Dewey Murdick is the Director at Georgetown’s Center for Security and Emerging Technology (CSET). He serves as an unpaid advisor to several organizations: the OECD Network of Experts on AI (ONE AI); Global Partnership on AI (GPAI) Data Governance Working Group; the Center for a New American Security (CNAS) Task Force on AI and National Security; and CEIMIA, where he is a member of the board of directors. Prior to joining CSET as its founding Director of Data Science, he was the Director of Science Analytics at the Chan Zuckerberg Initiative, where he led metric development, data science, and machine learning and statistical research for scientist-facing products and science-related initiatives. Dewey served as Chief Analytics Officer and Deputy Chief Scientist within the Department of Homeland Security. At the Intelligence Advanced Research Projects Activity (IARPA), he co-founded an office in anticipatory intelligence and led programs in high-risk, high-payoff research in support of national security missions. He has also held positions in intelligence analysis, research, software development and contract teaching.

Dewey’s research interests include connecting research and emerging technology to future capabilities, emerging technology forecasting, strategic planning, research portfolio management and policymaker support. He holds a Ph.D. in Engineering Physics from the University of Virginia and a B.S. in Physics from Andrews University.

CSET Director Dewey Murdick testified before the Senate Select Committee on Intelligence hearing on "Countering the People’s Republic of China’s Economic and Technological Plan for Dominance." Murdick discussed China's strategy to move towards self-sufficiency in key technologies and steps the United States can take to respond.

New analytic tools are used in this data brief to explore the public artificial intelligence (AI) research portfolio of China’s security forces. The methods contextualize Chinese-language scholarly papers that claim a direct working affiliation with components of the Ministry of Public Security, People's Armed Police Force, and People’s Liberation Army. The authors review potential uses of computer vision, robotics, natural language processing and general AI research.

Future Indices

October 2020

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. This issue brief used recent forecast data to illustrate Foretell’s methodology.

Establishing a new open-source National Science and Technology Analysis Center

Patent data can provide insights into the most active countries, fields and organizations in artificial intelligence research. This data brief analyzes worldwide trends in AI patenting to offer metrics on inventive activity.

The task of artificial intelligence policymaking is complex and challenging, made all the more difficult by such a rapidly evolving technology. In order to address the security and economic implications of AI, policymakers must be able to viably define, categorize and assess AI research and technology. In this issue brief, CSET puts forward a functional definition of AI, based on three core principles, that significantly outperforms methods developed over the last decade.

CSET's Director of Data Science, Dewey Murdick, joined Federal Drive with Tom Temin to discuss CORD-19, a collaboration between the White House and research groups coordinated by CSET to aggregate scholarly articles on the coronavirus.