The task of artificial intelligence policymaking is complex and challenging, made all the more difficult by such a rapidly evolving technology. In order to address the security and economic implications of AI, policymakers must be able to viably define, categorize and assess AI research and technology. In this issue brief, CSET puts forward a functional definition of AI, based on three core principles, that significantly outperforms methods developed over the last decade.

Tracking the output of a country’s researchers can inform assessments of its innovativeness or assist in evaluating the impact of certain funding initiatives. However, measuring research output is not as straightforward as it may seem. Using a detailed analysis that includes Chinese-language research publications, this data brief reveals that China's lead in artificial intelligence research output is greater than many English-language sources suggest.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. Our first series of Snapshots introduced CSET’s Map of Science and explored the underlying data and analytic utility of this new tool, which enables users to interact with the Map directly.

As technology competition intensifies between the United States and China, governments and policy researchers are looking for metrics to assess each country’s relative strengths and weaknesses. One measure of technology innovation increasingly used by the policy community is research output. Drawing on CSET’s experiences over the last four years, this post shares our best practices for using research output to study national technological competition and inform public policy.

This data brief explores how international collaboration relates to the impact and output of research publications. Focusing on the top 10 countries with the highest publication output from 2010 to 2019, the authors provide a comprehensive analysis across the major fields of science and technology.

With its massive information technology workforce, thriving research community and a growing technology ecosystem, India has a significant stake in the development of artificial intelligence globally. Drawing from a variety of original CSET datasets, the authors evaluate India’s potential for AI by examining its progress across five categories of indicators pertinent to AI development: talent, research, patents, companies and investments, and compute.