Polarization and Integration in Global AI Research

• URL: http://arxiv.org/abs/2604.17602v1
• Date: Sun, 19 Apr 2026 20:21:25 GMT
• Title: Polarization and Integration in Global AI Research
• Abstract summary: We measure the processes of polarization and integration in the global AI research over three decades.<n>We find that the US and China have long diverged in both dimensions, forming two poles around which global AI research increasingly revolves.<n> Developing and further developed countries, however, only integrate with China, signaling its expanding influence over the international AI research landscape.
• Score: 1.1470070927586018
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The AI race amplifies security risks and international tensions. While the US restricts mobility and knowledge flows, challenges regulatory efforts to protect its advantage, China leads initiatives of global governance. Both strategies depend on cross-country relationships in AI innovation; yet, how this system evolves is unclear. Here, we measure the processes of polarization and integration in the global AI research over three decades by using large-scale data of scientific publications. Comparing cross-country collaboration and citation links to their random realizations, we find that the US and China have long diverged in both dimensions, forming two poles around which global AI research increasingly revolves. While the United Kingdom and Germany have integrated exclusively with the US, many European countries have converged with both poles. Developing and further developed countries, however, only integrate with China, signaling its expanding influence over the international AI research landscape. Our results inform national science policies and efforts toward global AI regulations.

Related papers

• Owning the Intelligence: Global AI Patents Landscape and Europe's Quest for Technological Sovereignty [0.13390068757738613]
  China leads in patent volumes, while the United States dominates in citation impact and technological influence.<n>Europe accounts for a limited share of AI patents but exhibits signals of relatively high patent quality.<n>EU membership does not significantly enhance intra-European knowledge diffusion.
  arXiv  Detail & Related papers  (2025-12-22T16:52:36Z)
• Advancing Science- and Evidence-based AI Policy [163.43609502905707]
  This paper tackles the problem of how to optimize the relationship between evidence and policy to address the opportunities and challenges of AI.<n>An increasing number of efforts address this problem by often either (i) contributing research into the risks of AI and their effective mitigation or (ii) advocating for policy to address these risks.
  arXiv  Detail & Related papers  (2025-08-02T23:20:58Z)
• The Singapore Consensus on Global AI Safety Research Priorities [128.58674892183657]
  "2025 Singapore Conference on AI (SCAI): International Scientific Exchange on AI Safety" aimed to support research in this space.<n>Report builds on the International AI Safety Report chaired by Yoshua Bengio and backed by 33 governments.<n>Report organises AI safety research domains into three types: challenges with creating trustworthy AI systems (Development), challenges with evaluating their risks (Assessment) and challenges with monitoring and intervening after deployment (Control)
  arXiv  Detail & Related papers  (2025-06-25T17:59:50Z)
• The California Report on Frontier AI Policy [110.35302787349856]
  Continued progress in frontier AI carries the potential for profound advances in scientific discovery, economic productivity, and broader social well-being.<n>As the epicenter of global AI innovation, California has a unique opportunity to continue supporting developments in frontier AI.<n>Report derives policy principles that can inform how California approaches the use, assessment, and governance of frontier AI.
  arXiv  Detail & Related papers  (2025-06-17T23:33:21Z)
• Bridging the Artificial Intelligence Governance Gap: The United States' and China's Divergent Approaches to Governing General-Purpose Artificial Intelligence [0.0]
  U.S. and China are among the world's top players in the development of advanced artificial intelligence (AI) systems.<n>A look at U.S. and Chinese policy landscapes reveals differences in how the two countries approach the governance of AI systems.
  arXiv  Detail & Related papers  (2025-06-04T02:24:27Z)
• Open and Sustainable AI: challenges, opportunities and the road ahead in the life sciences (October 2025 -- Version 2) [49.142289900583705]
  We review the increased erosion of trust in AI research outputs, driven by the issues of poor reusability.<n>We discuss the fragmented components of the AI ecosystem and lack of guiding pathways to best support Open and Sustainable AI.<n>Our work connects researchers with relevant AI resources, facilitating the implementation of sustainable, reusable and transparent AI.
  arXiv  Detail & Related papers  (2025-05-22T12:52:34Z)
• Evolving landscape of US-China science collaboration: Convergence and divergence [0.0]
  The US and China have significantly fortified their collaboration across diverse scientific disciplines. Recent reports hint at a potential decline in collaboration between these two giants. This study delves into the evolving landscape of interaction between the US and China over recent decades.
  arXiv  Detail & Related papers  (2023-09-10T14:11:46Z)
• Has China caught up to the US in AI research? An exploration of mimetic isomorphism as a model for late industrializers [9.03136346887569]
  We examine China's AI development process, demonstrating that it is characterized by rapid learning and differentiation. By 2018, the time lag between China and the USA in addressing AI research topics had evaporated. This finding suggests that China has effectively bridged a significant knowledge gap and could potentially be setting out on an independent research trajectory.
  arXiv  Detail & Related papers  (2023-07-11T19:59:54Z)
• Artificial intelligence adoption in the physical sciences, natural sciences, life sciences, social sciences and the arts and humanities: A bibliometric analysis of research publications from 1960-2021 [73.06361680847708]
  In 1960 14% of 333 research fields were related to AI, but this increased to over half of all research fields by 1972, over 80% by 1986 and over 98% in current times. In 1960 14% of 333 research fields were related to AI (many in computer science), but this increased to over half of all research fields by 1972, over 80% by 1986 and over 98% in current times. We conclude that the context of the current surge appears different, and that interdisciplinary AI application is likely to be sustained.
  arXiv  Detail & Related papers  (2023-06-15T14:08:07Z)
• China and the U.S. produce more impactful AI research when collaborating together [2.115100245425281]
  We analyze a dataset of over 350,000 AI scientists and 5,000,000 AI papers. Most AI scientists who move to China come from the U.S., and most who move to the U.S. come from China. Although the number of collaborations between the two countries has increased since the dawn of the millennium, such collaborations continue to be relatively rare.
  arXiv  Detail & Related papers  (2023-04-21T16:47:51Z)
• Fairness in AI and Its Long-Term Implications on Society [68.8204255655161]
  We take a closer look at AI fairness and analyze how lack of AI fairness can lead to deepening of biases over time. We discuss how biased models can lead to more negative real-world outcomes for certain groups. If the issues persist, they could be reinforced by interactions with other risks and have severe implications on society in the form of social unrest.
  arXiv  Detail & Related papers  (2023-04-16T11:22:59Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.