Drawing from prior CSET research, this blog post describes different domestic and international initiatives the Chinese government and companies are pursuing to shore up investment in AI and meet China’s strategic objectives, as well as indicators to track their future trajectories.

Recent discussions of AI have focused on safety, reliability, and other risks. Lost in this debate is the real need to secure AI against malicious actors. This blog post applies lessons from traditional cybersecurity to emerging AI-model risks.

Existing U.S. government tools and approaches may help mitigate some of the issues worrying AI observers. This blog post describes long-standing “catch-all” controls, administered by the Department of Commerce’s Bureau of Industry and Security (BIS), and how they might be used to address some of these threats.

In the second of a series of publications, CSET and CNAS outline one avenue the U.S. government could pursue to cut off China’s access to cloud computing services in support of military, security, or intelligence services end use(r)s. The authors discuss pros, cons, and limitations.

In the first of a series of publications, CSET and CNAS outline one potential avenue for the U.S. government to cut off Chinese access to controlled chips via cloud computing, as well its pros, cons, and limitations.

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

The goal of this guide is to acquaint researchers and analysts with tools, resources, and best practices to ensure security when collecting or accessing open-source information.

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.