Skill Transformation and Precarious Employment in China: A New Form of Segmented Labor Market in the Era of Artificial Intelligence

In recent years, the profound impact of Artificial Intelligence and related technological changes on China’s labor market has garnered increasing scholarly attention, particularly regarding the implications of AI on precarious employment (Xie et al., 2021; Zhou et al., 2020; Wang et al., 2022). This study employed large-scale online job advertisement data to investigate the skill requirements and its impact on precarious employment in China. Utilizing unsupervised machine learning methodologies, detailed skill sets were identified and categorized based on real-time labor market data to reduce biases and offer a more precise evaluation of occupational skill structures. By integrating insights on these structures derived from big data with individual-level information sourced from the China General Social Survey (2012-2021), this study investigated the impact of skill transformation on the prevalence of precarious employment. The analysis yielded three key findings: 1)Varied skill dimensions have distinct effects on job security, with individuals engaged in STEM-skill-intensive occupations exhibiting lower vulnerability to precarious employment, while those in manual-skill-intensive and service-skill-intensive occupations facing heightened job insecurity. 2) The cross-wave analysis revealed a growing positive impact of creative-operating skills in mitigating the risk of precarious employment, alongside an escalating negative impact of routine-cognitive skills. 3) Classification of occupations into competitive-skill and uncompetitive-skill categories highlighted a widening gap in the likelihood of precarious employment between these two groups. These findings suggest the emergence of a segmented labor market driven by skill transformation in China amidst the era of artificial intelligence.