China is quickly closing the once formidable lead the U.S. maintained on AI research. Chinese researchers now publish more papers on AI and secure more patents than U.S. researchers do. The country seems poised to become a leader in AI-empowered businesses, such as speech and image recognition applications. But while China has caught up with impressive speed, the conditions that have allowed it to do so — the open science nature of AI and the nature of the Chinese market, for instance — will likely also prevent it from taking a meaningful lead and leaving the U.S. in the dust.
Twenty years ago, there was a huge gulf between China and the United States on AI research. While the U.S. was witnessing sustained growth in research efforts by both public institutions and private sectors, China was still conducting low-value-added activities in global manufacturing. But in the intervening years, China has surged to rapidly catch up. From a research perspective, China has become a world leader in AI publications and patents. This trend suggests that China is also poised to become a leader in AI-empowered businesses, such as speech and image recognition applications.
China’s feat is dramatic. According to earlier research — the China AI Development Report 2018 project, which one of us (Li) helped spearhead — as well as an ongoing study of the economic and social impacts of AI technologies, the country’s progress is stunning. China’s global share of research papers in the field of AI has vaulted from 4.26% (1,086) in 1997 to 27.68% in 2017 (37,343), surpassing any other country in the world, including the U.S. — a position it continues to hold. China also consistently files more AI patents than any other country. As of March 2019, the number of Chinese AI firms has reached 1,189, second only to the U.S., which has more than 2,000 active AI firms. These firms focus more on speech (e.g., speech recognition, speech synthesis) and vision (e.g., image recognition, video recognition) than their overseas counterparts.
Impressive as this may be, however, there’s no guarantee it will translate into a robust advantage in AI innovation and global leadership moving ahead. Paradoxically, the conditions that helped China catch up might also pose a challenge to its future development in AI as the country reaches the innovation frontier. To explain why — and build on earlier research — we conducted field interviews with 15 AI related organizations of different types (including firms, universities, research institutes, and government agencies) and used the idea of catch-up cycles, a theoretical framework developed to explain countries’ successive changes in industrial leadership.
How was China able to leapfrog countries that had been working on this technology for much longer to build a world-leading AI research infrastructure in just 20 years?
Here, the concept of “catch-up cycles” can help us understand. In essence, the catch-up cycle framework suggests that, in certain circumstances, changes in technology, market conditions, and policy environments can put latecomers and forerunners more or less on an equal footing. According to the framework, these changes can open windows of opportunity for latecomers by quickly reducing the advantage of incumbents — for example, the emergence of Android smartphones was a technological change that flattened market leader Nokia’s advantage and allowed fast-movers like Samsung and Huawei to displace it. The framework also helps us understand when — and why — newcomers will displace incumbents.
In the story of how China managed to catch up, this framework highlights a few important factors: how the nature of AI research means that leaders’ technological advantages aren’t particularly robust; how China’s huge market is particularly conducive to improving AI; and how the country’s friendly regulatory environment is especially encouraging to AI investment and adoption.
