CSET Senior Fellow Andrew Lohn testified before the U.S. Senate Armed Services Subcommittee on Cybersecurity hearing on artificial intelligence applications to operations in cyberspace. Lohn discussed AI's capabilities and vulnerabilities in cyber defenses and offenses.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This is the fifth in a series of Snapshots exploring CSET’s Private-sector AI-Related Activity Tracker (PARAT). Check in every two weeks to see our newest Snapshot, and explore PARAT, which collects data related to companies’ AI research and development to inform analysis of the global AI sector.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This is the fourth in a series of Snapshots exploring CSET’s Private-sector AI-Related Activity Tracker (PARAT). Check in every two weeks to see our newest Snapshot, and explore PARAT, which collects data related to companies’ AI research and development to inform analysis of the global AI sector.

Like traditional software, vulnerabilities in machine learning software can lead to sabotage or information leakages. Also like traditional software, sharing information about vulnerabilities helps defenders protect their systems and helps attackers exploit them. This brief examines some of the key differences between vulnerabilities in traditional and machine learning systems and how those differences can affect the vulnerability disclosure and remediation processes.

CSET Research Analyst Dakota Cary testified before the U.S.-China Economic and Security Review Commission hearing on "China’s Cyber Capabilities: Warfare, Espionage, and Implications for the United States." Cary discussed the cooperative relationship between Chinese universities and China’s military and intelligence services to develop talent with the capabilities to perform state-sponsored cyberespionage operations.

Between 2012 and 2018, the amount of computing power used by record-breaking artificial intelligence models doubled every 3.4 months. Even with money pouring into the AI field, this trendline is unsustainable. Because of cost, hardware availability and engineering difficulties, the next decade of AI can't rely exclusively on applying more and more computing power to drive further progress.

Artificial intelligence offers enormous promise to advance progress and powerful capabilities to disrupt it. This policy brief is the second installment of a series that examines how advances in AI could be exploited to enhance operations that automate disinformation campaigns. Building on the RICHDATA framework, this report describes how AI can supercharge current techniques to increase the speed, scale, and personalization of disinformation campaigns.

Artificial intelligence will play an increasingly important role in cyber defense, but vulnerabilities in AI systems call into question their reliability in the face of evolving offensive campaigns. Because securing AI systems can require trade-offs based on the types of threats, defenders are often caught in a constant balancing act. This report explores the challenges in AI security and their implications for deploying AI-enabled cyber defenses at scale.

Artificial intelligence offers enormous promise to advance progress, and powerful capabilities to disrupt it. This policy brief is the first installment of a series that examines how advances in AI could be exploited to enhance operations that automate disinformation. Introducing the RICHDATA framework—a disinformation kill chain—this report describes the stages and techniques used by human operators to build disinformation campaigns.

In science and technology, U.S. federal prize competitions are a way to promote innovation, advance knowledge, and solicit technological solutions to problems. In this report, the authors identify the unique advantages of such competitions over traditional R&D processes, and how these advantages might benefit artificial intelligence research.