This paper examines the convergence of artificial intelligence and robotics, analyzing the emerging field of Physical AI. It provides a detailed overview of the supply chain challenges, competitive dynamics, and policy considerations that define this potentially transformative emerging technology.

CSET submitted the following response to the White House Office of Science and Technology in support of its "Accelerating the American Scientific Enterprise initiative.

China is embracing “embodied AI”—artificial intelligence integrated with physical agents, such as robots and drones—both for commercial reasons and as a path to artificial general intelligence (AGI). The trend reflects China’s signature approach to AI, which recognizes diverse paths to AI dominance vis-à-vis the large models favored in the United States. This report documents PRC support for AI embodiment, describes how it is understood by China’s research community, and maps out the related infrastructure.

This report examines lessons from the North Carolina Life Sciences Apprenticeship Consortium for pharmaceutical and biomanufacturing workforce development, and analyzes how apprenticeship programs help address workforce shortages in emerging tech fields. It offers a practical framework with important considerations for designing and launching programs, and serves as a resource for employers, regional leaders, and policymakers seeking to build a more resilient and technically skilled workforce.

This roundtable report explores how practitioners, researchers, educators, and government officials view work-based learning as a tool for strengthening the cybersecurity workforce. Participants engaged in an enriching discussion that ultimately provided insight and context into what makes work-based learning unique, effective, and valuable for the cyber workforce.

System-to-model innovation is an emerging innovation pathway in artificial intelligence that has driven progress in several prominent areas over the last decade. System-level innovations advance with the diffusion of AI and expand the base of contributors to leading-edge progress in the field. Countries that can identify and harness system-level innovations faster and more comprehensively will gain crucial economic and military advantages over competitors. This paper analyzes the benefits of system-to-model innovation and suggests a three-part framework to navigate the policy implications: protect, diffuse, and anticipate.

CSET Lead Analyst Dr. William Hannas testified before the House Judiciary Subcommittee on the Courts, Intellectual Property, and the Internet for its hearing, "Intellectual Property and Strategic Competition with China: Part 3 - IP Theft, Cybersecurity, and AI."

Demand for an AI-literate workforce has surged, in large part to counter a growing skills gap. Meanwhile, expertise in ethical and governance dimensions of AI is increasingly deemed crucial to handle various organizational, regulatory, and social concerns. However, the focus of AI literacy efforts to date has been primarily technical. This paper helps close this gap by providing the first large-scale analysis of AI ethics and governance skills sought by employers in the labor market.