Publications

CSET produces evidence-driven analysis in a variety of forms, from informative graphics and translations to expert testimony and published reports. Our key areas of inquiry are the foundations of artificial intelligence — such as talent, data and computational power — as well as how AI can be used in cybersecurity and other national security settings. We also do research on the policy tools that can be used to shape AI’s development and use, and on biotechnology.

Analysis

CSET’s 2024 Annual Report

Center for Security and Emerging Technology
| March 2025

In 2024, CSET continued to deliver impactful, data-driven analysis at the intersection of emerging technology and security policy. Explore our annual report to discover key research highlights, expert testimony, and new analytical tools — all aimed at shaping informed, strategic decisions around AI and emerging tech.

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Analysis

AI System-to-Model Innovation

Jonah Schiestle and Andrew Imbrie
| July 2025

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.

Analysis

Wuhan’s AI Development

William Hannas, Huey-Meei Chang, and Daniel Chou
| May 2025

Wuhan, China’s inland metropolis, is paving the way for a nationwide rollout of “embodied” artificial intelligence meant to fast-track scientific discovery, optimize production, streamline commerce, and facilitate state supervision of social activities. Grounded in real-world data, the AI grows smarter, offering a pathway to artificial “general” intelligence that will reinforce state ideology and boost economic goals. This report documents the genesis of Wuhan’s AGI initiative and its multifaceted deployment.

Analysis

Promoting AI Innovation Through Competition

Jack Corrigan
| May 2025

Maintaining long-term U.S. leadership in artificial intelligence will require policymakers to foster a diversified, contestable, and competitive market for AI systems. Today, however, incumbent technology companies maintain a distinct advantage in the production of large AI models, and they have the means and motion to use their control over key chokepoints in the AI supply chain (compute, data, foundation models, distribution channels) to stifle competition. This report explores the associated economic and national security risks, and offers recommendations for maintaining an open and competitive AI industry.

Formal Response

CSET’s Recommendations for an AI Action Plan

March 14, 2025

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.

Analysis

Chinese Critiques of Large Language Models

William Hannas, Huey-Meei Chang, Maximilian Riesenhuber, and Daniel Chou
| January 2025

Large generative models are widely viewed as the most promising path to general (human-level) artificial intelligence and attract investment in the billions of dollars. The present enthusiasm notwithstanding, a chorus of ranking Chinese scientists regard this singular approach to AGI as ill-advised. This report documents these critiques in China’s research, public statements, and government planning, while pointing to additional, pragmatic reasons for China’s pursuit of a diversified research portfolio.

Analysis

Acquiring AI Companies: Tracking U.S. AI Mergers and Acquisitions

Jack Corrigan, Ngor Luong, and Christian Schoeberl
| November 2024

Maintaining U.S. technological leadership in the years ahead will require policymakers to promote competition in the AI market and prevent industry leaders from wielding their power in harmful ways. This brief examines trends in U.S. mergers and acquisitions of artificial intelligence companies. The authors found that AI-related M&A deals have grown significantly over the last decade, with large U.S. tech companies being the most prolific acquirers of AI firms.

Analysis

Fueling China’s Innovation: The Chinese Academy of Sciences and Its Role in the PRC’s S&T Ecosystem

Cole McFaul, Hanna Dohmen, Sam Bresnick, and Emily S. Weinstein
| October 2024

The Chinese Academy of Sciences is among the most important S&T organizations in the world and plays a key role in advancing Beijing’s S&T objectives. This report provides an in-depth look into the organization and its various functions within China’s S&T ecosystem, including advancing S&T research, fostering the commercialization of critical and emerging technologies, and contributing to S&T policymaking.

Analysis

Governing AI with Existing Authorities

Jack Corrigan, Owen Daniels, Lauren Kahn, and Danny Hague
| July 2024

A core question in policy debates around artificial intelligence is whether federal agencies can use their existing authorities to govern AI or if the government needs new legal powers to manage the technology. The authors argue that relying on existing authorities is the most effective approach to promoting the safe development and deployment of AI systems, at least in the near term. This report outlines a process for identifying existing legal authorities that could apply to AI and highlights areas where additional legislative or regulatory action may be needed.

Analysis

Enabling Principles for AI Governance

Owen Daniels and Dewey Murdick
| July 2024

How to govern artificial intelligence is a concern that is rightfully top of mind for lawmakers and policymakers.To govern AI effectively, regulators must 1) know the terrain of AI risk and harm by tracking incidents and collecting data; 2) develop their own AI literacy and build better public understanding of the benefits and risks; and 3) preserve adaptability and agility by developing policies that can be updated as AI evolves.

Data Snapshot

Pushing the Limits: Huawei’s AI Chip Tests U.S. Export Controls

Jacob Feldgoise and Hanna Dohmen
| June 17, 2024

Since 2019, the U.S. government has imposed restrictive export controls on Huawei—one of China’s leading tech giants—seeking, in part, to hinder the company’s AI chip development efforts. This data snapshot reveals how exactly Huawei’s latest AI chip—the Ascend 910B—improves on the prior generation and demonstrates how export controls are likely hindering Huawei’s production.