Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This short series explores how government procurement data can shed light on federal technological interest and utilization. It analyzes contract metadata, provided in a collaborative project with Govini, to track key emerging technologies through the federal procurement process.

When the technology and policy communities use terms associated with trustworthy AI, could they be talking past one another? This paper examines the use of trustworthy AI keywords and the potential for an “Inigo Montoya problem” in trustworthy AI, inspired by "The Princess Bride" movie quote: “You keep using that word. I do not think it means what you think it means.”

Read our translation of a white paper by a Chinese state-affiliated think tank that emphasizes the importance of Chinese and foreign AI frameworks.

Creating adequate talent pipelines for the cybersecurity workforce is an ongoing priority for the federal government. Understanding the effectiveness of current education initiatives will help policymakers make informed decisions. This report analyzes the National Centers of Academic Excellence in Cyber (NCAE-C), a consortium of institutions designated as centers of excellence by the National Security Agency. It aims to determine how NCAE-C designated institutions fare compared to other schools in graduating students with cyber-related degrees and credentials.

This is a translation of China’s plan for applying high technology to the field of transportation.

Read our original translation of revised guidelines, issued by the PRC Ministry of Science and Technology in September 2020 on the basis of previous guidelines from August 2019.

Dr. Dewey Murdick testified before the House Science Committee on steps the United States can take to support U.S. AI innovation, prevent authoritarian governments from surpassing us in AI, and improving user safety.

The current AI-for-cybersecurity paradigm focuses on detection using automated tools, but it has largely neglected holistic autonomous cyber defense systems — ones that can act without human tasking. That is poised to change as tools are proliferating for training reinforcement learning-based AI agents to provide broader autonomous cybersecurity capabilities. The resulting agents are still rudimentary and publications are few, but the current barriers are surmountable and effective agents would be a substantial boon to society.

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.