字技术 劳动者职业技能岗位转换 | | 英文关键词: Artificial Intelligence Non-AI Digital Technologies Occupational Skills Job Transitions | | 基金项目: | | | 中文摘要: | | 数字技术创造新岗位并重构工作任务内容，引致劳动者职业技能需求变化。本文采用微观个体数据探讨人工智能技术和非人工智能类数字技术对技术类、社交类和思维类等职业技能的影响。研究发现，人工智能技术通过任务去常规化和劳动者职业转换增强了劳动者的社交类技能，而非人工智能类数字技术通过促进劳动者转入新职业提升技术类技能。人工智能技术增加了合作能力需求，拓展劳动者的有效技能宽度，但降低了技能深度；非人工智能类数字技术促使劳动者更加依赖专业技术能力和计算机能力，从而增加了技能深度，但并未拓展有效技能宽度。本文揭示了不同类型数字技术对职业技能的差异化作用，为劳动者及时应对新兴技术冲击提供理论指导。 | | 英文摘要: | | The rapid development and widespread adoption of digital technologies have increasingly affected the labor market. These technologies not only transform the tasks within traditional occupations but also create new occupations, thereby necessitating some new occupational skills. While the existing literature has examined the substitution, complementarity, and creation effects of these technologies on job tasks, a quantitative analysis of their impact on workers’ occupational skills is lacking. Therefore, analyzing how digital technologies reshape the new skills required is essential.Using individual-level data from the China Labor-force Dynamics Survey, this study investigates how AI and non-AI digital technologies reshape workers’ skills across the following dimensions: technology skills, social skills, thinking skills, effective skill breadth, skill depth, and workers’ reliance on specific skills. We further explore the effects of AI and non-AI digital technologies on workers’ job mobility by focusing on occupational skill proximity and the difficulty of job mobility. Our findings shed light on the following key points: First, AI increases social skills by promoting the nonroutinization of job tasks and the occupational transformation of workers. In contrast, non-AI digital technologies enhance technology skills but degrade social skills by pushing workers into new occupations. Second, AI fosters workers’ reliance on cooperation ability and expands effective skill breadth but reduces skill depth, whereas non-AI digital technologies increase the reliance of workers on professional technical ability and computer ability, thereby deepening worker skills but not broadening the effective skill breadth. Ultimately, under the impact of digital technology, workers often switch between jobs that require similar skills. AI can also help workers move to jobs with higher skill demands, while non-AI digital technologies tend to lead workers to jobs with only minor skill upgrades or significant downgrades.Building on these empirical findings, this study offers several contributions to the literature as follows: First, departing from the existing literature that largely examines how a single technology influences workers’ occupational skills, we compare the differential effects of AI and non-AI digital technologies on workers’ technology, social, and thinking skills. Second, this study explores the mechanisms through which AI and non-AI digital technologies affect workers’ occupational skills from the perspectives of task reshaping and occupational switching. Third, we develop an effective skill-breadth index, a skill-depth index, and a single-skill dependence index. Building on these measures, we examine how AI and non-AI digital technologies affect effective skill breadth, skill depth, and dependence on each specific skill, exploring the distinct roles of different types of digital technologies in shaping workers’ skill structures. Finally, to deepen the understanding of technological change and the evolution of labor market structure, we analyze the differential effects of AI and non-AI digital technologies on workers’ job transitions in terms of skill similarity, the direction of skill change, and skill distance.The findings of this study provide useful insights for guiding workers to timely master skills suitable for the development of technology to promote the effective accumulation of human capital. First, firms should adopt digital technologies consistent with their resource endowments and provide targeted training to upgrade employees’ skills. On the one hand, AI adoption calls for human-machine collaboration, combining computational capacity with workers’ creativity and judgment. On the other hand, non-AI technologies require greater emphasis on technology skills such as equipment maintenance, data analysis, and system optimization. Second, education departments should strengthen workers’ skill development to improve their adaptability in the context of technological revolution. Specifically, flexible curricula that not only focus on technology skills development for working with digital systems but also strengthen workers’ social abilities in teamwork and communication should be developed. Moreover, lifelong learning systems should be improved to provide convenient retraining channels. Such reforms can strengthen workers’ adaptability to technological change and reduce the risks associated with excessive specialization. Third, human resources management should help workers optimize the skill structure to better cope with technological shocks. By cooperating with education authorities and training providers, these departments can construct an occupational skills training platform to help the workforce develop multidimensional skill portfolios to increase their career development opportunities and enhance their adaptability to occupational mobility. Furthermore, services such as career guidance, vocational training, and skills certification should be provided to facilitate smooth job transitions and promote sustainable career development. | | 查看全文 |
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