A CSET report estimated that China spent $1.6 billion to $5.4 billion on civilian AI research and development.

China is banking on applying AI to biotechnology research in order to transform itself into a “biotech superpower.” In pursuit of that goal, it has emphasized bringing together different aspects of the development cycle to foster multidisciplinary research. This data brief examines the emerging trend of co-location of AI and biotechnology researchers and explores the potential impact it will have on this growing field.

Through the Quad forum, the United States, Australia, Japan and India have committed to pursuing an open, accessible and secure technology ecosystem and offering a democratic alternative to China’s techno-authoritarian model. This report assesses artificial intelligence collaboration across the Quad and finds that while Australia, Japan and India each have close AI-related research and investment ties to both the United States and China, they collaborate far less with one another.

CSET Director Dewey Murdick described how institutions programs like Georgetown's Tech & Society help CSET deliver evidence-driven analysis to key policy-makers.

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.

In an interview with The Wire China, Research Fellow Emily Weinstein discusses the future of research security and collaboration with China with the end of the China Initiative.

CSET submitted this comment to the Office of Science and Technology Policy on updating the National Artificial Intelligence Research and Development Strategic Plan.

Research Analyst Emily Weinstein discusses the end of the U.S. Department of Justice's China Initiative and its after-effects for academia.

Heather Frase was a Senior Fellow at CSET, focused on AI Standards and Testing.

Problems of AI safety are the subject of increasing interest for engineers and policymakers alike. This brief uses the CSET Map of Science to investigate how research into three areas of AI safety — robustness, interpretability and reward learning — is progressing. It identifies eight research clusters that contain a significant amount of research relating to these three areas and describes trends and key papers for each of them.