China Has Started a Grand Experiment in AI Education. It Could Reshape How the World Learns.


  • In three hours we understand students more than the three years spent by the best teachers.
  • Three things have fueled China’s AI education boom. The first is tax breaks and other incentives for AI ventures that improve anything from student learning to teacher training to school management. For VCs, this means such ventures are good bets. According to one estimate, China led the way in over $1 billion invested globally last year in AI education.
  • Second, academic competition in China is fierce. Ten million students a year take the college entrance exam, the gaokao. Your score determines whether and where you can study for a degree, and it’s 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.
  • Finally, Chinese entrepreneurs have masses of data at their disposal to train and refine their algorithms.The population is vast, people’s views on data privacy are much more lax than in the West (especially if they can get coveted benefits like academic performance in return), and parents are big believers in the potential of technology, having seen how much it has transformed the country in just a few decades.
  • Squirrel’s approach may yield great results on traditional education, but it doesn’t prepare students to be flexible in a changing world, the experts I spoke to say. “There’s a difference between adaptive learning and personalized learning,” says Chris Dede, a professor at Harvard University in the Technology, Innovation, and Education Program. Squirrel is doing adaptive learning, which is about “understanding exactly what students know and don’t know.” But it pays no attention to what they want to know or how they learn best. Personalized learning takes their interests and needs into account to “orchestrate the motivation and time for each student so they are able to make progress.
  • Much of Squirrel’s philosophy stems from Li’s own experiences as a child. When he was young, he didn’t have very good emotional intelligence, he says, and reading books on the subject didn’t help. So he spent half a year dividing the skill into 27 different components and trained himself on each one. He trained himself to be more observant, for example, and to be an interesting conversationalist (“I spent a lot of time finding 100 topics, so I have a lot of material to talk with others,” he says). He even trained himself to keep smiling when others criticized him. (“After that, in my life, I do not have any enemies.”) The method gave him the results he wanted — along with the firm belief that anything can be taught this way.
  • That’s exactly what China lacks. If you are able to speak multiple languages, you are able to talk to different people; you are able to communicate different ideas


  • 估计阅读时间是17mins,然而我抠脚的英语水平加上文章的深度和联想性让我看了整整一个小时
  • AI教学有很好的数据分析优势,计算机的快速处理数据能力,不分日夜地工作能力,都使得AI教学有很好的前景,只要不断地迭代分析数据的算法,一定可以让计算机拥有快速检测一个学生水平的能力,传统老师与计算机的差距在于经验的积累速度,不过对于单个知识点来说目前可能一个老师可能能给更好的帮助,所以我认为当下如果有AI算法辅助分析一个学生的水平,然后给针对的训练,再在个别的知识点上用上老师,那么可以大大降低对老师经验性的要求。因为我认为一个顶级老师和一个初级老师的区别仅在于对知识系统性的掌握以及对学生知识框架的快速认识能力上面(后者为主),所以有了AI算法的辅助,将能降低家长花重金请名师的成本,而可以请一个初级老师+AI算法辅助的方式
  • 感叹世界变化之快!
  • 感觉自己如果要成为认知层的上层人士,必须和世界进行连接,和更多的大师交流,那就必须学好英语,不然看一篇这样简单的文章要花上太久的时间…所以坚持好好学English!