ArticleScientific reports2024
China and the U.S. produce more impactful AI research when collaborating together.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed.
- Review
- Competition and Collaboration in the AI Race: Country-LevelDirectional Evidence for Risk Monitoring and Policy.Risk analysis : an official publication of the Society for Risk Analysis · 2026Article
- Global Research Landscape and Thematic Evolution of Fungi-Derived Antimicrobials Against Methicillin-ResistantBiology · 2026Review
- Artificial Intelligence in Anterior Cruciate Ligament Tear Diagnosis: A Bibliometric Analysis of the 50 Most Cited Studies.The Indian journal of radiology & imaging · 2026Review
- Application of Artificial Intelligence in Nursing: A Bibliometric Analysis of Global Research Trends.Healthcare (Basel, Switzerland) · 2026Review
- Large language models reflect the ideology of their creators.NPJ artificial intelligence · 2026Article
- Shifting power asymmetries in scientific teams reveal China's rising leadership in global science.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Evolution of artificial intelligence in healthcare: a 30-year bibliometric study.Frontiers in medicine · 2024Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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