人工智能、偏向型技术进步与技能溢价的互动机制

The Interaction Mechanism of Artificial Intelligence, Biased Technological Progress, and Skill Premium

摘要:

人工智能的广泛应用改变社会资源配置模式，并且技术的偏向性深刻影响着劳动力技能溢价。但现有的研究缺乏从偏向型技术进步视角探究人工智能所带来的偏向性，并从两种不同的偏向性探究其对技能溢价的不同影响。本研究根据偏向型技术进步理论，基于技能偏向型和任务偏向型两个不同的视角从受教育水平和产业结构转型对技能溢价的不同影响开展研究。以中国微观城市为研究对象，采用2015－2020年的面板数据探究人工智能、受教育水平、产业结构转型和技能溢价的作用关系。研究结果表明：人工智能对受教育水平、产业结构转型具有显著的正向影响，受教育水平对技能溢价具有显著的正向影响，而产业结构转型对技能溢价具有显著的负向影响。因此提出应加强对中、低技能劳动力的培训与教育，强化制造业产业结构转型升级，从而抑制技能溢价的持续上升。

Abstract:

The widespread application of artificial intelligence has altered the mode of social resource allocation, and the biased nature of technology profoundly influences the skill premium of the labor force. However, existing studies have not sufficiently investigated the bias characteristics inherent in artificial intelligence from the perspective of biased technological progress, nor have they systematically explored the differential impacts of these two distinct types of bias on skill premiums. This study, based on the theory of skill-biased technological progress, explores the impact of education level and industrial structure transformation on skill premium from two different perspectives: skill-biased and task-biased technological change. This study takes China's micro-cities as the research object, and uses panel data from 2015 to 2020 to explore the relationship between artificial intelligence, education level, industrial structure transformation and skill premium. The research results show that artificial intelligence has a significant positive impact on education level and industrial structure transformation, education level has a significant positive impact on skill premium, and industrial structure transformation has a significant negative impact on skill premium. Enhancing training and education for mid- and low-skilled labor, as well as strengthening the transformation and upgrading of the manufacturing industry structure, can curb the continuous rise of the skill premium.