This report presents an analytic approach to help U.S. policymakers deconstruct artificial intelligence governance proposals by identifying their underlying assumptions, which are the foundational elements that facilitate the success of a proposal. By applying the approach to five U.S.-based AI governance proposals from industry, academia, and civil society, as well as state and federal government, this report demonstrates how identifying assumptions can help policymakers make informed, flexible decisions about AI under uncertainty.

As artificial intelligence systems are deployed and affect more aspects of daily life, effective risk mitigation becomes imperative to prevent harm. This report analyzes AI incidents to improve our understanding of how risks from AI materialize in practice. By identifying six mechanisms of harm, it sheds light on the different pathways to harm, and on the variety of mitigation strategies needed to address them.

This report analyzes over 250 scientific publications that use open language models in ways that require access to model weights and derives a taxonomy of use cases that open weights enable. The authors identified a diverse range of seven open-weight use cases that allow researchers to investigate a wider scope of questions, explore more avenues of experimentation, and implement a larger set of techniques.

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.

Artificial intelligence (AI) is beginning to change cybersecurity. This report takes a comprehensive look across cybersecurity to anticipate whether those changes will help cyber defense or offense. Rather than a single answer, there are many ways that AI will help both cyber attackers and defenders. The report finds that there are also several actions that defenders can take to tilt the odds to their favor.

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.

Artificial intelligence is reshaping military decision-making. This concise overview explores how AI-enabled systems can enhance situational awareness and accelerate critical operational decisions—even in high-pressure, dynamic environments. Yet, it also highlights the essential need for clear operational scopes, robust training, and vigilant risk mitigation to counter the inherent challenges of using AI, such as data biases and automation pitfalls. This report offers a balanced framework to help military leaders integrate AI responsibly and effectively.