Artificial intelligence (AI) tools pose exciting possibilities to advance scientific, biomedical, and public health research. At the same time, these tools have raised concerns about their potential to contribute to biological threats, like those from pathogens and toxins. This report describes pathways that result in biological harm, with or without AI, and a range of governance tools and mitigation measures to address them.

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.

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.

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.

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.

This publication examines how emerging AI tools—including LLM-based chatbots and biological design tools—are reshaping the biosecurity landscape for commercial DNA synthesis.

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.

CSET Non-Resident Senior Fellow Kevin Wolf testified before the US-China Economic and Security Review Commission on economic competition with China.

Medical artificial intelligence, which depends on large repositories of biological data, can improve public health and contribute to the growing global bioeconomy. Countries that strategically prioritize medical AI could benefit from a competitive advantage and set global norms. This report examines China’s stated goals for medical AI, finding that the country’s strategy for biodata collection and medical AI development positions it to be an economic and technological leader in this sector.

As the U.S. government considers banning genomics companies from China, it opens a broader question about how the United States and other market economies should deal with China’s “national champions.” This paper provides an overview of one such company—BGI—and how China’s industrial policy impacts technology development in China and around the world.