A recent open letter organized by the Stanford Digital Economy Lab, signed by over 200 leading economists and AI researchers, including 16 Nobel laureates, issued a stark warning about the transformative economic impact of artificial intelligence. However, as highlighted in an opinion piece published in the South China Morning Post, the letter suffered from a glaring omission: not a single signatory was from China.
The SCMP article, co-authored by Allen Huang of the Hong Kong University of Science and Technology (HKUST) and Frederik Anseel, argues that this absence is symptomatic of a broader, systemic flaw in Western discourse surrounding AI governance and the future of the technology. It echoes a question we have raised before: is China positioning itself as the responsible AI governance actor while the US takes a wild west approach? Debating the future of AI without including China, they contend, is akin to “studying the Industrial Revolution while ignoring the country with the most factories.”
The Information Gap
Huang and Anseel point out that China is home to roughly half of all frontier AI model development and boasts arguably the world’s fastest rate of AI adoption. The failure to include Chinese voices in high-level discussions about AI’s economic and societal impacts reflects a profound “information gap” that limits the West’s understanding of the technology’s true trajectory.
This gap exists on two levels. The first is a lack of awareness regarding the capabilities of Chinese AI models. While Western policymakers and academics debate the theoretical risks of AI, Western businesses are already integrating Chinese technology into their operations. The authors note that major corporations like DoorDash, Siemens, and Airbnb have adopted models from Chinese developers such as DeepSeek, Z.ai (Zhipu AI), and Moonshot AI, often choosing them over American alternatives due to their competitive performance and significantly lower costs.
The recent release of Moonshot AI’s Kimi K3, a 2.8 trillion-parameter open-weight model that rivals leading US systems, further underscores the rapid advancement of Chinese AI. The fact that such significant developments are often overlooked or minimized in Western policy circles highlights the disconnect between the reality of the global AI landscape and the narrative dominating Western discourse.
The Governance Disconnect
The second level of the information gap relates to AI governance and regulation. The Stanford open letter called for urgent action to build institutions to steer the AI revolution. OpenAI has previously called for an IAEA-style global AI governance body including China, a proposal that gained little traction precisely because of the exclusionary dynamics Huang and Anseel describe. However, Huang and Anseel argue that any global governance framework developed without China’s participation is inherently flawed and unlikely to be effective.
China is not merely a passive observer in the AI revolution; it is actively shaping the technology’s development and deployment. The country has implemented its own comprehensive AI regulations, including the world’s first binding rules on AI agents, and is aggressively promoting its open-source models as a global public good, particularly in the Global South.
By excluding China from the conversation, the West risks developing governance frameworks that are incompatible with the reality of the global AI ecosystem. This could lead to a fragmented regulatory landscape, where different regions operate under conflicting rules, hindering international cooperation and exacerbating geopolitical tensions.
The Need for Inclusive Dialogue
The SCMP opinion piece serves as a crucial reminder that the AI revolution is a global phenomenon, and its challenges cannot be addressed in isolation. The authors urge Western policymakers, researchers, and industry leaders to actively engage with their Chinese counterparts to foster a more inclusive and comprehensive dialogue on AI’s future.
This engagement is essential for several reasons. First, it is necessary to develop a shared understanding of the risks and opportunities associated with advanced AI. Second, it is crucial for establishing effective global norms and standards for AI development and deployment. Finally, it is vital for preventing the AI race from escalating into a destabilizing geopolitical conflict.
The authors acknowledge that engaging with China on AI governance is complex, given the ongoing technological rivalry and differing political systems. However, they argue that the stakes are too high to allow these differences to preclude meaningful dialogue. The economic and societal transformations driven by AI will affect every nation, and managing these changes requires a coordinated global effort.
Conclusion
The Stanford open letter’s omission of Chinese signatories is a stark illustration of the blind spots in Western AI discourse. As Huang and Anseel eloquently argue, debating the future of AI with half the world absent is not only intellectually incomplete but practically dangerous.
To navigate the profound challenges and opportunities presented by the AI revolution, the West must recognize China’s central role in the global AI ecosystem and actively seek its participation in shaping the technology’s future. Only through inclusive, global dialogue can we hope to build the institutions and frameworks necessary to ensure that AI benefits all of humanity.