This roundtable report explores how practitioners, researchers, educators, and government officials view work-based learning as a tool for strengthening the cybersecurity workforce. Participants engaged in an enriching discussion that ultimately provided insight and context into what makes work-based learning unique, effective, and valuable for the cyber workforce.

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.

This new report summarizes a March 2025 workshop hosted by CSET and ORCA, with support from NSF. The workshop brought together more than 30 experts to discuss advancing open science and metascience, and brainstorm how artificial intelligence can be a tool in those efforts. Informed by workshop panels and discussions, the report outlines an agenda for near-term, high-priority next steps to benefit researchers, funders, and policymakers.

Artificial intelligence (AI) is beginning to change cybersecurity. This report takes a comprehensive look across cybersecurity to anticipate whether those changes will help cyber defense or offense. Rather than a single answer, there are many ways that AI will help both cyber attackers and defenders. The report finds that there are also several actions that defenders can take to tilt the odds to their favor.

Demand for an AI-literate workforce has surged, in large part to counter a growing skills gap. Meanwhile, expertise in ethical and governance dimensions of AI is increasingly deemed crucial to handle various organizational, regulatory, and social concerns. However, the focus of AI literacy efforts to date has been primarily technical. This paper helps close this gap by providing the first large-scale analysis of AI ethics and governance skills sought by employers in the labor market.

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.

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.

We investigate the scale of attack and defense mathematically in the context of AI's possible effect on cybersecurity. For a given target today, highly scaled cyber attacks such as from worms or botnets typically all fail or all succeed.

Unlike other domains of conflict, and unlike other fields with high anticipated risk from AI, the cyber domain is intrinsically digital with a tight feedback loop between AI training and cyber application. Cyber may have some of the largest and earliest impacts from AI, so it is important to understand how the cyber domain may change as AI continues to advance. Our approach reviewed the literature, collecting nine arguments that have been proposed for offensive advantage in cyber conflict and nine proposed arguments for defensive advantage.

The Carnegie Classification of Institutions of Higher Education is simplifying its top-tier R1 research criteria this year. Recognizing the strategic importance of historically Black colleges and universities, Congress passed Section 223 of the 2023 National Defense Authorization Act to increase defense research capacity by encouraging the most eligible among these institutions to seek the highly coveted R1 status. This in-depth analysis examines the 2025 classification changes, their effect on eligible HBCUs, and strategies for Congress to maintain progress.