Daniel Chou is a Data Scientist at Georgetown’s Center for Security and Emerging Technology (CSET) focused on transforming data into knowledge. He previously worked at Defense Group supporting government clients with analytics of geospatial, unstructured, and text-based data sets. Daniel enjoys playing the game of Go. He was a member of the U.S. Go Team in the 1st World Mind Sports Games. Daniel holds degrees from Johns Hopkins University (MSE, Computer Science) and Caltech (B.S., Mathematics).

Tracking the output of a country’s researchers can inform assessments of its innovativeness or assist in evaluating the impact of certain funding initiatives. However, measuring research output is not as straightforward as it may seem. Using a detailed analysis that includes Chinese-language research publications, this data brief reveals that China's lead in artificial intelligence research output is greater than many English-language sources suggest.

China is following a national strategy to lead the world in artificial intelligence by 2030, including by pursuing “general AI” that can act autonomously in novel circumstances. Open-source research identifies 30 Chinese institutions engaged in one or more of this project‘s aspects, including machine learning, brain-inspired AI, and brain-computer interfaces. This report previews a CSET pilot program that will track China’s progress and provide timely alerts.

CSET's Daniel Chou provides an update on previous CSET research exploring China's security forces' AI research portfolio.

China’s State Key Laboratory system drives the country’s innovation in science and technology. A key part of China’s aim to reduce its dependence on foreign technology, these labs conduct cutting-edge basic and applied research, attract and train domestic and foreign talent, and conduct academic exchanges with foreign counterparts. These laboratories are spread across almost all Chinese provinces except Tibet, with the majority clustered in large coastal cities.

China is banking on applying AI to biotechnology research in order to transform itself into a “biotech superpower.” In pursuit of that goal, it has emphasized bringing together different aspects of the development cycle to foster multidisciplinary research. This data brief examines the emerging trend of co-location of AI and biotechnology researchers and explores the potential impact it will have on this growing field.

New analytic tools are used in this data brief to explore the public artificial intelligence (AI) research portfolio of China’s security forces. The methods contextualize Chinese-language scholarly papers that claim a direct working affiliation with components of the Ministry of Public Security, People's Armed Police Force, and People’s Liberation Army. The authors review potential uses of computer vision, robotics, natural language processing and general AI research.

In this proof-of-concept project, CSET and Amplyfi Ltd. used machine learning models and Chinese-language web data to identify Chinese companies active in artificial intelligence. Most of these companies were not labeled or described as AI-related in two high-quality commercial datasets. The authors' findings show that using structured data alone—even from the best providers—will yield an incomplete picture of the Chinese AI landscape.

China AI-Brain Research

September 2020

Since 2016, China has engaged in a nationwide effort to "merge" AI and neuroscience research as a major part of its next-generation AI development program. This report explores China’s AI-brain program — identifying key players and organizations and recommending the creation of an open source S&T monitoring capability within the U.S. government.