AI and big data in economic regulation: A comparative analysis of China and the United States

Abstract

This paper examines the application of artificial intelligence (AI) and big data in economic regulation within China and the United States, highlighting the differing approaches and outcomes. In China, the centralized governance structure allows for the swift and uniform implementation of AI-driven strategies, optimizing government strategies, and balancing economic growth with social equity. The National Development and Reform Commission (NDRC) and the People's Bank of China (PBOC) are key players in utilizing AI to forecast economic trends and stabilize the economy. Conversely, the U.S. employs a decentralized approach, with AI applications driven primarily by the private sector and academia. The Federal Reserve leverages AI for policy decisions, while private firms use predictive models to enhance market strategies. Big data analysis supports decision-making in both nations, but differing governance structures lead to unique challenges and benefits. This study compares the centralized and decentralized systems, assessing their impact on economic performance and policy flexibility. The findings provide insights into how AI and big data can be optimized for economic regulation, offering lessons for other countries in adopting these technologies.