It’s widely understood that Beijing invests significant resources in shoring up its science and technology prowess, but the extent and flows of the Chinese government’s public investments in S&T are not as well known. This project tracks publicly available information about the budgets of more than two-dozen high-level Chinese government entities, including those that support science, technology, and talent recruitment.

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.

Foreign investors comprise a significant portion of investors in top U.S. AI startups, with China as the leading location. The authors analyze investment data in the U.S. AI startup ecosystem both domestically and abroad, outlining the sources of global investment.

Corporate investors are a significant player in the U.S. AI startup ecosystem, funding 71 percent of top U.S. AI startups. The authors analyze the trends in top corporate funders and the startups receiving corporate money.

See our original translation of a 2020 PRC regulation, issued by the Cyberspace Administration of China.

See our original translation of a 2017 PRC document, issued by the predecessor office of today's Cyberspace Administration of China.

Based on news coverage alone, it can seem as if corporations dominate the research on artificial intelligence and machine learning when compared to the work of universities and academia. Authors Simon Rodriguez, Tim Hwang and Rebecca Gelles analyze the data over the past decade of research publications and find that, in fact, universities are the more dominant producers of AI papers. They also find that while corporations do tend to generate more citations to the work they publish in the field, these “high performing” papers are most frequently cross-collaborations with university labs.

Open source intelligence (OSINT) and science and technology intelligence (STI) are realized differently in the United States and China, China putting greater value on both. In the United States’ understanding, OSINT “enables” classified reporting, while in China it is the intelligence of first resort. This contrast extends to STI which has a lower priority in the U.S. system, whereas China and its top leaders personally lavish great attention on STI and rely on it for national decisions. Establishing a “National S&T Analysis Center” within the U.S. government could help to address these challenges.

The countries with the greatest capacity to develop, produce and acquire state-of-the-art semiconductor chips hold key advantages in the development of emerging technologies. At present, the United States and its allies possess significant leverage over core segments of the supply chain used to produce these chips. This policy brief outlines actions the United States and its allies can take to secure that advantage in the long term and use it to promote the beneficial use of emerging technologies, such as artificial intelligence.

Semiconductors are a key component in fueling scientific progress, promoting economic advancement, and ensuring national security. This issue brief summarizes each component of the semiconductor supply chain and where the United States and its allies possess the greatest leverage. A related policy brief, “Securing Semiconductor Supply Chains,” recommends policy actions to ensure the United States maintains this leverage and uses it to promote the beneficial use of emerging technologies, such as artificial intelligence.