Recent op-eds comparing the United States’ and China’s artificial intelligence (AI) programs fault the former for its focus on artificial general intelligence (AGI) while praising China for its success in applying AI throughout the whole of society. These op-eds overlook an important point: although China is outpacing the United States in diffusing AI across its society, China has by no means de-emphasized its state-sponsored pursuit of AGI.

Over the past year, artificial intelligence has quickly become a focal point in K-12 education. This blog post describes new and existing K-12 AI education efforts so that U.S. policymakers and other decision-makers may better understand what’s happening in practice.

The Carnegie Classification of Institutions of Higher Education is making changes to drastically simplify the criteria that determine its highly coveted R1 top-tier research classification. Last year, CSET Senior Fellow, Jaret Riddick, wrote about a new law from Congress, Section 223 of the 2023 National Defense Authorization Act, intended to leverage existing Carnegie classification criteria to increase defense research capacity for historically Black colleges and universities. Now, research is needed to understand how the changes proposed for 2025 classification criteria impact U.S. Department of Defense goals for eligible HBCU partners.

This guide provides a run-down of CSET’s research since 2019 for first-time visitors and long-term fans alike. Quickly get up to speed on our “must-read” research and learn about how we organize our work.

Recent announcements from both Pentagon and Congressional leaders offer significant opportunity for rapidly delivering autonomous systems technology at-scale for U.S. Warfighters well into the future. Dr. Jaret Riddick, CSET Senior Fellow and former Principal Director for Autonomy in USD(R&E) offers his perspective on DOD’s Replicator Initiative and recent legislative proposals about DOD autonomy.

CSET has received a lot of questions about LLMs and their implications. But questions and discussions tend to miss some basics about LLMs and how they work. In this blog post, we ask CSET’s NLP Engineer, James Dunham, to help us explain LLMs in plain English.

Machine learning advances have powered the development of new and more powerful generative language models. These systems are increasingly able to write text at near human levels. In a new report, authors at CSET, OpenAI, and the Stanford Internet Observatory explore how language models could be misused for influence operations in the future, and they provide a framework for assessing potential mitigation strategies.

CSET's Daniel Chou provides an update on previous CSET research exploring China's security forces' AI research portfolio.

The transfer of national security relevant technology—to peer competitors especially—is a well-documented problem and must be balanced with the benefits of free exchange. The following propositions covering six facets of the transfer issue reflect CSET’s current recommendations on the matter.

Foretell was CSET's crowd forecasting pilot project focused on technology and security policy. It connected historical and forecast data on near-term events with the big-picture questions that are most relevant to policymakers. In January 2022, Foretell became part of a larger forecasting program to support U.S. government policy decisions called INFER, which is run by the Applied Research Laboratory for Intelligence and Security at the University of Maryland and Cultivate Labs.