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This chapter examines the challenges facing international neuroscience-AI collaboration amid rising nationalism and geopolitical fragmentation. This chapter argues that traditional centralized research networks create profound structural vulnerabilities when nationalist policies restrict scientific cooperation. In these networks, one major power serves as the dominant hub for international partnerships. Using detailed network architecture analysis, the author demonstrates how centralized models fragment entirely when the dominant hub adopts restrictive policies. In contrast, distributed models maintain functionality through multiple direct partnerships and redundant connectivity pathways. The analysis draws extensively on COVID-19 research networks as a natural experiment, showing how some scientific communities successfully preserved international cooperation through bottom-up connections, neutral intermediaries, and rapid adoption of technical solutions including federated learning and privacy-preserving computational methods that enable collaborative research without requiring sensitive data to cross national boundaries. This chapter examines multistakeholder governance frameworks that extend beyond traditional government-to-government agreements. These frameworks incorporate research institutions, funding agencies, patient advocacy groups, and industry partners, creating multiple channels for continued cooperation even when formal diplomatic relationships deteriorate. Technical innovations including regulatory interoperability frameworks and federated analysis systems are presented as concrete mechanisms for overcoming political barriers while maintaining scientific integrity. The author concludes by identifying key principles for building resilient global science: structural distribution of leadership and capabilities across multiple jurisdictions, proactive relationship maintenance during stable periods, and strategic deployment of technical solutions to circumvent political constraints. This chapter maintains a practical focus on implementable solutions rather than idealistic frameworks, acknowledging that nationalist pressures in neuroscience-AI research seem likely to persist while demonstrating that essential international collaboration can be preserved through appropriate institutional adaptations.

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Global Collaboration in an Age of Nationalism

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  • 发表日期：

    2025年

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  • Thorsten Rudroff

摘要

This chapter examines the challenges facing international neuroscience-AI collaboration amid rising nationalism and geopolitical fragmentation. This chapter argues that traditional centralized research networks create profound structural vulnerabilities when nationalist policies restrict scientific cooperation. In these networks, one major power serves as the dominant hub for international partnerships. Using detailed network architecture analysis, the author demonstrates how centralized models fragment entirely when the dominant hub adopts restrictive policies. In contrast, distributed models maintain functionality through multiple direct partnerships and redundant connectivity pathways. The analysis draws extensively on COVID-19 research networks as a natural experiment, showing how some scientific communities successfully preserved international cooperation through bottom-up connections, neutral intermediaries, and rapid adoption of technical solutions including federated learning and privacy-preserving computational methods that enable collaborative research without requiring sensitive data to cross national boundaries. This chapter examines multistakeholder governance frameworks that extend beyond traditional government-to-government agreements. These frameworks incorporate research institutions, funding agencies, patient advocacy groups, and industry partners, creating multiple channels for continued cooperation even when formal diplomatic relationships deteriorate. Technical innovations including regulatory interoperability frameworks and federated analysis systems are presented as concrete mechanisms for overcoming political barriers while maintaining scientific integrity. The author concludes by identifying key principles for building resilient global science: structural distribution of leadership and capabilities across multiple jurisdictions, proactive relationship maintenance during stable periods, and strategic deployment of technical solutions to circumvent political constraints. This chapter maintains a practical focus on implementable solutions rather than idealistic frameworks, acknowledging that nationalist pressures in neuroscience-AI research seem likely to persist while demonstrating that essential international collaboration can be preserved through appropriate institutional adaptations.