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The very recent summit involving Presidents Trump and XI Jinping dealt with many political controversies of the day, which included AI and related issues such as intellectual property. The mention of AI brought to mind a book by Kai-Fu Lee<\/a>, which I think I read in 2019. I remembered some of the comments Lee made about China, computer science, and AI at that time. Lee, who has held both U.S. and Taiwanese citizenship, wrote that China would have important advantages in the development and application of technology, which surprised me at the time but made some sense given what I knew about China. Lee was educated in the U.S. (Carnegie Mellon Ph.D.), worked for Apple, then returned to Taiwan and later worked for Google in China. I explored my notes and highlights from that book and also from The Big Nine<\/em>. My interest in the role of AI in education and its application across different countries led me to another article in my personal archive (Hao, 2019). The following comments are mostly based on Lee\u2019s ideas, with some expansion using the other two references I have mentioned. All sources are a bit dated, given the rapid pace of AI developments, but I still find the core ideas worth considering. <\/p>\n\n\n\n According to Lee, China\u2019s advantages in AI come from scale, data, industrial capacity, talent, and state coordination.<\/p>\n\n\n\n Scale equals more data<\/strong><\/p>\n\n\n\n China\u2019s 1.4 billion people give it control of \u201cthe largest, and possibly most important, natural resource in the era of AI: human data\u201d\u2014and that its huge number of internet users gives it both data quantity and quality for training models. This resource is roughly the equivalent of the combined resources of the United States and Europe. Lee offered this perspective some years ago when finding content seemed more a priority for U.S. companies who encountered push back when scrapping the web and books without permission. <\/p>\n\n\n\n Industry integration<\/strong><\/p>\n\n\n\n Chinese companies share. For example, Tencent\u2019s ecosystem is noted as perhaps the single richest data ecosystem of all the giants and combines multiple services, say, in contrast to X and Amazon. Concentration of data and services in a few massive platforms offers a related quantity and quality advantage.<\/p>\n\n\n\n Quantity of Talent<\/strong><\/p>\n\n\n\n There is a Thomas Friedman quote<\/a> I have always remembered. \u201cRemember in China if you are a one in a million talent, there are 1400 others just like you.\u201d Lee offers a different assessment of the talent situation specific to AI. He claims that the U.S. has more superstars, but China has the advantage in the number of engineers and computer scientists working in on AI and related fields. Aside of the great difference in population, engineering, programming and science are simply fields of advanced study that are seen as more of an opportunity in China. My own way of thinking about this difference is that in the U.S., business and finance attract many and in China these fields are less of a draw. <\/p>\n\n\n\n State Coordination and Standards<\/strong><\/p>\n\n\n\n A \u201cbig advantage for China: it doesn\u2019t have the privacy and security restrictions that might hinder progress in the United States\u201d. The commitment to the massive surveillance of its own population is known focus of the Chinese government and a means of control and manipulation of its population. We rightfully consider the use of technology to probe the personal lives and values a violation of basic human rights and bristle internally at the collection of information about us by companies and the government. Simply put, China doesn\u2019t have the privacy and security restrictions that might hinder progress in the United States. Despite tolerated abuses, the commitment to collecting and analyzing this type of information is a source of funding and a focus of experimentation in China. <\/p>\n\n\n\n ” Move fast and break things” was the original Google creed, but a value system that has come under increasing criticism in China. Without the pressure to curb potential negative aspects of AI, China moves faster. Related to this is the greater top down decision making of the Chinese system. In the U.S., you have multiple businesses trying to raise huge sums of money and are often isolated from each other, often duplicating similar approaches. We historically value competition and assume the motivation has advantages. While true, I wonder about the \u201cbusiness model\u201d sucking up a large share of the available investment money in this sector in the US. The amount of money required has to a great degree squeezed out university researchers who either leave universities or work around the edges of AI innovation. While AI research is a high priority in China, the U.S. has cut funding for NSF funding<\/a> for AI and cybersecurity.\u00a0<\/p>\n\n\n\n AI in China and Education<\/strong><\/p>\n\n\n\n The personal interest that has driven my own interest in AI has been potential opportunities in education<\/a>. This has been a messy issue in this country with pushback due to legitimate concerns for cheating, failure to address skill development, and lack of interest in instruction presented by a computer<\/a>. China has committed to exploring AI-facilitated education. <\/p>\n\n\n\n Academic competition in China is tense. Millions of students a year take the college entrance exam, the gaokao<\/strong>. Your score determines whether and where you can study for a degree, and it\u2019s seen as the biggest determinant of success for the rest of your life. Parents willingly pay for tutoring or anything else that helps their children get ahead. The options tech can provide outside of classrooms offer opportunities to sell experiences to well-meaning parents. (Hao)<\/p>\n\n\n\n Two companies that are likely unfamiliar to most U.S. educators, Squirrel AI<\/a> and Alo7<\/a>, make good example. Since the Hao article was published both services became available in the U.S. <\/p>\n\n\n\n Squirrel AI uses an “adaptive learning” model that breaks subjects into thousands of “knowledge points”\u2014far more granular than traditional textbooks. The system diagnoses a student’s specific gaps and provides targeted video lectures and practice problems. The teachers are intended to act like “pilots,” stepping in only for emotional support or complex issues while the algorithm handles the core instruction. Educators will likely recognize similarities to the Kahn Academy<\/a>. <\/p>\n\n\n\n In contrast, Alo7 emphasizes a “quality-oriented education” focusing on creativity and the liberal arts. This “intelligent classroom” use AI to analyze student engagement, pronunciation, and even “joy” through facial and vocal recognition\u00a0<\/p>\n\n\n\n The interest in AI in education seems to be a combination of the emphasis of standardized test performance for advancement and opportunity, the larger population, and the greater risk tolerance within the context of exploration for improvement. <\/p>\n\n\n\n Summary<\/strong><\/p>\n\n\n\n This post is not a value judgment comparing U.S. AI policies, but rather an attempt to summarize what some experts have said about the differences. My personal issue concerns the economic pressure in the U.S. based in our trust in competition among corporations to drive innovation. While this is an approach that has worked in many areas, the huge investments that are required have to this point sucked a great deal of capital from the economy and seem largely and unnecessarily redundant. I personally also find the focus of interest in AI in education (personalized and adaptive instruction) interesting as this emphasis has appealed to me based on my interest in mastery learning<\/a>. <\/p>\n\n\n\n Sources<\/strong><\/p>\n\n\n\n Hao, K. (2019). China has started a grand experiment in AI education. It could reshape how the world learns. MIT Technology Review<\/em>, 123<\/em>(1), 1-9.<\/p>\n\n\n\n