As humanity enters an epoch defined by artificial intelligence and data, AI transcends its role as a mere technological tool, emerging as a force poised to reshape the fabric of human existence, ethical paradigms, and societal structures. We humans are standing at a pivotal crossroads.
An international dialogue concluded in Shanghai on April 25, 2025, as experts from academia, industry, and policy converged to address critical challenges in fostering global collaboration amid rapid AI advancement, as a crucial exploration for the cutting-edge issues.
Hosted by Fudan University’s Research Center for Technological Innovation Strategy and co-supported by the Global Industry Organization (GIO) and Wanbang Digital Energy Co., Ltd., the sub-forum “Navigating International Cooperation and Innovation in the Era of Technological Transformation” drew extensive attention for its focus on bridging divides in AI governance, data space construction, and sustainable innovation.
Charting Pathways for Inclusive AI Collaboration
In his welcome speech, CHEN Zhimin, Vice President of Fudan University, underscored the transformative potential of artificial intelligence, stressing the need to translate technological advancements into tangible global cooperation.
“Only when we can leverage artificial intelligence technology and apply it to various scenarios can we further promote international cooperation and innovation in this AI era,” he noted, emphasizing that ethical deployment and inclusive innovation must remain central to technological progress.
CHEN Zhimin
William XU, professor of Fudan Development Institute and the Research Center for Technological Innovation Strategy, outlined forum’s core agenda: fostering industrial cooperation and governance in the AI era, and constructing an open, resilient framework to harness AI’s industrial potential.
“This forum seeks to offer actionable insights, practical methodologies, and tangible support to less-developed regions or those temporarily lacking in computational capacity,” he said, highlighting the urgency of aligning global efforts to bridge the digital divide.
William XU
Driving Innovation by AI's Transformative Power and Action Plans
German industry consultant Juergen Grotepass focused on the role of AI-driven manufacturing in promoting the innovative upgrading and remarkable development of multi-level businesses in the global supply chain.
Grotepass spotlighted the EU’s recent “AI Continental Action Plan” —a 200 billion Euro initiative earmarking funds for super-factories and startup support, as a landmark in scaling industrial AI. “This plan not only upskills workforces but also modernizes legacy infrastructure,” he observed.
Juergen Grotepass
Drawing on Metcalfe’s Law, Luis Jorge Romero, Chief Strategy Officer of Comentropy, notes that the value of collaborative networks grows exponentially with the number of nodes, advocating for the construction of open and shared digital ecological networks in global industries and society to reduce innovation costs through technology inclusion and avoid zero-sum games.
Federico Menna, CEO of the European Institute of Innovation and Technology’s Digital Institute, warned of imbalanced AI investments, noting that 70% is concentrated on basic models and talent, leaving high-performance computing (HPC) and applications underfunded. He called for strategic autonomy in AI capabilities, framing the technology as a foundational pillar of global competitiveness rather than a mere tool. On ethics, Menna emphasized diversity, inclusion, morality, and skills as non-negotiable principles, urging sustained investment in workforce training.
Federico Menna
Data Governance as the Cornerstone for Future Sustainable AI Development
Chinese experts highlighted progress and challenges in unlocking data’s potential. LIU Dong, director of the China Future Internet Engineering Center, described data and AI as inseparable pillars of intelligent societies, noting that while China has accelerated data circulation, vast private-sector datasets remain underutilized.
LIU Dong
Huawei’s CHEN Liang echoed this, stressing that robust data governance—encompassing copyright, bias mitigation, privacy and cybersecurity—is pivotal to the AI industry development. He proposed a three-pronged approach combining technological solutions, engineering standards, and regulatory frameworks to establish trust in data ecosystems, calling for global consensus on standardization and certification mechanisms.
CHEN Liang
Embracing the Physical AI World and the Global Compute Alliance Initiative
South Korean scholars introduced novel perspectives on AI’s expansion into the physical realm. Seoul National University’s Byoung-Tak Zhang pointed out that “Humanoid robots need real-time perception, cognition, and action cycles. Moreover, they must continuously learn and adapt to the real world due to the constantly changing environment.” He argued that humanoid robotics and real-world automation demand reimagined computing architectures, necessitating international cooperation akin to OPEC to coordinate computational power distribution.
Yoo Chang Dong from Korea Advanced Institute of Science and Technology focused on fairness in generative AI, advocating automated bias-detection toolkits to address systemic inequalities in data processing. Manual oversight is insufficient; we need scalable, machine-aided solutions to ensure equitable outcomes.
Byoung-Tak Zhang
Yoo Chang Dong
Building Trust for a Thriving Data Ecosystem
International policymakers emphasized trust as the cornerstone of cross-border data exchange. China Academy of Information and Communications Technology’s WEI Sha outlined three hurdles to data sharing—lack of trust, inadequate incentives, and technical barriers—and detailed China’s Sustainable Data Space Action Plan, which aims to maximize circulation through capability-building and regulatory safeguards.
WEI Sha
MING Xinguo from the Department of Industrial Engineering and Management, Shanghai Jiao Tong University, outlined his opinions on integrating large-scale models with knowledge graphs, carrying out human intervention, and improving efficiency in the human-machine interaction state based on his in-depth exchanges with industrial enterprises.
MING Xinguo
Sebastian Steinbuß, the chief technology officer of the International Data Space Association, pointed out four core points of the data space—core rules requiring the consensus of all, an organization-centered perspective, mutual trust among participants and scalability. Japan’s Noboru Koshizuka of the University of Tokyo linked data governance to the vision of “Society 5.0”, a hyper-connected ecosystem merging physical and digital realms.
Sebastian Steinbuß
Noboru Koshizuka
A Crossroads for Global AI Governance
As the forum closed, participants highlighted a shared recognition: the “super-AI” era demands collective action to balance innovation with accountability.
From EU industrial plans to Asian data sovereignty frameworks, the discussions underscored a need for adaptive governance, inclusive investment, and technological interoperability. With stakeholders from China, Europe, and East Asia emphasizing common goals despite regional nuances, the dialogue served as a testament to the power of multilateral cooperation in shaping a sustainable technological future, one where innovation is both transformative and equitable.
Reported by the Media Center of Fudan University
Writer: FENG Zihan
Proofreader: WANG Jingyang
Editor: WANG Mengqi, LI Yijie
