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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Reports

The DOD’s Hidden Artificial Intelligence Workforce

Diana Gehlhaus, Ron Hodge, Luke Koslosky, Kayla Goode, and Jonathan Rotner
| September 2021

This policy brief, authored in collaboration with the MITRE Corporation, provides a new perspective on the U.S. Department of Defense’s struggle to recruit and retain artificial intelligence talent. The authors find that the DOD already has a cadre of AI and related experts, but that this talent remains hidden. Better leveraging this talent could go a long way in meeting the DOD’s AI objectives. The authors argue that this can be done through policies that more effectively identify AI talent and assignment opportunities, processes that incentivize experimentation and changes in career paths, and investing in the necessary technological infrastructure.

Reports

AI Education in China and the United States

Dahlia Peterson, Kayla Goode, and Diana Gehlhaus
| September 2021

A globally competitive AI workforce hinges on the education, development, and sustainment of the best and brightest AI talent. This issue brief compares efforts to integrate AI education in China and the United States, and what advantages and disadvantages this entails. The authors consider key differences in system design and oversight, as well as strategic planning. They then explore implications for the U.S. national security community.

Reports

Education in China and the United States

Dahlia Peterson, Kayla Goode, and Diana Gehlhaus
| September 2021

A globally competitive AI workforce hinges on the education, development, and sustainment of the best and brightest AI talent. This issue brief provides an overview of the education systems in China and the United States, lending context to better understand the accompanying main report, “AI Education in China and the United States: A Comparative Assessment.”

Reports

Responsible and Ethical Military AI

Zoe Stanley-Lockman
| August 2021

Allies of the United States have begun to develop their own policy approaches to responsible military use of artificial intelligence. This issue brief looks at key allies with articulated, emerging, and nascent views on how to manage ethical risk in adopting military AI. The report compares their convergences and divergences, offering pathways for the United States, its allies, and multilateral institutions to develop common approaches to responsible AI implementation.

Reports

Military AI Cooperation Toolbox

Zoe Stanley-Lockman
| August 2021

The Department of Defense can already begin applying its existing international science and technology agreements, global scientific networks, and role in multilateral institutions to stimulate digital defense cooperation. This issue brief frames this collection of options as a military AI cooperation toolbox, finding that the available tools offer valuable pathways to align policies, advance research, development, and testing, and to connect personnel–albeit in more structured ways in the Euro-Atlantic than in the Indo-Pacific.

Data Brief

China is Fast Outpacing U.S. STEM PhD Growth

Remco Zwetsloot, Jack Corrigan, Emily S. Weinstein, Dahlia Peterson, Diana Gehlhaus, and Ryan Fedasiuk
| August 2021

Since the mid-2000s, China has consistently graduated more STEM PhDs than the United States, a key indicator of a country’s future competitiveness in STEM fields. This paper explores the data on STEM PhD graduation rates and projects their growth over the next five years, during which the gap between China and the United States is expected to increase significantly.

Data Brief

U.S. AI Summer Camps

Claire Perkins and Kayla Goode
| August 2021

Summer camps are an integral part of many U.S. students’ education, but little is known about camps that focus on artificial intelligence education. This data brief maps out the AI summer camp landscape in the United States and explores the camps’ locations, target age ranges, price, and hosting organization type.

Data Brief

China’s Robotics Patent Landscape

Sara Abdulla
| August 2021

Since 2011, China has dramatically grown its robotics sector as part of its mission to achieve technological leadership. The Chinese government has encouraged this growth through incentives and, in some cases, subsidies. Patents in robotics have surged, particularly at Chinese universities; by contrast, private companies comprise the bulk of robotics patent filers around the world. China has also seen a corresponding growth in robotics purchasing and active robotics stock. This data brief explores the trends in robotics patent families published from China as a measure of robotics advancement and finds that China is on track to emerge as a world leader in robotics.

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.