The headlines are predictable by now. The United States restricts chip exports. Chinese labs release competitive models. Pundits declare who is “winning” the artificial intelligence race. The language borrows from sport and war: sprints, breakthroughs and supremacy.
It makes for compelling drama. It also misses the point.
A key issue in the AI era is not who builds the most powerful model. It is what different societies want intelligence to do. And on that metric, China is not merely competing in a Western-defined race. It is redefining the destination.
In Silicon Valley, AI is framed as frontier exploration. What are the implications of general intelligence that rivals or exceeds human cognition? Should it be regulated? The US government largely maintains a hands-off posture, funding research while allowing private firms to lead.
In Beijing, the framing is different. The question is not: How intelligent can machines become? It is: How can intelligence be integrated into society and embedded in national infrastructure?
China’s national policy treats artificial intelligence as a capacity to be absorbed. The emphasis is on systemic embedding. AI is deployed across logistics, healthcare, finance, and urban management. It becomes part of the national architecture.
The contrast appears in investment patterns. In the US, capital flows toward foundational models, breakthrough research and moonshot ventures. The assumption is that innovation happens at the frontier, and the rest of the economy will adapt.
China inverts that logic. Before AI can transform society, the required substrate must be built: data centers, high-speed connectivity, industrial internet systems, power grids and interoperability standards.
These investments are capital-intensive, but once established, they lower the marginal cost of deploying intelligence across every sector.
Economically, AI is intended to serve as a primary engine for productivity growth, offsetting demographic challenges posed by a shrinking workforce through industrial automation and smart manufacturing.
Among the objectives: capturing a dominant share of the projected $5 trillion global humanoid robot market, with AI-powered robots deployed across industrial, commercial, and household applications.
By 2050, China aims to achieve global leadership in artificial intelligence, building upon the foundational 2017 Next Generation Artificial Intelligence Development Plan. The strategic vision calls for a fully realized “AI-optimized society” in which intelligent systems drive transportation, healthcare, urban planning, and all public services.
The Confucian-legalist lens
To understand China’s approach, one must look beyond policy to deeper cultural patterns. Chinese political thought has long emphasized order, hierarchy, and systemic coherence. These are not rhetorical flourishes. They are operating assumptions embedded in institutions.
Confucianism provides a moral vision: a well-governed society is one in which roles are defined, duties are fulfilled, and harmony is maintained. Technology is judged by its contribution to order. AI is valued not because it maximizes individual autonomy, but because it can reduce uncertainty and align behavior with collective norms.
Legalism supplies the machinery. It assumes systems decay without enforcement. Stability requires clear rules and credible consequences. AI sharpens this capacity. Algorithmic monitoring, risk scoring, and targeted intervention make discipline scalable.
The two traditions are complementary. Confucianism defines the harmony to be preserved. Legalism provides the instruments to preserve it. Artificial intelligence enhances both by expanding visibility and precision.
This composite logic explains why Chinese AI can appear both pervasive and abrupt. The regulation of major platforms illustrates the pattern.
Firms like Alibaba, during their rapid expansion, were encouraged to innovate, gather data and digitize vast sectors of the economy. As platforms approached infrastructural status (controlling finance, payments, and data flows), the calculus shifted.
Concentrated private power risked distorting hierarchy and undermining state authority. Legalist correction followed: antitrust actions, restructuring mandates, and regulatory tightening.
In 2022, Algorithmic Recommendation Regulations required platforms to register their recommendation algorithms with authorities and mandated transparency in how they operate. Algorithms became legible to the state.
The objective was not destruction but reintegration. Private capability was absorbed into public strategy. The pattern is consistent: allow growth, observe concentration, intervene at leverage points and restore equilibrium.
The predictive state
The deeper consequence of China’s AI strategy is the emergence of what might be called the “predictive state.”
Traditional governance is reactive. It legislates rules and responds after violations occur. The Predictive State aims to detect deviations before they crystallize into instability. It intervenes not only in the fact of transgression but also in the probability of one.
This requires a reengineered nervous system. Digital identity platforms, integrated payments, and sensor networks do more than monitor society. They render it computationally legible. Transactions, movements, and interactions become structured inputs for predictive models.
Once legibility is achieved, preemption becomes possible. Traffic congestion is mitigated before gridlock forms. Financial risk is flagged before contagion spreads. Public health interventions activate before outbreaks accelerate. The state shifts from referee to systems architect.
For citizens, the benefits are tangible: reduced friction, faster services, perceived stability. The bargain is not simply privacy for convenience. It is visibility for inclusion. Disconnection from the system limits participation in economic and social life. Participation becomes not just rational but necessary.
Western debates often focus on AI replacing humans. In China, the emphasis is functional reorganization.
AI systems coordinate, filter, and optimize within hierarchical institutions. Human roles persist but change. Workers supervise dashboards rather than operate machinery. Physicians use diagnostic systems to triage. Administrators review algorithmic outputs and intervene when anomalies appear.
Labor moves from direct execution to supervision and exception management. Hybrid systems are more resilient than fully automated ones; human oversight absorbs failure.
Yet this reorganization carries a structural cost. When expertise is encoded in software, tacit knowledge erodes. Decision-making increasingly aligns with quantified indicators. Discretion survives, but within parameters set by system design.
Political design
Whether this model proves durable remains uncertain. Predictive systems excel within the boundaries of the known, extending past patterns into the future. But history includes rupture as well as continuity. Financial crises evade models. Technological shifts can challenge existing frameworks.
The AI era will not be defined by a single breakthrough, a benchmark score or a temporary lead in model performance. It will be shaped by how societies choose to embed intelligence into their institutions, economies and daily life—and by what those choices reveal about their deepest political priorities.
Some nations will treat AI primarily as an amplifier of markets, innovation and individual agency, letting private firms and open competition drive progress while minimizing centralized direction.
Others, like China, will embrace it as a powerful instrument of coordination, risk management and enhanced state capacity. It will actively integrate AI to improve industries, manage public services, ensure social stability and promote national independence through planned strategies such as the “AI+” initiative and long-term plans aimed at widespread use across manufacturing, services, urban management and more.
The true contest, therefore, lies not in who temporarily builds the most advanced system, but in which model ultimately delivers the most sustainable and broadly shared outcomes for human well-being.
AI serves as a mirror, reflecting how civilizations define progress, value collective well-being and envision the proper role of government in orchestrating shared prosperity and stability.
Jan Krikke is a contributing writer for Asia Times and author of the forthcoming book “The Predictive State: China, AI, and the Future of Governance”, from which this essay is adapted.