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.

Filter publications
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

China’s CyberAI Talent Pipeline

Dakota Cary
| July 2021

To what extent does China’s cultivation of talent in cybersecurity and AI matter in terms of competitiveness with other countries? Right now, it seems to have an edge: China’s 11 World-Class Cybersecurity Schools offer more classes on artificial intelligence and machine learning than do the 20 U.S. universities certified as Centers of Academic Excellence in Cyber Operations. This policy brief recommends tracking 13 research grants from the National Science Foundation that attempt to integrate AI into cybersecurity curricula.

Data Visualization

National Cybersecurity Center Map

Dakota Cary and Jennifer Melot
| July 2021

China wants to be a “cyber powerhouse” (网络强国). At the heart of this mission is the sprawling 40 km2 campus of the National Cybersecurity Center. Formally called the National Cybersecurity Talent and Innovation Base (国家网络安全人才与创新基地), the NCC is being built in Wuhan. The campus, which China began constructing in 2017 and is still building, includes seven centers for research, talent cultivation, and entrepreneurship; two government-focused laboratories; and a National Cybersecurity School.

Reports

China’s National Cybersecurity Center

Dakota Cary
| July 2021

China’s National Cybersecurity Center (NCC) resides on a 40 km2 plot in Wuhan. As one indication of its significance, the Chinese Communist Party’s highest-ranking members have an oversight committee for the facility. Over the next decade, the NCC will provide the talent, innovation, and indigenization of cyber capabilities that China’s Ministry of State Security, Ministry of Public Security, and People’s Liberation Army Strategic Support Force hacking teams lack. Though still under construction, the NCC’s first class of graduates will cross the stage in June 2022.

Reports

Poison in the Well

Andrew Lohn
| June 2021

Modern machine learning often relies on open-source datasets, pretrained models, and machine learning libraries from across the internet, but are those resources safe to use? Previously successful digital supply chain attacks against cyber infrastructure suggest the answer may be no. This report introduces policymakers to these emerging threats and provides recommendations for how to secure the machine learning supply chain.

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

Machine Learning and Cybersecurity

Micah Musser and Ashton Garriott
| June 2021

Cybersecurity operators have increasingly relied on machine learning to address a rising number of threats. But will machine learning give them a decisive advantage or just help them keep pace with attackers? This report explores the history of machine learning in cybersecurity and the potential it has for transforming cyber defense in the near future.

Reports

Truth, Lies, and Automation

Ben Buchanan, Andrew Lohn, Micah Musser, and Katerina Sedova
| May 2021

Growing popular and industry interest in high-performing natural language generation models has led to concerns that such models could be used to generate automated disinformation at scale. This report examines the capabilities of GPT-3--a cutting-edge AI system that writes text--to analyze its potential misuse for disinformation. A model like GPT-3 may be able to help disinformation actors substantially reduce the work necessary to write disinformation while expanding its reach and potentially also its effectiveness.

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.