# Artificial Intelligence and Employment: A Delicate Balance Between Progress and Quality in China
## 5 Discussion
### Comparison with Literature  
There have been numerous interesting results that add unique contributions to the body of knowledge of AI's effects on the quality of employment [16; 40; 41]. Above all, it highlights how important policy support is for reducing regional inequities. Government initiatives encouraging technological adoption and industry upgrading greatly improve the quality of jobs in central and western China. This point of view is not as often mentioned in the literature; hence, it offers a significant addition. Moreover, the research reveals how complicated and context-dependent artificial intelligence is, and solid empirical validation over several tests validates its conclusions. The results emphasize skill polarization and regional variability in line with earlier studies. In line with previous research, it implies that the adoption of artificial intelligence disproportionately advantages highly trained individuals while displacing middle- and low-skilled labor, hence widening the skills gap [40; 41; 42; 43]. By pointing out that automation has a negative impact on industrially developed eastern regions while boosting productivity and creating jobs in less developed central and western regions, it also supports studies on developing economies, including those conducted in Brazil and India [32; 44; 45]. Moreover, it supports findings about income inequality, which show that the adoption of AI results in productivity gains for highly trained individuals and salary stagnation or decreases for low-skilled workers. Nevertheless, this study deviates from a large portion of the literature by concluding that AI has a negligible practical impact on the quality of employment [41; 42]. This study presents a fair view that helps to explain the small effect size of structural and geographical traits exclusive to China, even if the general conversation usually predicts disruptive changes in labor markets [41; 42; 43; 44]. This disparity highlights the need for context in assessing the larger effects of artificial intelligence. The results on AI's overall effect on job quality, including its statistically significant but limited practical implications, were found to be average in contrast with more disruptive estimations in the literature. This well-rounded perspective lends credence to the idea that politics and geography greatly influence the implications of AI, which are not always revolutionary. While much of the existing literature on AI and employment quality has concentrated on developed economies, such as the U.S. and Germany, where AI adoption has primarily been associated with productivity gains in high-tech industries, this study offers a novel perspective by examining the impact of AI in China, a developing economy with diverse regional contexts. Previous studies from the BRICS nations (e.g., Brazil and India) also highlight the role of AI in industrial upgrading but show mixed results regarding its impact on employment quality [44; 45]. This study expands upon these works by emphasizing regional disparities within China and how industrial structure and government policy can mediate AI's effects on employment outcomes. Therefore, our findings not only contribute to the understanding of AI in developing economies but also complement studies in developed countries by highlighting the importance of regional context and policy interventions in shaping labor market outcomes. Unlike [PERSON] and [PERSON]'s (2020) findings in the U.S., China's smaller effect size (\(-0.00003\) vs. \(-0.0004\)) may reflect the regional policies buffering low-skilled workers [2]. For instance, central/western provinces' industrial upgrading programs (e.g., smart manufacturing subsidies) offset displacement, highlighting the role of state intervention in moderating AI's labor market impacts. In line with more general social, environmental, and financial objectives, the development of sustainable precision manufacturing marks a major turning point for raising employment quality in China.