In an article by Nikkei Asia, CSET's Lauren Kahn provided her expert analysis on Baykar Technology, a Turkish drone maker, has achieved global recognition by producing the Bayraktar TB2 armed drone.

This data brief uses procurement records published by the U.S. Department of Defense and China’s People’s Liberation Army between April and November of 2020 to assess, and, where appropriate, compare what each military is buying when it comes to artificial intelligence. We find that the two militaries are prioritizing similar application areas, especially intelligent and autonomous vehicles and AI applications for intelligence, surveillance and reconnaissance.

In a recent Bloomberg article, CSET's Helen Toner provides her expert analysis on Beijing's implementation of fresh regulations governing artificial intelligence (AI) services.

In his op-ed featured in Defense One, Jaret Riddick discusses the need for the Pentagon to leverage existing laws and new metrics to enhance the research capacity of historically Black colleges and universities (HBCUs) in the United States.

On November 1, 2023, CSET will be co-hosting the all day Kalaris Conference with Georgetown's Center for Security Studies. This year's event focuses on "Decision Advantage: Emerging Technology Opportunities and Challenges for U.S. Intelligence." Join us in person or virtually for exciting panel discussions and keynotes.

In his op-ed featured in Breaking Defense, CSET's Sam Bresnick from offers a deep dive into China's remarkable progress in bolstering space resilience, with a specific focus on tactically responsive space launch (TRSL).

Collaborations between researchers and policymakers are necessary for progress, but can be challenging in practice. This blog post reports on recent discussions by privacy experts on the obstacles they face when engaging in the policy space and advice on how to improve these barriers.

On July 21, the White House announced voluntary commitments from seven AI firms to ensure safe, secure, and transparent AI. CSET’s research provides important context to this discussion.

With the rapid integration of AI into our daily lives, we must all learn when and whether to trust the technology, understand its capabilities and limitations, and adapt as these systems — and our functional relationships with them — evolve.

Artificial intelligence-enabled systems are transforming society and driving an intense focus on what policy and technical communities can do to ensure that those systems are trustworthy and used responsibly. This analysis draws on prior work about the use of trustworthy AI terms to identify 18 clusters of research papers that contribute to the development of trustworthy AI. In identifying these clusters, the analysis also reveals that some concepts, like "explainability," are forming distinct research areas, whereas other concepts, like "reliability," appear to be accepted as metrics and broadly applied.