This data brief identifies the most influential AI researchers in the United States between 2010 and 2021 via three metrics: number of AI publications, citations, and AI h-index. It examines their demographic profiles, career trajectories, and research collaboration rates, finding that most are men in the later stages of their career, largely concentrated in 10 elite universities and companies, and that nearly 70 percent of America’s top AI researchers were born abroad.

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.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This short series explores how government procurement data can shed light on federal technological interest and utilization. It analyzes contract metadata, provided in a collaborative project with Govini, to track key emerging technologies through the federal procurement process.

The choice of method for surfacing AI-relevant publications impacts the ultimate research findings. This report provides a quantitative analysis of various methods available to researchers for identifying AI-relevant research within CSET’s merged corpus, and showcases the research implications of each method.

China has poured resources into improving the resilience of its space architecture. But how much progress has Beijing made? This issue brief analyzes China’s space resilience efforts and identifies areas where the United States may need to invest to keep pace.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This short series explores how government procurement data can shed light on federal technological interest and utilization. It analyzes contract metadata, provided in a collaborative project with Govini, to track key emerging technologies through the federal procurement process.

When the technology and policy communities use terms associated with trustworthy AI, could they be talking past one another? This paper examines the use of trustworthy AI keywords and the potential for an “Inigo Montoya problem” in trustworthy AI, inspired by "The Princess Bride" movie quote: “You keep using that word. I do not think it means what you think it means.”

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This five-part series uses data from the U.S. Department of Education and other select sources to complement existing CSET work on the U.S. AI workforce.

U.S. tech companies have played a critical role in the international effort to support and defend Ukraine against Russia. To better understand and envision how these companies can help U.S. strategic interests, CSET convened a group of industry experts and former government leaders to discuss lessons learned from the ongoing war in Ukraine and what those lessons might mean for the future. The workshop’s discussion and this accompanying report expand on the themes explored in the October 2022 "Foreign Affairs" article, "Big Tech Goes to War."

Policymakers, engineers, program managers and operators need the bedrock of a common set of terms to instantiate responsible AI for the Department of Defense. Rather than create a DOD-specific set of terms, this paper argues that the DOD could benefit by adopting the key characteristics defined by the National Institute of Standards and Technology in its draft AI Risk Management Framework with only two exceptions.