The choice of method for surfacing AI-relevant publications impacts the ultimate research findings. This report provides a quantitative analysis of various methods available to researchers for identifying AI-relevant research within CSET’s merged corpus, and showcases the research implications of each method.

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.”

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.

Progress in artificial intelligence (AI) depends on talented researchers, well-designed algorithms, quality datasets, and powerful hardware. The relative importance of these factors is often debated, with many recent “notable” models requiring massive expenditures of advanced hardware. But how important is computational power for AI progress in general? This data brief explores the results of a survey of more than 400 AI researchers to evaluate the importance and distribution of computational needs.

Biosafety Level-3 laboratories (BSL-3) are an essential part of research infrastructure and are used to develop vaccines and therapies. The research conducted in them provides insights into host-pathogen interactions that may help prevent future pandemics. However, these facilities also potentially pose a risk to society through lab accidents or misuse. Despite their importance, there is no comprehensive list of BSL-3 facilities, or the institutions in which they are housed. By systematically assessing PubMed articles published in English from 2006-2021, this paper maps institutions that host BSL-3 labs by their locations, augmenting current knowledge of where high-containment research is conducted globally.

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.

China’s State Key Laboratory system drives innovation in science and technology. These labs conduct cutting-edge basic and applied research, attract and train domestic and foreign talent, and conduct academic exchanges with foreign counterparts. This report assesses trends in the research priorities, management structures, and talent recruitment efforts of nearly five hundred Chinese State Key Labs. The accompanying data visualization maps their geographical locations and host institutions.

China is banking on applying AI to biotechnology research in order to transform itself into a “biotech superpower.” In pursuit of that goal, it has emphasized bringing together different aspects of the development cycle to foster multidisciplinary research. This data brief examines the emerging trend of co-location of AI and biotechnology researchers and explores the potential impact it will have on this growing field.

This brief illuminates the scale of Chinese government funding for higher education, science, and technology by exploring budget and expense reports for key government organizations and 34 of China’s most elite “Double First Class” universities. Chinese political leaders view elite universities as key components of the country’s military modernization, economic growth, and soft power; a situation that presents security risks for international partners.

Problems of AI safety are the subject of increasing interest for engineers and policymakers alike. This brief uses the CSET Map of Science to investigate how research into three areas of AI safety — robustness, interpretability and reward learning — is progressing. It identifies eight research clusters that contain a significant amount of research relating to these three areas and describes trends and key papers for each of them.