While demonstrating technical proficiency, challenges and competitions can reveal China’s People's Liberation Army’s (PLA) key priorities, bottlenecks, and institutional dynamics within its defense innovation system, which would otherwise be difficult to observe. This blog summarizes public PLA announcements of challenges and competitions from January 2023 to December 2024 to understand the signals the PLA may be sending about technical priorities.

Who counts as part of the AI workforce? The answer shapes how researchers measure AI talent, how policymakers diagnose shortages, and how workforce strategies are designed. Yet many existing definitions capture very different kinds of work under the same label. This blog examines the strengths and weaknesses of prevailing approaches and introduces CSET’s new definition of AI development jobs as a narrower, policy-relevant alternative.

CSET researchers share their early analysis of the White House's AI Policy Framework and what the prospects are for near-term legislative action on AI.

Ambitious projects to accelerate AI-driven scientific discovery such as the Genesis Mission aim to unlock large federal datasets and incentivize private-sector participation. This blog examines how federal prize competitions—recognized in the Genesis Mission, the FY26 National Defense Authorization Act (NDAA), and recommendations from the National Security Commission on Emerging Biotechnology—can serve as effective implementation tools. Drawing on recent scientific prize competitions highlight lessons for designing incentives that advance national biotechnology and AI research priorities.

How far has Beijing advanced on the goals set in its 2021 Space Perspective? Drawing from open-source evidence, this analysis tracks progress across seven mission areas. The findings reveal steady, wide-ranging advances toward 2027 objectives, with one major shortfall: persistent challenges in debris mitigation.

The U.S. AI Action Plan is built on three familiar pillars—accelerating innovation, expanding infrastructure, and maintaining technological leadership—but its real test depends on education and training. To that end, the Trump Administration has linked the plan to two executive orders issued in April 2025: Executive Order 14277, “Advancing Artificial Intelligence Education for American Youth,” and Executive Order 14278, “Preparing Americans for High-Paying Skilled Trade Jobs of the Future.” Both orders came with tight deadlines and those windows have now closed. So where do things stand?

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.

This blog examines 18 AI-related laws that California enacted in 2024, 8 of which are explored in more detail in an accompanying CSET Emerging Technology Observatory (ETO) blog. This blog also chronicles California’s history of regulating AI and other emerging technologies and highlights several AI bills that have moved through the California legislature in 2025.

Red-teaming is a popular evaluation methodology for AI systems, but it is still severely lacking in theoretical grounding and technical best practices. This blog introduces the concept of threat modeling for AI red-teaming and explores the ways that software tools can support or hinder red teams. To do effective evaluations, red-team designers should ensure their tools fit with their threat model and their testers.

As AI agents become more autonomous and capable, organizations need new approaches to deploy them safely at scale. This explainer introduces the rapidly growing field of AI control, which offers practical techniques for organizations to get useful outputs from AI agents even when the AI agents attempt to misbehave.