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.

CSET's machine learning primer "Hacking AI" illustrates how hackers can access AI systems and argues for policymakers to build a robust and transparent AI for military systems.

According to The Hill, China is outpacing the U.S.' development of frontier technologies in part due to China's asymmetric STEM talent. According to a CSET brief, China produces twice as many STEM PhDs annually compared to the U.S.

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.

Research Analyst Emily Weinstein spoke with University World News about continued collaboration between Chinese and American university researchers amidst tensions from the China Initiative.

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.

A globally competitive AI workforce hinges on the education, development, and sustainment of the best and brightest AI talent. This issue brief provides an overview of the education systems in China and the United States, lending context to better understand the accompanying main report, “AI Education in China and the United States: A Comparative Assessment.”

CSET's Anna Puglisi unpacks how US exports are affecting China's access to scientific research equipment.

A new CSET report "Headline or Trend Line? Evaluating Chinese-Russian Collaboration in AI" uses data-backed analysis to address the Sino-Russian partnership and its effect on U.S. strategic interests.

In her latest opinion piece, CSET's Husanjot Chahal outlines a roadmap for the United States and India to collaborate on AI applications.