# Artificial Intelligence and Employment: A Delicate Balance Between Progress and Quality in China
## 1 Introduction  
The rapid advancement of artificial intelligence (AI) is reshaping global labor markets, with profound implications for employment quality, productivity, and economic development. As countries worldwide embrace AI-driven technologies, the transformation of work and employment structures has become a central topic of discussion. In the U.S., AI adoption has accelerated skill polarization, with high-tech hubs like Silicon Valley creating high-paying jobs while displacing routine roles in manufacturing and logistics. The EU's Digital Compass initiative emphasizes AI ethics and worker reskilling to mitigate displacement risks, while Southeast Asian economies like Vietnam and Indonesia face similar tensions between industrial automation and labor-intensive growth. Initiatives such as Society 5.0 in Japan, Industry 4.0 in Germany, and AI regulations in the UK highlight the strategic importance of AI as a key enabler of innovation and productivity growth [1,2]. However, the adoption of AI also raises critical concerns about job displacement, skill polarization, and regional disparities in employment quality, particularly in developing economies like China.  
China, as a global leader in AI development, offers a critical lens to examine these dynamics. Its labor market--marked by regional economic disparities, varied industrial structures, and rapid technological adoption--reflects challenges faced by other developing economies undergoing digital transitions, such as India's gig economy expansion and Brazil's manufacturing automation struggles [3, 4, 5, 6, 7, 8, 9, 10]. While national initiatives like the New Generation AI Development Plan aim to leverage AI for sustainable growth, theyalso underscore socioeconomic risks, including job insecurity and uneven skill distribution. This study's focus on China's prefecture-level cities provides insights applicable to regions worldwide where infrastructure gaps, industrial composition, and policy frameworks shape AI's labor market impacts.  
This study seeks to address this gap by investigating the regional disparities in the impact of AI on employment quality across China's prefecture-level cities from 2011 to 2019. Specifically, we aim to answer the following research questions:  
1. How does AI adoption affect employment quality in different regions of China, and what are the underlying mechanisms driving these effects?
2. What role do regional economic structures, industrial composition, and policy interventions play in moderating the impact of AI on employment quality?
3. How can policymakers design targeted interventions to mitigate the negative effects of AI on employment quality while promoting sustainable labor market development?  
By addressing these questions, this study contributes to the global discourse on AI and labor market dynamics, offering empirical evidence on the heterogeneous effects of AI adoption across regions. Furthermore, it provides practical recommendations for policymakers to align AI-driven technological advancements with sustainable employment strategies, ensuring a balanced approach to innovation and labor market resilience.