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.

In the second installation of our blog series analyzing 147 AI-related laws enacted by Congress between January 2020 and March 2025 from AGORA, we explore the governance strategies, risk-related concepts, and harms addressed in the legislation. In the first blog, we showed that the majority of these AI-related legislative documents were drawn from National Defense Authorization Acts and apply to national security contexts.

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.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This three-part series introduces CSET’s patent clusters, which connect related patents through citations and text similarity.

In this two-part analysis, we use data from the Emerging Technology Observatory's AGORA to explore AI-related legislation that was enacted by Congress between January 2020 and March 2025. This first blog explores the origin and application domains of the AI-related legislation we reviewed. The second blog examines the governance strategies, risk-related concepts, and harms covered by this legislation.

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."

This new report summarizes a March 2025 workshop hosted by CSET and ORCA, with support from NSF. The workshop brought together more than 30 experts to discuss advancing open science and metascience, and brainstorm how artificial intelligence can be a tool in those efforts. Informed by workshop panels and discussions, the report outlines an agenda for near-term, high-priority next steps to benefit researchers, funders, and policymakers.