On July 31, 2025, the Trump administration released “Winning the Race: America’s AI Action Plan.” CSET has broken down the Action Plan, focusing on specific government deliverables. Our Provision and Timeline tracker breaks down which agencies are responsible for implementing recommendations and the types of actions they should take.

🔔 The number of AI-related governance documents is rapidly proliferating, but what risks, mitigations, and other concepts do these documents actually cover?

MIT AI Risk Initiative researchers Simon Mylius, Peter Slattery, Yan Zhu, Alexander Saeri, Jess Graham, Michael Noetel, and Neil Thompson teamed up with CSET’s Mina Narayanan and Adrian Thinnyun to pilot an approach to map over 950 AI governance documents to several extensible taxonomies. These taxonomies cover AI risks and actors, industry sectors targeted, and other AI-related concepts, complementing AGORA’s thematic taxonomy of risk factors, harms, governance strategies, incentives for compliance, and application areas.

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.

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.

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.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This three-part series uses data from a variety of sources to track how three cloud providers—Amazon, Alphabet, and Microsoft—distribute their financial resources to create and sustain demand for their cloud services. By investing in data centers & workforce training, the large tech platforms of Amazon, Google, and Microsoft draw developers, companies, and governments to their tools & services.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This three-part series uses data from a variety of sources to track how three cloud providers—Amazon, Alphabet, and Microsoft—distribute their financial resources to create and sustain demand for their cloud services. By investing in data centers & workforce training, the large tech platforms of Amazon, Google, and Microsoft draw developers, companies, and governments to their tools & services.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This three-part series uses data from a variety of sources to track how three cloud providers—Amazon, Alphabet, and Microsoft—distribute their financial resources to create and sustain demand for their cloud services. By investing in data centers & workforce training, the large tech platforms of Amazon, Google, and Microsoft draw developers, companies, and governments to their tools & services.