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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Data Brief

U.S. Demand for Talent at the Intersection of AI and Cybersecurity

Cindy Martinez and Micah Musser
| November 2020

As demand for cybersecurity experts in the United States has grown faster than the supply of qualified workers, some organizations have turned to artificial intelligence to bolster their overwhelmed cyber teams. Organizations may opt for distinct teams that specialize exclusively in AI or cybersecurity, but there is a benefit to having employees with overlapping experience in both domains. This data brief analyzes hiring demand for individuals with a combination of AI and cybersecurity skills.

Reports

Destructive Cyber Operations and Machine Learning

Dakota Cary and Daniel Cebul
| November 2020

Machine learning may provide cyber attackers with the means to execute more effective and more destructive attacks against industrial control systems. As new ML tools are developed, CSET discusses the ways in which attackers may deploy these tools and the most effective avenues for industrial system defenders to respond.

Reports

Downscaling Attack and Defense

Andrew Lohn
| October 7, 2020

The resizing of images, which is typically a required part of preprocessing for computer vision systems, is vulnerable to attack. Images can be created such that the image is completely different at machine-vision scales than at other scales and the default settings for some common computer vision and machine learning systems are vulnerable.

Reports

Tracking AI Investment

Zachary Arnold, Ilya Rahkovsky, and Tina Huang
| September 2020

The global AI industry is booming, with privately held firms pulling in nearly $40 billion in disclosed investment in 2019 alone. U.S. companies continue to attract the majority of that funding—64 percent of it in 2019—but that lead is not guaranteed. This report analyzes AI investment data from 2015 to 2019 to help better understand trends in the global AI landscape.

Reports

System Re-engineering

Melissa Flagg and Paul Harris
| September 2020

The United States must adopt a new approach to R&D policy to optimize the diversity of the current system, manage the risks of system dispersion and deliver the benefits of R&D to society. This policy brief provides a new framework for understanding the U.S. R&D ecosystem and recommendations for repositioning the role of the federal government in R&D.

Data Brief

Patents and Artificial Intelligence

Dewey Murdick
| September 2020

Patent data can provide insights into the most active countries, fields and organizations in artificial intelligence research. This data brief analyzes worldwide trends in AI patenting to offer metrics on inventive activity.

Reports

Mainframes: A Provisional Analysis of Rhetorical Frames in AI

Andrew Imbrie, James Dunham, Rebecca Gelles, and Catherine Aiken
| August 2020

Are great powers engaged in an artificial intelligence arms race? This issue brief explores the rhetorical framing of AI by analyzing more than 4,000 English-language articles over a seven-year period. Among its findings: a growing number of articles frame AI development as a competition, but articles using the competition frame represent a declining proportion of articles about AI.

One sentence summarizes the complexities of modern artificial intelligence: Machine learning systems use computing power to execute algorithms that learn from data. This AI triad of computing power, algorithms, and data offers a framework for decision-making in national security policy.

Reports

Deepfakes: A Grounded Threat Assessment

Tim Hwang
| July 2020

The rise of deepfakes could enhance the effectiveness of disinformation efforts by states, political parties and adversarial actors. How rapidly is this technology advancing, and who in reality might adopt it for malicious ends? This report offers a comprehensive deepfake threat assessment grounded in the latest machine learning research on generative models.

Reports

Shaping the Terrain of AI Competition

Tim Hwang
| June 2020

How should democracies effectively compete against authoritarian regimes in the AI space? This report offers a “terrain strategy” for the United States to leverage the malleability of artificial intelligence to offset authoritarians' structural advantages in engineering and deploying AI.