Research

CSET produces evidence-driven analysis in a variety of forms, from informative graphics and translations to expert testimony and published reports. Our key areas of inquiry are the foundations of artificial intelligence — such as talent, data and computational power — as well as how AI can be used in cybersecurity and other national security settings. We also do research on the policy tools that can be used to shape AI’s development and use, and on biotechnology.

Report

China’s STI Operations

William Hannas Huey-Meei Chang
| January 2021

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.

China


Cybersecurity


Data, algorithms and models


Hardware and compute


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Analysis

AI Verification

Matthew Mittelsteadt
| February 2021

The rapid integration of artificial intelligence into military systems raises critical questions of ethics, design and safety. While many states and organizations have called for some form of “AI arms control,” few have discussed the technical details of verifying countries’ compliance with these regulations. This brief offers a starting point, defining the goals of “AI verification” and proposing several mechanisms to support arms inspections and continuous verification.

Analysis

Trusted Partners

Margarita Konaev Tina Huang Husanjot Chahal
| February 2021

As the U.S. military integrates artificial intelligence into its systems and missions, there are outstanding questions about the role of trust in human-machine teams. This report examines the drivers and effects of such trust, assesses the risks from too much or too little trust in intelligent technologies, reviews efforts to build trustworthy AI systems, and offers future directions for research on trust relevant to the U.S. military.

Data Visualization

Chinese State Council Budget Tracker

Ryan Fedasiuk Emily Weinstein Ben Murphy Alan Loera
| February 2021

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.

Data Brief

Using Machine Learning to Fill Gaps in Chinese AI Market Data

Zachary Arnold Joanne Boisson Lorenzo Bongiovanni Daniel Chou Carrie Peelman Ilya Rahkovsky
| February 2021

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.

Data Brief

From China to San Francisco: The Location of Investors in Top U.S. AI Startups

Rebecca Kagan Rebecca Gelles Zachary Arnold
| February 2021

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.

Data Brief

Corporate Investors in Top U.S. AI Startups

Rebecca Kagan Rebecca Gelles Zachary Arnold
| February 2021

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.

Translation

Measures for Cybersecurity Reviews

February 3, 2021

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.

Analysis

Assessing the Scope of U.S. Visa Restrictions on Chinese Students

Remco Zwetsloot Emily Weinstein Ryan Fedasiuk
| February 2021

In May 2020, the White House announced it would deny visas to Chinese graduate students and researchers who are affiliated with organizations that implement or support China’s military-civil fusion strategy. The authors discuss several ways this policy might be implemented. Based on Chinese and U.S. policy documents and data sources, they estimate that between three and five thousand Chinese students might be prevented from entering U.S. graduate programs each year.

Data Brief

Comparing Corporate and University Publication Activity in AI/ML

Simon Rodriguez Tim Hwang Rebecca Gelles
| January 2021

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.