This research agenda provides a roadmap for the next phase of CSET’s line of research on the U.S. AI workforce. Our goal is to assist policymakers and other stakeholders in the national security community to create policies that will ensure the United States maintains its competitive advantage in AI talent. We welcome comments, feedback and input on this vision at cset@georgetown.edu.

This data brief explores how international collaboration relates to the impact and output of research publications. Focusing on the top 10 countries with the highest publication output from 2010 to 2019, the authors provide a comprehensive analysis across the major fields of science and technology.

Advances in robotics technology are having a transformative effect on how people work, travel, communicate, and fight wars. This data brief provides an overview of global trends in robotics patents between 2005 and 2019, focusing in particular on the state of robotics patenting in Russia, as well as developments in military robotics patents both in Russia and across the globe.

This report examines nearly 350 artificial intelligence-related equipment contracts awarded by the People’s Liberation Army and state-owned defense enterprises in 2020 to assess how the Chinese military is adopting AI. The report identifies China’s key AI defense industry suppliers, highlights gaps in U.S. export control policies, and contextualizes the PLA’s AI investments within China’s broader strategy to compete militarily with the United States.

Created through a joint partnership between CSET and the AI Education Project, the AI Education Catalog aims to raise awareness of the AI-related programs available to students and educators, as well as to help inform AI education and workforce policy.

Militaries around the world have often relied on the largest global defense companies to acquire and integrate cutting-edge technologies. This issue brief examines the investment and mergers and acquisition activities in artificial intelligence of the top 50 global defense companies — a key, if limited, approach to accessing AI innovation in the commercial sector — and assesses investment trends of their corporate venture capital subsidiaries and offers a geographic breakdown of defense companies and their AI target companies.

This policy brief addresses the need for a clearly defined artificial intelligence education and workforce policy by providing recommendations designed to grow, sustain, and diversify the U.S. AI workforce. The authors employ a comprehensive definition of the AI workforce—technical and nontechnical occupations—and provide data-driven policy goals. Their recommendations are designed to leverage opportunities within the U.S. education and training system while mitigating its challenges, and prioritize equity in access and opportunity to AI education and AI careers.

This policy brief, authored in collaboration with the MITRE Corporation, provides a new perspective on the U.S. Department of Defense’s struggle to recruit and retain artificial intelligence talent. The authors find that the DOD already has a cadre of AI and related experts, but that this talent remains hidden. Better leveraging this talent could go a long way in meeting the DOD’s AI objectives. The authors argue that this can be done through policies that more effectively identify AI talent and assignment opportunities, processes that incentivize experimentation and changes in career paths, and investing in the necessary technological infrastructure.

As U.S. policymakers grapple with the need to control international technology flows, this annotated bibliography distills key lessons and surveys 50 years of scholarship, government documents, and commentary. The resources it presents are at the intersection of international economics and technology and span from the Cold War to the current challenges surrounding U.S.-China relations.

A globally competitive AI workforce hinges on the education, development, and sustainment of the best and brightest AI talent. This issue brief compares efforts to integrate AI education in China and the United States, and what advantages and disadvantages this entails. The authors consider key differences in system design and oversight, as well as strategic planning. They then explore implications for the U.S. national security community.