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

Staying Ahead

Diana Gehlhaus
| November 2021

This research agenda provides a roadmap for the next phase of CSET’s line of research on the U.S. AI workforce. Our goal is to assist policymakers and other stakeholders in the national security community to create policies that will ensure the United States maintains its competitive advantage in AI talent. We welcome comments, feedback and input on this vision at cset@georgetown.edu.

Data Brief

Trends in Robotics Patents

Margarita Konaev and Sara Abdulla
| November 2021

Advances in robotics technology are having a transformative effect on how people work, travel, communicate, and fight wars. This data brief provides an overview of global trends in robotics patents between 2005 and 2019, focusing in particular on the state of robotics patenting in Russia, as well as developments in military robotics patents both in Russia and across the globe.

Data Visualization

AI Education Catalog

Claire Perkins, Diana Gehlhaus, Kayla Goode, Jennifer Melot, Ehrik Aldana, Grace Doerfler, and Gayani Gamage
| October 2021

Created through a joint partnership between CSET and the AI Education Project, the AI Education Catalog aims to raise awareness of the AI-related programs available to students and educators, as well as to help inform AI education and workforce policy.

Reports

U.S. AI Workforce: Policy Recommendations

Diana Gehlhaus, Luke Koslosky, Kayla Goode, and Claire Perkins
| October 2021

This policy brief addresses the need for a clearly defined artificial intelligence education and workforce policy by providing recommendations designed to grow, sustain, and diversify the U.S. AI workforce. The authors employ a comprehensive definition of the AI workforce—technical and nontechnical occupations—and provide data-driven policy goals. Their recommendations are designed to leverage opportunities within the U.S. education and training system while mitigating its challenges, and prioritize equity in access and opportunity to AI education and AI careers.

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.”

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.

CSET Senior Fellow Anna Puglisi testified before the Senate Select Committee on Intelligence on "Beijing's Long Arm: Threats to U.S. National Security." She offered recommendations to counter China's S&T collection efforts.

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.