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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Formal Response

Comment on BIS Request for Information

Jacob Feldgoise Hanna Dohmen
| April 30, 2024

Jacob Feldgoise and Hanna Dohmen at the Center for Security and Emerging Technology (CSET) at Georgetown University offer the following response to the Bureau of Industry and Security’s (BIS) Notice of Proposed Rulemaking (NPRM): Taking Additional Steps To Address the National Emergency With Respect to Significant Malicious Cyber-Enabled Activities (89 FR 5698).

CSET's Ngor Luong testified before the U.S.-China Economic and Security Review Commission where she discussed Chinese investments in military applications of AI.

CSET's Jack Corrigan testified before the U.S.-China Economic and Security Review Commission where he discussed security threats posed by Chinese information and communications technology systems.

Formal Response

Comment on Advanced Computing Chips Rule

Jacob Feldgoise Hanna Dohmen
| January 17, 2024

On January 17, 2024, CSET Researchers submitted a response to proposed rules from the Bureau of Industry and Security at the U.S. Department of Commerce. In the submission, CSET recommends that Commerce not implement controls on U.S. companies providing IaaS to Chinese entities, among other recommendations.

Data Brief

Spurring Science

Christian Schoeberl Hanna Dohmen
| November 2023

This data brief analyzes over 200,000 U.S. government grants awarded to industry and academic recipients for artificial intelligence research between January 2017 and May 2023. The authors find that while the majority of federal grants are awarded to academic recipients, industry played an outsized role in U.S. government grant funding of AI research. Moreover, departments within the U.S. Department of Defense appear to prioritize funding industry and AI research relative to other funding agencies.

Data Snapshot

BIS Best Data Practices: Part 2

Christian Schoeberl
| November 16, 2023

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This is the second installment of a two-part series of data snapshots that explores export control data from the Bureau of Industry and Security (BIS), namely the 2021 and 2022 yearly reports for trade with China and Hong Kong.

Data Snapshot

BIS Best Data Practices: Part 1

Christian Schoeberl
| November 3, 2023

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This is the first installment of a two-part series of data snapshots that explores export control data from the Bureau of Industry and Security (BIS), namely the 2021 and 2022 yearly reports for trade with China and Hong Kong.

Analysis

Decoding Intentions

Andrew Imbrie Owen Daniels Helen Toner
| October 2023

How can policymakers credibly reveal and assess intentions in the field of artificial intelligence? Policymakers can send credible signals of their intent by making pledges or committing to undertaking certain actions for which they will pay a price—political, reputational, or monetary—if they back down or fail to make good on their initial promise or threat. Talk is cheap, but inadvertent escalation is costly to all sides.

Other

Techniques to Make Large Language Models Smaller: An Explainer

Kyle Miller Andrew Lohn
| October 11, 2023

This explainer overviews techniques to produce smaller and more efficient language models that require fewer resources to develop and operate. Importantly, information on how to leverage these techniques, and many of the subsequent small models, are openly available online for anyone to use. The combination of both small (i.e., easy to use) and open (i.e., easy to access) could have significant implications for artificial intelligence development.

In collaboration with colleagues from CNAS and the Atlantic Council, CSET Researchers Ngor Luong and Emily Weinstein provided this comment in request to Treasury's Advanced Notice of Rule-making request for public comment (TREAS-DO-2023-0009-0001).