CSET is partnering with top universities to expand AGORA, its living collection of 1,000+ AI-related laws, regulations, and standards.

CSET’s Catherine Aiken shared her expert insight in an article published by Nature. The article explores an open-access dataset called Cosmos 1.0, published in Scientific Data, which uses a Wikipedia-based AI model to identify the "Momentum 100," a data-driven list of rapidly emerging technologies such as reinforcement learning, blockchain, and 3D printing.

CSET’s Ronnie Kinoshita shared her expert insight in an article published by NPR. The article explores the rapid expansion of AI data centers across the United States and the growing political backlash as communities push back against their environmental and economic impacts.

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

MIT AI Risk Initiative researchers expanded their pipeline with CSET to map over 1,000 AI governance documents from the AGORA dataset to several extensible taxonomies. These taxonomies cover AI risks, actors, industry sectors, AI lifecycle stages, legislative status, and AI system technical scope, complementing AGORA’s thematic taxonomy of risk factors, harms, governance strategies, incentives for compliance, and application areas.

CSET’s Lauren Kahn shared her expert analysis in an article published by Scientific American. The article discusses the growing dangers of space debris and how increasing orbital traffic threatens satellites, space stations, and human space missions.

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.