Publications

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

CSET’s 2024 Annual Report

Center for Security and Emerging Technology
| March 2025

In 2024, CSET continued to deliver impactful, data-driven analysis at the intersection of emerging technology and security policy. Explore our annual report to discover key research highlights, expert testimony, and new analytical tools — all aimed at shaping informed, strategic decisions around AI and emerging tech.

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PARAT – Tracking the Activity of AI Companies

Rebecca Gelles, Zachary Arnold, Ngor Luong, and Jennifer Melot
| June 2021

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.

Reports

U.S. Demand for AI Certifications

Diana Gehlhaus and Ines Pancorbo
| June 2021

This issue brief explores whether artificial intelligence and AI-related certifications serve as potential pathways to enter the U.S. AI workforce. The authors find that according to U.S. AI occupation job postings data over 2010–2020, there is little demand from employers for AI and AI-related certifications. From this perspective, such certifications appear to present more hype than promise.

Reports

U.S. AI Workforce

Diana Gehlhaus and Ilya Rahkovsky
| April 2021

A lack of good data on the U.S. artificial intelligence workforce limits the potential effectiveness of policies meant to increase and cultivate this cadre of talent. In this issue brief, the authors bridge that information gap with new analysis on the state of the U.S. AI workforce, along with insight into the ongoing concern over AI talent shortages. Their findings suggest some segments of the AI workforce are more likely than others to be experiencing a supply-demand gap.

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.

CSET Research Analyst Emily Weinstein 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." Weinstein discussed China's military-civil fusion strategy in university investment firms and Chinese talent programs.

Reports

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

Remco Zwetsloot, Emily S. Weinstein, and 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.

Reports

The U.S. AI Workforce

Diana Gehlhaus and Santiago Mutis
| January 2021

As the United States seeks to maintain a competitive edge in artificial intelligence, the strength of its AI workforce will be of paramount importance. In order to understand the current state of the domestic AI workforce, Diana Gehlhaus and Santiago Mutis define the AI workforce and offer a preliminary assessment of its size, composition, and key characteristics. Among their findings: The domestic supply of AI talent consisted of an estimated 14 million workers (or about 9% of total U.S. employment) as of 2018.

Data Brief

Most of America’s “Most Promising” AI Startups Have Immigrant Founders

Tina Huang, Zachary Arnold, and Remco Zwetsloot
| October 2020

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.

Reports

Estimating the Number of Chinese STEM Students in the United States

Jacob Feldgoise and Remco Zwetsloot
| October 2020

In recent years, concern has grown about the risks of Chinese nationals studying science, technology, engineering and mathematics (STEM) subjects at U.S. universities. This data brief estimates the number of Chinese students in the United States in detail, according to their fields of study and degree level. Among its findings: Chinese nationals comprise 16 percent of all graduate STEM students and 2 percent of undergraduate STEM students, lower proportions than were previously suggested in U.S. government reports.

Data Brief

U.S. Demand for AI-Related Talent Part II: Degree Majors and Skills Assessment

Autumn Toney and Melissa Flagg
| September 2020

Future U.S. competitiveness in artificial intelligence will require a robust AI workforce. This data brief analyzes market demand for AI-related jobs to determine the skills necessary in the field. It concerns jobs considered both “core AI” and “AI-adjacent.”