Chinese language Coverage Analyst Assaults America’s New ‘Tremendous Intelligence’
United States President Donald Trump signed an govt order directing federal companies to exchange the time period “Synthetic Intelligence” with “Tremendous Intelligence” in official documentation, a regulatory rebrand that Chinese language expertise analysts argue masks basic structural flaws within the international tech sector.
The Sept. 29 govt order grants federal regulators 60 days to formulate a statutory definition for “Tremendous Intelligence” in an try to consolidate fragmented state-level laws underneath federal oversight. On the identical day, the White Home secured a voluntary security settlement titled the Frontier Accountability Joint Dedication with main tech corporations together with OpenAI, Anthropic, Meta, Google, and Nvidia. The executive push follows a Sept. 26 bilateral consensus between Washington and Beijing to ascertain a proper U.S.-China AI dialogue mechanism, with the subsequent session scheduled for November.
Writing within the Chinese language coverage journal Cultural Side, outstanding scholar Jiang Yuhao argued that substituting administrative terminology fails to handle three core paradoxes impeding the real-world financial utility of contemporary expertise: the productiveness paradox, Polanyi’s paradox, and the innovation paradox.
Analyzing the productiveness paradox, Jiang famous that huge company capital expenditure in synthetic intelligence has didn’t translate into broad-based effectivity features exterior the quick info expertise sector, particularly in America. Citing studies from the United Nations Convention on Commerce and Growth, Jiang highlighted that productiveness features stay tightly concentrated inside information middle operators and software program builders, whereas non-tech industries expertise stagnant whole issue productiveness.
Beneath Polanyi’s paradox, Jiang states, present generative fashions stay restricted to specific, codifiable, and extremely repetitive duties, similar to doc modifying, fundamental information processing, and assembly summarization. Jiang emphasised that probabilistic AI architectures can’t grasp the tacit, uncodified human information required for advanced bodily operations, stopping automated programs from integrating into crucial industrial manufacturing and operational management workflows.
The innovation paradox arises from the focus of scientific capital inside a small circle of expertise monopolies. Pushed by company revenue incentives, these conglomerates dictate an automation trajectory targeted on changing human labor and imposing office surveillance moderately than constructing instruments that increase employee capabilities. Citing analysis by economist Daron Acemoglu, Jiang warned that personal tech giants, particularly in America and the West, form tutorial analysis agendas and authorities coverage by way of compute monopolies, tutorial philanthropy, and protection contracting.
To counter tech-giant monopolies, Jiang advocated for the democratization of innovation by way of open-source basis fashions, public computing infrastructure, and worker-centric design. Pointing to China’s nationwide “AI Plus” initiative, Jiang famous that combining open-source software program with domain-specific commerce information permits small enterprises and frontline employees to adapt superior applied sciences to specialised manufacturing wants with out counting on expensive proprietary programs.
