Beyond tech race: Science, trust and the future of China-US ties

Do we sometimes overestimate what artificial intelligence can do, while underestimating what we need to do as human beings?

AI is clearly transforming science. It can predict protein structures, accelerate the discovery of new materials and help researchers explore hypotheses at unprecedented speeds. Yet we should distinguish between accelerating discovery and creating knowledge, and between generating established scientific truth and developing genuine new understanding.

AI can help us explore possibilities at unprecedented speeds. Yet scientific progress still depends on meaningful questions, real-world experimental validation, manufacturing capabilities and human judgment. A simulation is not a manufactured product, and a plausible answer is not necessarily a scientific breakthrough.

This is particularly relevant to the AI competition between China and the United States. The two countries are competing across broad areas including advanced chips, computing infrastructure, foundation models, scientific research and industrial applications. The US has major strengths in frontier research, advanced computing and its innovation ecosystem. While China has developed competitive AI models and possesses substantial manufacturing capabilities. However, export controls, concerns about national security and different approaches to technology governance have made cooperation more difficult.

Washington recently took a step further by directing the US executive branch to use "super intelligence", or "SI", instead of "artificial intelligence", or "AI". Whatever the intention behind this terminology shift, it seems to express an aspiration that AI might become something far more powerful than a tool for assisting human intelligence. However, as we become increasingly ambitious about what AI can achieve, how do we distinguish technological aspiration from the actual capabilities and limitations of the technology?

Consider the Genesis Mission, launched in the US in November 2025, which aims to integrate national laboratory resources, scientific datasets and AI systems to accelerate scientific discovery. This is an ambitious initiative. But its success will depend not only on AI models, but also on experimental infrastructure, manufacturing expertise and the ability to translate discoveries into practical technologies.

The semiconductor sector illustrates this point particularly well. During the 20th century, the global chip industry transitioned from "vertical integration" to "vertical division of labor". This division of labor improved efficiency, with chip design and manufacturing becoming concentrated in different firms and regions. Today, however, governments are increasingly seeking to rebuild integrated national capabilities spanning chip design, fabrication, advanced packaging and commercialization. We might call this a shift toward national integrated device manufacturer (IDM-like) innovation ecosystems, marking a second major shift in industrial organization models in the post-Moore era. There are initiatives such as the National Semiconductor Technology Center in the US and Europe's Imec, which was founded in 1984 and is today the world's largest independent research and innovation center for nanoelectronics and digital technology. The NSTC and Imec-centered research ecosystems illustrate different approaches to strengthening semiconductor research and development. Their institutional models are not identical: one emphasizes national technological capacity, while the other has a long history of connecting industrial partners through collaborative precompetitive research.

But this brings us to a deeper question: Is technological progress ultimately about maximizing speed and national advantages, or should we also consider what the ultimate goals of scientific progress actually are?

Competition can stimulate innovation. Yet if efficiency becomes our only measure of progress, we risk confusing the means with the ends. Faster discovery does not automatically produce greater human well-being, and technological leadership does not necessarily translate into a more secure or meaningful future.

Traditional theories of international relations have often given very limited attention to ethics and morality as independent forces in world politics. Realism tends to prioritize power and national interests, while liberalism emphasizes rational choice, institutions and the potential for cooperation and shared benefits. Even constructivism, which recognizes the importance of shared identities and norms, often explains trust in terms of how these shared understandings facilitate cooperation and restrain conflict. In this sense, trust can still be understood instrumentally: countries exercise self-restraint partly because they expect reciprocal behavior.

But I believe we should consider a deeper possibility: What if trust is not merely an instrument to achieve strategic objectives, but is rooted in a framework of ontological ethics — an understanding that ethical relationships are not simply instruments of cooperation, but fundamental to how we understand human existence and society at large.

Here, I find the book Relational Theory of World Politics by Qin Yaqing, an expert in international relations, particularly instructive. It emphasizes that international order is shaped not only by individual interests and formal rules, but also by relationships, interaction and trust. Confucian philosophy similarly reminds us that good governance requires more than compliance with clear, agreed-upon rules. It also depends on responsibility, integrity and moral cultivation.

This distinction matters for AI governance. If cooperation depends exclusively on immediate returns, it may collapse whenever political circumstances evolve. If countries instead keep lines of communication open and engage in dialogue, fulfill commitments and develop habits of responsible interaction, cooperation may survive even when disagreements remain unresolved.

I would therefore propose two practical areas for cooperation between the US and China.

First, US and Chinese universities and research institutions could establish carefully defined collaborative projects in areas such as climate science, public health and nonsensitive materials research, with clear arrangements for intellectual property, data protection and research security.

Second, we should value the process of cooperation itself. The Asia-Pacific Economic Cooperation forum offers a useful illustration — even when negotiations do not produce immediate breakthroughs, continued interaction can build familiarity, shared understanding and channels for resolving future disagreements. In international governance, preserving these relationships can be valuable in its own right.

Ultimately, I believe we need what I would call "ecological rationality" — a way of thinking that evaluates technological progress not only based on speed, productivity or national advantage, but also by its overall effects on society, human dignity and our shared future.

The goal should not be to replace rules with relationships, or competition with cooperation. It should be to build an international community in which competition operates within responsible boundaries, rules are supported by trust and scientific progress serves purposes beyond winning a race.

The writer is an associate professor at Shanghai Institute for Science of Science, and now works at the Institute for the History of Natural Sciences, Chinese Academy of Sciences.

The views do not necessarily reflect those of China Daily.