As artificial intelligence transforms the economy and American society, it will also transform the practice of law and the role of courts in regulating its use. What role should, will, or might judges play in addressing the use of AI? And relatedly, how will AI and machine learning impact judicial practice in federal and state courts? This report is intended to provide a framework for judges to address AI.

A new CSET report by Tim Rudner and Helen Toner introduces specification in machine learning as a key element in greater AI safety.

By combining a versatile and frequently updated bibliometrics tool — the CSET Map of Science — with more hands-on analyses of technical developments, this brief outlines a methodology for measuring the publication growth of AI-related topics, where that growth is occurring, what organizations and individuals are involved, and when technical improvements in performance occur.

This paper is the fourth installment in a series on “AI safety,” an area of machine learning research that aims to identify causes of unintended behavior in machine learning systems and develop tools to ensure these systems work safely and reliably. The first paper in the series, “Key Concepts in AI Safety: An Overview,” outlined three categories of AI safety issues—problems of robustness, assurance, and specification—and the subsequent two papers described problems of robustness and assurance, respectively. This paper introduces specification as a key element in designing modern machine learning systems that operate as intended.

CSET's Husanjot Chahal discusses India's economic role as an emerging AI superpower.

Research Analyst Ryan Fedasiuk reveals China's artificial intelligence intentions in an op-ed for Breaking Defense.

In an opinion piece for Politico Magazine, Ryan Fedasiuk highlights China's adoption of artificial intelligence into its military systems using evidence from his CSET report.

CSET research shows India is building economic value from basic AI research, but a lack of PhD talent places it behind the United States and China in the development of high-end AI research according to Research Analyst Husanjot Chahal.

This brief explores the development and testing of artificial intelligence system classification frameworks intended to distill AI systems into concise, comparable and policy-relevant dimensions. Comparing more than 1,800 system classifications, it points to several factors that increase the utility of a framework for human classification of AI systems and enable AI system management, risk assessment and governance.

CSET's Ryan Fedasiuk joins CSIS' ChinaPower podcast for a discussion on the People's Liberation Army's adoption of AI.