The use cases described in this essay are examples of how AI, with its ability to learn from massive data, can reduce inefficiencies as well as stepping in when human professionals are scarce. AI, together with other digital technologies, can transform vital public services to be highly scalable and readily available at a very low cost, even to rural areas of China.

It is less than three years since China announced its AI strategy yet it has achieved widespread use of AI across all industry sectors, benefiting all aspects of daily life in China, and at a pace unseen elsewhere. For Europe and North America, there are some lessons to be learned. China’s approach to AI and other new technologies is to experiment and innovate first, while putting in place supporting policies and regulations as it goes. Time to market is crucial. This is in stark contrast to western economies, where lengthy policies and regulations usually precede innovation use. There may be a place for a middle ground where new technologies can be tried out within regulatory sandbox environments so as not to stifle innovation growth. In addition, China has a unique edge on AI development – the vast amounts of data constantly produced by its 1.4 billion population are the fuel for AI’s machine learning. Chinese citizens are also more willing to share data in exchange for convenience and low-cost services. To mitigate the data disadvantage, western countries may need to find ways to share their datasets while maintaining data privacy, such as using new federated approaches to machine learning. Finally, the stark reality of a global pandemic has highlighted where China’s investment in AI is yielding results in speeding up some of the processes involved in combating the coronavirus. While there may be social and democratic implications in some elements of this approach, it offers a path that other countries might learn from.