Research

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 AI — such as talent, data and computational power — as well as how it can be used in cybersecurity and other national security settings. We also do research focusing on the policy tools that can be used to shape AI’s development and use.

Report

Automating Cyber Attacks

Ben Buchanan John Bansemer Dakota Cary Jack Lucas Micah Musser
| November 2020

Based on an in-depth analysis of artificial intelligence and machine learning systems, the authors consider the future of applying such systems to cyber attacks, and what strategies attackers are likely or less likely to use. As nuanced, complex, and overhyped as machine learning is, they argue, it remains too important to ignore.

Cybersecurity


Data, algorithms and models


Hardware and compute


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Analysis

Universities and the Chinese Defense Technology Workforce

Ryan Fedasiuk Emily Weinstein
| December 2020

To help U.S. policymakers address long-held concerns about risks and threats associated with letting Chinese university students or graduates study in the United States, CSET experts examine which forms of collaboration, and with which Chinese universities, pose the greatest risk to U.S. research security.

See our original translation of a statistical report by the PRC Ministry of Science and Technology detailing changes in China's research and development personnel pool.

See our original translation of the Chinese Communist Party (CCP) proposal—approved at the Fifth Plenum of the 19th CCP Central Committee in late October 2020—on China's 14th Five-Year Plan.

Analysis

Automating Cyber Attacks

Ben Buchanan John Bansemer Dakota Cary Jack Lucas Micah Musser
| November 2020

Based on an in-depth analysis of artificial intelligence and machine learning systems, the authors consider the future of applying such systems to cyber attacks, and what strategies attackers are likely or less likely to use. As nuanced, complex, and overhyped as machine learning is, they argue, it remains too important to ignore.

Data Brief

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

Cindy Martinez 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.

Data Visualization

Chinese Talent Program Tracker

Emily Weinstein
| November 2020

China operates a number of party- and state-sponsored talent programs to recruit researchers -- Chinese citizens and non-citizens alike -- to bolster its strategic civilian and military goals. CSET has created a tracker to catalog publicly available information about these programs. This catalog is a work in progress; if you have further information on programs currently not included in it -- or if you spot an error -- please complete the form at http://bit.ly/ChineseTalent

See our original translation of a speech given by Chinese President Xi Jinping in April 2020 at the seventh meeting of the Central Financial and Economic Affairs Commission.

Is there a rift between the U.S. tech sector and the Department of Defense? To better understand this relationship, CSET surveyed U.S. AI industry professionals about their views toward working on DOD-funded AI projects. The authors find that these professionals hold a broad range of opinions about working with DOD. Among the key findings: Most AI professionals are positive or neutral about working on DOD-funded AI projects, and willingness to work with DOD increases for projects with humanitarian applications.

Destructive Cyber Operations and Machine Learning

Dakota Cary 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.

Data Brief

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

Tina Huang Zachary Arnold 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.