Jasmine Sun Reports on the Contrast in AI Employment Attitudes Between China and the U.S.
A lengthy investigation by Jasmine Sun, a technology reporter for The New York Times in San Francisco, points out that Silicon Valley AI practitioners generally believe that most ordinary people's economic prospects are bleak, but they lack solutions.
Anthropic CEO Dario Amodei predicts that 50% of entry-level white-collar jobs may disappear by 2030; Block CEO Jack Dorsey laid off nearly half of his staff in March due to AI agents.
In terms of market mechanisms, U.S. tech capital is accelerating the deployment of AI agents to replace human labor, shifting funds from traditional white-collar services to AI infrastructure. In contrast, due to lower labor costs and policy buffers, capital in China is more inclined towards the popularization of AI learning and applications. Companies in the U.S. heavily impacted by AI face pressure, while local AI education and training in China benefit.
Source: Public Information
ABAB AI Insight
Jasmine Sun has previously reported on the technological differences between China and the U.S. This NYT investigation continues her comparison of Silicon Valley anxiety with Chinese pragmatism, similar to past observations on U.S.-China internet regulation and innovation attitudes, emphasizing the amplifying or buffering effects of culture, policy, and labor structure on technology.
In terms of capital pathways, U.S. AI companies are reallocating resources from labor costs to model training and inference through large-scale layoffs and agent deployment, while China is transforming the enthusiasm for AI learning into low-cost applications and entrepreneurship through an oversupply of talent and low-paying jobs following increased university admissions. The motivation lies in the U.S. pursuit of maximum efficiency, while China focuses on social stability and employment buffering.
Similar cases include multiple rounds of layoffs in U.S. tech companies driven by AI in 2023-2024, and China's rapid absorption of automated factories in the past. The current global AI employment impact is transitioning from a U.S.-led white-collar replacement to a bifurcated response from China and the U.S.
Essentially, this reflects regulatory changes: AI's rapid replacement in the U.S. under a free market is contrasted with China's labor laws that protect jobs and buffer public positions. The root mechanism is that youth unemployment in China has long been structural and labor costs are extremely low, leading AI to be more of an incremental tool rather than a destructive force. Only when policies explicitly prohibit pure AI replacement can a structural balance be achieved in transitioning from technological shock to social stability.
ABAB News · Cognitive Laws
The disappearance of jobs is not an AI issue, but rather whose labor structure is hit first by AI. The lower the labor cost, the harder it is for AI to become an enemy rather than a new skill. Those who fear AI teach others to be anxious, while those eager to learn AI directly turn the crisis into an opportunity.