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).

China’s brain-computer interface research has two dimensions. Besides its usual applications in neuropathology, China is extending the benefits of BCI to the general population, aiming at enhanced cognition and a “merger” of natural and artificial intelligence. This report, authored in collaboration with researchers from the Department of War Studies at King’s College London uses bibliometric analysis and expert assessment of technical documents to evaluate China’s BCI, and conclude that the research is on track to achieve its targets.

Research participants who read propaganda generated by GPT-3 davinci (a large language model) were nearly as persuaded as those who read real propaganda from Iran or Russia, according to a new peer-reviewed study by Josh A. Goldstein and co-authors.

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.

This data snapshot is the first in a series on CSET’s cybersecurity jobs data, a new dataset created by classifying data from 513 million LinkedIn user profiles. Here, we offer an overview of its creation and explore some use cases for analysis.

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.

Strengthening the federal cyber workforce is one of the main priorities of the National Cyber Workforce and Education Strategy. The National Science Foundation’s CyberCorps Scholarship-for-Service program is a direct cyber talent pipeline into the federal workforce. As the program tries to satisfy increasing needs for cyber talent, it is apparent that some form of program expansion is needed. This policy brief summarizes trends from participating institutions to understand how the program might expand and illustrates a potential future artificial intelligence (AI) federal scholarship-for-service program.

While recent progress in artificial intelligence (AI) has relied primarily on increasing the size and scale of the models and computing budgets for training, we ask if those trends will continue. Financial incentives are against scaling, and there can be diminishing returns to further investment. These effects may already be slowing growth among the very largest models. Future progress in AI may rely more on ideas for shrinking models and inventive use of existing models than on simply increasing investment in compute resources.

Concerns over risks from generative artificial intelligence systems have increased significantly over the past year, driven in large part by the advent of increasingly capable large language models. But, how do AI developers attempt to control the outputs of these models? This primer outlines four commonly used techniques and explains why this objective is so challenging.