As technology competition intensifies between the United States and China, governments and policy researchers are looking for metrics to assess each country’s relative strengths and weaknesses. One measure of technology innovation increasingly used by the policy community is research output. Drawing on CSET’s experiences over the last four years, this post shares our best practices for using research output to study national technological competition and inform public policy.

CSET’s CAT presents data related to countries' artificial intelligence ecosystems to give an overview of domestic capabilities, as well as insights on competitiveness and collaboration globally. It presents metrics on AI research, patents, and investment-related activities for AI overall and its various subfields.

As modern machine learning systems become more widely used, the potential costs of malfunctions grow. This policy brief describes how trends we already see today—both in newly deployed artificial intelligence systems and in older technologies—show how damaging the AI accidents of the future could be. It describes a wide range of hypothetical but realistic scenarios to illustrate the risks of AI accidents and offers concrete policy suggestions to reduce these risks.

CSET’s Private-sector AI-Related Activity Tracker (PARAT) collects data related to companies’ AI research and development to inform analysis of the global AI sector. The global AI market is already expanding rapidly and is likely to continue growing in the coming years. Identifying “AI companies” helps illustrate the size and health of the AI industry in which they participate as well as the most sought-after skills and experience in the AI workforce.

As part of its strategy to achieve global leadership in AI, the Chinese government brings together local governments, academic institutions, and companies to establish collaboration platforms. This data brief examines the role of China’s Artificial Intelligence Industry Alliance in advancing its AI strategy, and the key players in the Chinese AI industry.

CSET Research Fellows Remco Zwetsloot and Zachary Arnold argue against the banning of Chinese STEM students from the United States and outline how rejecting foreign talent hampers U.S. innovation.

CSET Research Fellow Zachary Arnold testified before the U.S.-China Economic and Security Review Commission hearing on "U.S. Investment in China's Capital Markets and Military-Industrial Complex." Arnold discussed discuss China’s use of financial capital flows and the state’s prominent role in allocating capital to specific firms and sectors.

The Chinese government is pouring money into public-private investment funds, known as guidance funds, to advance China’s strategic and emerging technologies, including artificial intelligence. These funds are mobilizing massive amounts of capital from public and private sources—prompting both concern and skepticism among outside observers. This overview presents essential findings from our full-length report on these funds, analyzing the guidance fund model, its intended benefits and weaknesses, and its long-term prospects for success.

China’s government is using public-private investment funds, known as guidance funds, to deploy massive amounts of capital in support of strategic and emerging technologies, including artificial intelligence. Drawing exclusively on Chinese-language sources, this report explores how guidance funds raise and deploy capital, manage their investment, and interact with public and private actors. The guidance fund model is no silver bullet, but it has many advantages over traditional industrial policy mechanisms.

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.

U.S. research security requires trust and collaboration between those conducting R&D and the federal government. Most R&D takes place in the private sector, outside of government authority and control, and researchers are wary of federal government or law enforcement involvement in their work. Despite these challenges, as adversaries work to extract science, technology, data and know-how from the United States, the U.S. government is pursuing an ambitious research security initiative. In order to secure the 78 percent of U.S. R&D funded outside the government, authors Melissa Flagg and Zachary Arnold propose a new, public-private research security clearinghouse, with leadership from academia, business, philanthropy, and government and a presence in the most active R&D hubs across the United States.

Half of Silicon Valley’s startups have at least one foreign-born founder, and immigrants are twice as likely as native-born Americans to start new businesses. To understand how immigration shapes AI entrepreneurship in particular in the United States, Huang, Arnold and Zwetsloot analyze the 2019 AI 50, Forbes’s list of the “most promising” U.S.-based AI startups. They find that 66 percent of these startups had at least one immigrant founder. The authors write that policymakers should consider lifting some current immigration restrictions and creating new pathways for entrepreneurs.

CSET submitted the following comment to the Department of Homeland Security regarding a fixed time period of admission for nonimmigrant students, exchange visitors and representatives of foreign information media.

The global AI industry is booming, with privately held firms pulling in nearly $40 billion in disclosed investment in 2019 alone. U.S. companies continue to attract the majority of that funding—64 percent of it in 2019—but that lead is not guaranteed. This report analyzes AI investment data from 2015 to 2019 to help better understand trends in the global AI landscape.

Establishing a new public-private institution to improve American research security

Preserving pathways for high-skilled foreign talent critical to U.S. leadership in artificial intelligence.

Artificial intelligence is of increasing interest to the private sector, but what exactly constitutes an “AI company?” This data brief offers a flexible, data-driven framework for identifying the companies most relevant in this field at the moment, providing policymakers and researchers with a tool for mapping technology transfer risks and gauging the overall health of America’s AI sector.

New ICE restrictions on foreign students speed up a trend that make it slower and costlier for immigrants to come to the United States, write Zachary Arnold and Tina Huang. America’s historic near-monopoly on the global market for foreign talent is fading.

Official data shows a 75 percent increase in the number of U.S. residents advancing through Express Entry, Canada's flagship skilled immigration program. These findings call for immigration reforms and greater investment in STEM research and workforce development.

Current immigration policies may undermine the historic strength of the United States in attracting and retaining international AI talent. This report examines the immigration policies of four U.S. economic competitor nations—the United Kingdom, Canada, France, and Australia—to offer best practices for ensuring future AI competitiveness.

"AI is very different from other security-relevant technologies, in that the private sector is in the driver's seat." Zach Arnold and Ashwin Acharya joined the ChinaTalk podcast to discuss their work at CSET on AI investment.

While AI innovation would presumably continue in some form without Big Tech, the authors find that breaking up the largest technology companies could fundamentally change the broader AI innovation ecosystem, likely affecting the development of AI applications for national security.

CSET research shows more than 80 percent of international students receiving Ph.D.s in artificial intelligence remain in the U.S. for at least five years. That’s good, write Remco Zwetsloot and Zach Arnold, because America’s tech sector relies on foreign-born talent.

Talent is core to U.S. competitiveness in artificial intelligence, and international graduate students are a large source of AI talent for the United States. Retaining them in this country as they transition into the workforce is key. Graduate student retention has historically been a core U.S. strength, but that strength is endangered by recent events.

This product is a Chinese translation of the CSET issue brief, "Chinese Public AI R&D Spending: Provisional Findings" by Ashwin Acharya and Zachary Arnold.

China aims to become “the world’s primary AI innovation center” by 2030. Toward that end, the Chinese government is spending heavily on AI research and development (R&D)—but perhaps not as heavily as some have thought. This memo provides a provisional, open-source estimate of China’s spending.

The Forbes AI 50 list “shows that foreign talent is critical to AI innovation—and that for now, the United States can still attract talent from around the world,” write CSET’s Remco Zwetsloot, Tina Huang and Zachary Arnold.

Green card limits haven’t budged in decades, while new policies make it harder, costlier, and more uncertain for the world’s talent to come to the United States.

A sustained talent shortage could undermine U.S. strength in artificial intelligence; current immigration policies would make it worse. Read our recommendations for bolstering U.S. leadership in AI research and practice.

As the artificial intelligence field becomes more developed globally, the United States will continue to rely on foreign AI talent to stay ahead of the curve. Here are our preliminary recommendations to maintain current U.S. leadership, bolster the domestic AI workforce and improve the outlook for the future.