Two recently released statistics have captured attention. One indicates that China's total research and development (R&D) spending has surpassed that of the United States for the first time, while the other reveals that Chinese students ranked first in mathematics and science in the Programme for International Student Assessment (PISA). Both indicators suggest that China is preparing for dominance in the AI era, starting from foundational strengths.
According to the 'Science and Technology Indicators' report from Japan's Ministry of Education, Culture, Sports, Science and Technology, China's R&D expenditure is projected to reach approximately 847 trillion won in 2024, surpassing the U.S. figure of about 831 trillion won. This marks the first time since the survey began in 1981 that China has taken the lead. Additionally, China’s top ranking in PISA for mathematics and science reflects its strong talent pool.
As the world enters an AI competition era, the importance of education in mathematics and science, which underpin AI, is paramount. Choi Tae-won, chairman of SK Group, recently stated, 'In the AI era, mathematicians will earn more than doctors,' emphasizing that a rote memorization and exam-focused education will struggle to keep pace in the AI competition. Jensen Huang, CEO of NVIDIA, also remarked, 'If I could go back to being 20, I would study physical sciences over software.'
Dan Wang, a technology industry analyst in China, contrasts the U.S. as a 'nation of lawyers' with China as a 'nation of engineers.' He notes that while U.S. bureaucrats often come from legal backgrounds, China's leadership is predominantly composed of engineers and technicians. In China, the cultivation of advanced industries is treated as an engineering project rather than mere rhetoric. Although Wang points out some negative side effects of this governance style, it is undeniable that it has propelled China to its current status as an AI powerhouse.
In this context, South Korea, which has set a national goal to become one of the 'three AI superpowers,' must reassess its educational landscape. While the country is rapidly investing in infrastructure such as semiconductor and data center projects, questions arise about how well its educational policies align with the ultimate competitive factor: talent development. South Korean students have consistently performed at the top in academic assessments, and the country ranks second globally in R&D spending as a percentage of GDP at 5.13%. However, as South Korea aims to join the ranks of the U.S. and China as an AI superpower, this is not a time for complacency.
Amid this, there have been hopeful reports that some semiconductor contract programs have surpassed admission scores of Seoul National University’s natural sciences. This shift has attracted top science students to practical career paths, such as employment with major semiconductor companies like Samsung Electronics and SK Hynix, slightly altering the previously dominant trend toward medical school. However, this change is limited to a few prestigious universities and does not yet represent a fundamental shift in the broader engineering education landscape.
The goal of becoming one of the 'three AI superpowers' cannot be achieved through infrastructure investment alone. Unlike building semiconductor factories, talent cannot be produced on a short timeline. The ongoing global competition for AI talent is even more intense than the AI semiconductor race. Therefore, a consistent educational framework must be redesigned across all levels, from elementary to graduate school, to cultivate AI talent. This involves understanding AI through the lens of mathematics, science, and engineering, and fostering individuals who can create new technologies grounded in human values and ethics. This is the true starting point for AI education.
* This article has been translated by AI.
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