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.

Annual Report

CSET at Five

Center for Security and Emerging Technology
| March 2024

In honor of CSET’s fifth birthday, this annual report is a look at CSET’s successes in 2023 and over the course of the past five years. It explores CSET’s different lines of research and cross-cutting projects, and spotlights some of its most impactful research products.

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See our original translation of a 2017 Wuhan City government document outlining policies to encourage the development of Wuhan's National Cybersecurity Talent and Innovation Base.

See our original translation of a 2012 PRC regulation governing the establishment, operation, and evaluation of state key laboratories housed in corporations.

See our original translation of a 2021 draft PRC government plan for the development of China's cybersecurity industry.

See our original translation of a 2016 PRC Ministry of Science and Technology press conference announcing the creation of China's overarching "National Key R&D Program."

A CSET original translation of 2021 PRC "Opinions" outlining new policies for Pudong New District in Shanghai, long a trendsetter in Chinese economic reform.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. Our first series of Snapshots introduced CSET’s Map of Science and explored the underlying data and analytic utility of this new tool, which enables users to interact with the Map directly.

Analysis

Small Data’s Big AI Potential

Husanjot Chahal Helen Toner Ilya Rahkovsky
| September 2021

Conventional wisdom suggests that cutting-edge artificial intelligence is dependent on large volumes of data. An overemphasis on “big data” ignores the existence—and underestimates the potential—of several AI approaches that do not require massive labeled datasets. This issue brief is a primer on “small data” approaches to AI. It presents exploratory findings on the current and projected progress in scientific research across these approaches, which country leads, and the major sources of funding for this research.

Analysis

Headline or Trend Line?

Margarita Konaev Andrew Imbrie Ryan Fedasiuk Emily S. Weinstein Katerina Sedova James Dunham
| August 2021

Chinese and Russian government officials are keen to publicize their countries’ strategic partnership in emerging technologies, particularly artificial intelligence. This report evaluates the scope of cooperation between China and Russia as well as relative trends over time in two key metrics of AI development: research publications and investment. The findings expose gaps between aspirations and reality, bringing greater accuracy and nuance to current assessments of Sino-Russian tech cooperation.

Data Snapshot

Concentrations of AI-related Topics in Research: Computer Vision

Autumn Toney
| August 25, 2021

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. Our first series of Snapshots introduced CSET’s Map of Science and explored the underlying data and analytic utility of this new tool, which enables users to interact with the Map directly.

Analysis

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.