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.

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.

Helen Toner testified before the House Judiciary Subcommittee on Courts, Intellectual Property, Artificial Intelligence, and the Internet on recommendations to bolster security and transparency around U.S.-developed frontier AI.

We investigate the scale of attack and defense mathematically in the context of AI's possible effect on cybersecurity. For a given target today, highly scaled cyber attacks such as from worms or botnets typically all fail or all succeed.

In response to the Office of Science and Technology Policy's request for input on an AI Action Plan, CSET provides key recommendations for advancing AI research, ensuring U.S. competitiveness, and maximizing benefits while mitigating risks. Our response highlights policies to strengthen the AI workforce, secure technology from illicit transfers, and foster an open and competitive AI ecosystem.

This paper presents two new methods for identifying research relevant to emerging technology. The authors developed and deployed technology topic classification and targeted research field scoring over a corpus of scientific literature to identify research relevant to cybersecurity, LLM development, and chips fabrication and design—expanding CSET’s existing set of topic classifications for AI, computer vision, NLP, robotics, and AI safety. The paper summarizes motivation, methods, and results.

Dr. Steph Batalis and Vikram Venkatram offered the following comment in response to the National Institute of Standards and Technology's request for information on safety considerations for chemical and biological AI models.