In an opinion piece for The Hill, Research Fellow Diana Gehlhaus calls for a clear U.S. AI workforce policy if the U.S. wants to be the leader in AI talent drawing from her latest report.

In her latest CSET report, Research Fellow Diana Gehlhaus discusses the United States' lack of a defined AI education and AI workforce policy, and offers policy recommendations.

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.

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.

CSET submitted this comment to the Office of Science and Technology Policy and the National Science Foundation to support the work of the National Artificial Intelligence Research Resource (NAIRR) Task Force to develop an implementation roadmap that would provide AI researchers and students across scientific disciplines access to computational resources, high-quality data, educational tools, and user support.

The CSET Legislation Tracker serves as a resource to identify and monitor U.S. federal legislation related to emerging technology and national security, with a particular focus on measures relevant to CSET’s key areas of inquiry such as research security, S&T development, and funding for hardware design and manufacturing capabilities. The tracker includes identifying information for each piece of legislation, links to related CSET analyses, and access to associated congressional hearings, among other items.

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.”