Artificial intelligence and urban employment in China's agricultural Sector: Conditions for job creation across skill levels

Abstract

With the development of artificial intelligence, widespread concerns have arisen about labor substitution. This study conducts a novel analysis of the dual impact of artificial intelligence on urban employment within China's agricultural sector, and presents the sensitivity coefficient to identify the conditions under which artificial intelligence shifts from displacing jobs to generating new employment opportunities, using panel data from 31 provinces between 2010 and 2019. The study assumes that the sensitivity coefficient approaches zero between change of medium-skilled labor to change artificial intelligence capital, which causes employment creation. Therefore, the study tests the assumption, and get three key findings. First, a 1 % increase of artificial intelligence capital reduces urban employment in China's agriculture sector by 0.205 % for the low-skilled labor, 0.147 % for medium-skilled labor and 0.809 % for high-skilled labor. Second, by categorizing labor's skill levels into seven groups based on educational attainment, this study identifies that a positive creation effect is generated for high-skilled labor with graduate level, resulting in a 0.138 % increase in employment. Finally, mechanism testing reveals that artificial intelligence promotes employment growth among high-skilled labor with graduate level in China's agricultural sector by reducing the sensitivity coefficient, with the mediating effect accounting for 42.91 %. To mitigate the negative effects on low- and medium-skilled workers while fostering job creation among high-skilled labor, artificial intelligence should be implemented gradually and accompanied by targeted retraining programs.