China and the U.S. produce more impactful AI research when collaborating together
Not on the map. Why?
Abstract (arXiv)
Artificial Intelligence (AI) has become a disruptive technology, promising to grant a significant economic and strategic advantage to nations that harness its power. China, with its recent push towards AI adoption, is challenging the U.S.'s position as the global leader in this field. Given AI's massive potential, as well as the fierce geopolitical tensions between China and the U.S., several recent policies have been put in place to discourage AI scientists from migrating to, or collaborating with, the other nation. Nevertheless, the extent of talent migration and cross-border collaboration are not fully understood. Here, we analyze a dataset of over 350,000 AI scientists and 5,000,000 AI papers. We find that since 2000, China and the U.S. have led the field in terms of impact, novelty, productivity, and workforce. Most AI scientists who move to China come from the U.S., and most who move to the U.S. come from China, highlighting a notable bidirectional talent migration. Moreover, the vast majority of those moving in either direction have Asian ancestry. Upon moving, those scientists continue to collaborate frequently with those in the origin country. Although the number of collaborations between the two countries has increased since the dawn of the millennium, such collaborations continue to be relatively rare. A matching experiment reveals that the two countries have always been more impactful when collaborating than when each works without the other. These findings suggest that instead of suppressing cross-border migration and collaboration between the two nations, the science could benefit from promoting such activities.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 18 of its 110 references that are in the map. First posted on arXiv 21 Apr 2023.
Builds on
18 of 110 references.
References · 18
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6 more
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Built on by
Citing papers per year: 2023: 1; 2024: 1; 2025: 2; 2026: 2.
6 papers.
- 2024Large Language Models Reflect the Ideology of their Creatorscited by 57
- 2025Fair Foundation Models for Medical Image Analysis: Challenges and Perspectivescited by 3
- 2023Has China caught up to the US in AI research? An exploration of mimetic isomorphism as a model for late industrializerscited by 2
- 2025Disparities in Peer Review Tone and the Role of Reviewer Anonymitycited by 2
- 2026RAGnaroX: A Secure, Local-Hosted ChatOps Assistant Using Small Language Modelscited by 0
- 2026Polarization and Integration in Global AI Researchcited by 0
- 2026Polarization and Integration in Global AI Research19 Apr 2026
- 2026RAGnaroX: A Secure, Local-Hosted ChatOps Assistant Using Small Language Models27 Mar 2026
- 2025Disparities in Peer Review Tone and the Role of Reviewer Anonymity19 Jul 2025
- 2025Fair Foundation Models for Medical Image Analysis: Challenges and Perspectives24 Feb 2025
- 2024Large Language Models Reflect the Ideology of their Creators24 Oct 2024
- 2023Has China caught up to the US in AI research? An exploration of mimetic isomorphism as a model for late industrializers11 Jul 2023