The Pentagon has a wide range of research and development programs using autonomy and AI in unmanned vehicles and systems, information processing, decision support, targeting functions, and other areas. This policy brief delves into the details of DOD’s science and technology program to assess trends in funding, key areas of focus, and gaps in investment that could stymie the development and fielding of AI systems in operational settings.

Today’s research and development investments will set the course for artificial intelligence in national security in the coming years. This Executive Summary presents key findings and recommendations from CSET’s two-part analysis of U.S. military investments in autonomy and AI, including our assessment of DOD’s research priorities, trends and gaps, as well as ways to ensure U.S. military leadership in AI in the short and the long term.

In recent years, concern has grown about the risks of Chinese nationals studying science, technology, engineering and mathematics (STEM) subjects at U.S. universities. This data brief estimates the number of Chinese students in the United States in detail, according to their fields of study and degree level. Among its findings: Chinese nationals comprise 16 percent of all graduate STEM students and 2 percent of undergraduate STEM students, lower proportions than were previously suggested in U.S. government reports.

Over the last decade, Moscow has boosted funding of universities and implemented reforms in order to make Russia a global leader in AI. As part of that effort, Russian researchers have expanded their English-language publication output, a key—if imperfect—measure of the country’s innovation and impact. Between 2010 and 2018, the number of English-language publications by Russian scientists in AI-related fields increased six-fold.

The resizing of images, which is typically a required part of preprocessing for computer vision systems, is vulnerable to attack. Images can be created such that the image is completely different at machine-vision scales than at other scales and the default settings for some common computer vision and machine learning systems are vulnerable.

China’s surge in artificial intelligence development has been fueled, in large part, by advances in computer vision, the AI subdomain that makes powerful facial recognition technologies possible. This data brief compares U.S. and Chinese computer vision patent data to illustrate the different approaches each country takes to AI development.

Understanding AI activity in the private sector is crucial both to grasping its economic and security implications and developing appropriate policy frameworks. This data brief shows particularly robust AI activity in software publishing and manufacturing, along with a high concentration of companies in California, Massachusetts and New York.

See our original translation of a speech that Xi delivered to a meeting of academics in 2020 that he convened to solicit input for China’s upcoming 14th Five-Year Plan.

This translation is the result of collaboration between CSET and the DigiChina Project, based at the Stanford University Cyber Policy Center and a joint effort with New America.

The global AI industry is booming, with privately held firms pulling in nearly $40 billion in disclosed investment in 2019 alone. U.S. companies continue to attract the majority of that funding—64 percent of it in 2019—but that lead is not guaranteed. This report analyzes AI investment data from 2015 to 2019 to help better understand trends in the global AI landscape.