Summary of the Core Content
This article discusses the controversy surrounding The Economist's criticism of China's investment in technology, pointing out that such criticism only focuses on the surface phenomena. The real issue at hand is the global challenge of wealth distribution in the age of AI: as machines, particularly AI, begin to replace human cognitive tasks (such as coding, consulting, and legal analysis), the traditional economic cycle of “labor creating value → wage growth → expanded consumption” is disrupted. The benefits of technology are increasingly concentrated in the hands of a few capital owners and tech giants, leaving ordinary people out of the loop. The article argues that the key to future competition among countries will not be who has the strongest AI, but who can establish a system that allows the general public to share in these benefits. China has institutional advantages that could enable it to explore this path.
I. The Economist’s Criticism Misses the Mark: The Problem Lies Not in the Speed of Technology, but in the Failure to Distribute the Benefits to Ordinary People
The Economist claims that China is investing too much in robots and AI, leading to weak consumption and pressure on corporate profits. However, this reverses the cause and effect:
- China must rely on “new quality productive forces” like AI and renewable energy for transformation (since the real estate sector is no longer a viable option). The problem is not that technology is developing too quickly, but that the value created by technology is not reaching the hands of the general public.
- For example, although China leads the world in new energy vehicles and photovoltaics, consumer confidence remains low due to concerns about job loss, declining asset values (such as falling housing prices), and an underdeveloped social security system. In short, machines are producing more goods, but ordinary people do not have the money to buy them, creating a vicious cycle of overproduction and insufficient consumption.
II. Why Does AI Disrupt the Traditional Distribution Logic?
Previous industrial revolutions (steam engines, assembly lines, computers) merely assisted with tasks; humans remained the core of production:
- Steam engines replaced physical labor, but people were still needed to operate them; computers replaced computational tasks, but programmers were required. As efficiency increased, companies hired more workers and raised wages, allowing people to spend more and driving economic growth (this is how the middle class in Europe and America emerged).
AI, however, is different:
- For the first time, it replaces cognitive tasks—80% of the code written by Anthropic is generated by AI, and companies like Microsoft and Google use AI for research and development. Lawyers and consultants are also being replaced by AI. In the future, AGI (Artificial General Intelligence) could even handle management and decision-making.
- The result is that while the economy grows and companies make money, fewer people are directly creating value. Without jobs, there is no income, and consumption cannot increase—this is more frightening than unemployment, as it undermines the foundation of “labor in exchange for income.”
III. A Global Problem of Inequality: Not Unique to China
This is not just a Chinese issue; the United States faces the same challenges:
- The seven major tech companies in the U.S. (Apple, Microsoft, etc.) account for a large portion of the S&P 500’s growth, and the top ten tech companies have a combined market value of over $20 trillion. However, the proportion of labor income in the U.S. GDP is declining, with wealth concentrated in the hands of a few individuals (such as Elon Musk and Mark Zuckerberg).
- Essentially, AI has expanded the “pie,” but fewer people are getting a share of it; a small number of capital owners and tech companies take the majority, while the rest can only benefit indirectly.
IV. Three Possible Paths for Future Distribution
The article proposes three possible approaches to distribute the benefits of AI:
1. Traditional Capitalism: Capitalists take the majority, with the government redistributing through taxation (as currently in the U.S.): AI profits go to shareholders, and the government uses taxes (such as wealth taxes) to support the poor. However, wealthy individuals may evade taxes, and the subsidies may not be sufficient.
2. State Capitalism: The state owns AI companies, and the benefits are shared among all citizens (proposed by Trump): The government invests in AI companies, and the profits are placed in a public fund for everyone to benefit from indirectly.
3. Innovative Approaches: Directly giving everyone shares in AI companies or providing a basic income: For example, establishing a “digital sovereignty fund” to distribute shares of AI companies to all citizens, or providing a monthly “AI dividend” (similar to a minimum wage, but funded by AI profits).
The ideal approach is the third one—allowing ordinary people to directly benefit from the value created by AI, rather than relying on government redistribution.
V. China’s Opportunities: Leveraging Institutional Advantages to Solve Distribution Issues
China has two unique advantages:
1. Complete industrial chain and large market: AI development requires data, computing power, and application scenarios, all of which China possesses (as evidenced by the popularity of new energy vehicles).
2. Institutional coordination: China can simultaneously promote technological development and distribution reforms (for example, supporting AI companies while improving social security and training workers for new roles).
What China needs to do in the future:
- Continue to invest in AI and robotics, but not just focus on becoming the largest producer; it must also explore mechanisms for sharing the benefits (for example, requiring state-owned AI companies to contribute to social security or piloting shared ownership of AI companies).
- Improve vocational training to help workers transition to new roles (for example, teaching them how to operate AI robots or how to use AI for more advanced tasks).
Only by ensuring that ordinary people truly benefit from AI can China transform from a “powerful AI nation” into a “nation with AI-driven welfare.” This is the key to future competition.
Conclusion
The ultimate question in the age of AI is not “what machines can do,” but “who gets to keep the money they earn.” Whoever solves this issue first will gain control of the next phase of civilization. For China, this is both a challenge and an opportunity to surpass the West, as the Western capitalist system struggles to break the monopoly of capital on benefits. China has the potential to explore a more equitable distribution model.