This brief provides a framework for a systems-oriented approach to technology and national security strategy. It identifies and discusses the tensions among three strategic goals of technology and national security policy—driving technological innovation, impeding adversaries’ progress, and promoting safe, values-driven technology deployment—and highlights various levers of power that policymakers can use to pursue those goals. This adaptable framework, suitable for any country or international body, emphasizes the importance of creative problem-solving and maintaining a comprehensive understanding of the policy landscape.

Process frameworks provide a blueprint for organizations implementing responsible artificial intelligence (AI), but the sheer number of frameworks, along with their loosely specified audiences, can make it difficult for organizations to select ones that meet their needs. This report presents a matrix that organizes approximately 40 public process frameworks according to their areas of focus and the teams that can use them. Ultimately, the matrix helps organizations select the right resources for implementing responsible AI.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This five-part series uses data from the U.S. Department of Education and other select sources to complement existing CSET work on the U.S. AI workforce.

Vaccines keep the U.S. public healthy while safeguarding economic stability and biosecurity. This report assesses the domestic vaccine manufacturing landscape and identifies two major vulnerabilities: a reliance on foreign manufacturers and a lack of manufacturing redundancy. Maintaining a resilient vaccine supply will require the U.S. government to take steps to protect the existing supply, identify and monitor manufacturing vulnerabilities, and create a stronger domestic production base.

ETO’s Research Almanac provides high-level data on key trends in emerging technology research, including overall research output, growth, and trends among countries, research institutions, and companies active in R&D. This initial version of the Almanac focuses on topics and applications in artificial intelligence.

In late 2020, China established the Beijing Institute for General Artificial Intelligence, a state-backed institution dedicated to building software that emulates or surpasses human cognition in many or all of its aspects. Open source materials now available provide insight into BIGAI’s goals, scope, organization, methodology, and staffing. The project formalizes a trend evident in Chinese AI development toward broadly capable (general) AI.

Israel has by far the largest AI ecosystem in the Middle East as measured in AI companies and financial investments, and foreign investors play a critical role in Israel’s AI market growth. This issue brief finds that AI investments in Israel have mostly originated from the United States. To date, Chinese investors have played a limited role in funding Israel’s dynamic AI companies. But understanding the risk of Chinese investments into the Israeli AI ecosystem will be important for the national security of both the United States and Israel.

Read our original translation of a significant Party and government reorganization plan that China’s parliament, the National People’s Congress, passed in March 2023.

U.S. tech companies have played a critical role in the international effort to support and defend Ukraine against Russia. To better understand and envision how these companies can help U.S. strategic interests, CSET convened a group of industry experts and former government leaders to discuss lessons learned from the ongoing war in Ukraine and what those lessons might mean for the future. The workshop’s discussion and this accompanying report expand on the themes explored in the October 2022 "Foreign Affairs" article, "Big Tech Goes to War."

Progress in artificial intelligence (AI) depends on talented researchers, well-designed algorithms, quality datasets, and powerful hardware. The relative importance of these factors is often debated, with many recent “notable” models requiring massive expenditures of advanced hardware. But how important is computational power for AI progress in general? This data brief explores the results of a survey of more than 400 AI researchers to evaluate the importance and distribution of computational needs.