CSET Research Analyst Dahlia Peterson testified before the U.S.-China Economic and Security Review Commission at a hearing on "China’s Challenges and Capabilities in Educating and Training the Next Generation Workforce."

China’s government has pushed the country’s technology and financial firms to expand abroad, and Southeast Asia’s growing economies — and AI companies — offer promising opportunities. This report examines the scope and nature of Chinese investment in the region. It finds that China currently plays a limited role in Southeast Asia’s emerging AI markets outside of Singapore and that Chinese investment activity still trails behind that of the United States. Nevertheless, Chinese tech companies, with support from the Chinese government, have established a broad range of other AI-related linkages with public and commercial actors across Southeast Asia.

U.S. policies on artificial intelligence education and the AI workforce must grow, cultivate, attract, and retain the world’s best and brightest. Given China’s role as a producer of AI talent, understanding its AI workforce could provide important insight. This report provides an analysis of the AI workforce demand in China using a novel dataset of 6.8 million job postings. It then outlines potential implications along with future reports in this series.

CSET's Catherine Aiken testified before the National Artificial Intelligence Advisory Committee on measuring progress in U.S. AI research and development.

Universities are the engines that power the AI talent pipeline, but mounting evidence suggests that U.S. computer science departments do not have enough faculty to meet growing student interest. This paper explores the potential mismatch between supply and demand in AI education, discusses possible causes and consequences, and offers recommendations for increasing teaching capacity at U.S. universities.

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.

Community and technical colleges offer enormous potential to grow, sustain, and diversify the U.S. artificial intelligence (AI) talent pipeline. However, these institutions are not being leveraged effectively. This report evaluates current AI-related programs and the associated number of graduates. The authors find that few AI and AI-related degrees and certificates are being awarded today. They propose five recommendations to address existing challenges and harness the potential of these institutions to train tomorrow’s AI workforce.

This issue brief uses data from the National Science Foundation’s Survey of Doctorate Recipients to explore how many of the international students who earn STEM PhDs from U.S. universities stay in the country after graduation. The authors trace the journeys that these graduates take through the immigration system and find that most remain in the United States long after earning their degrees.

The strength of a country’s talent pipeline depends in no small part on the quality of its universities. This data brief explores how Chinese and U.S. universities perform in two different global university rankings, why their standings have changed over time, and what those trends mean for graduates.

In the past decade, Chinese researchers have become increasingly prolific authors of highly cited AI publications, approaching the global research share of their U.S. counterparts. However, some analysts question the impact of Chinese publications; are they well respected internationally, and do they cover important topics? In this data brief, the authors build on prior analyses of top AI publications to provide a richer understanding of the two countries’ contributions to high-impact AI research.