To help U.S. policymakers address long-held concerns about risks and threats associated with letting Chinese university students or graduates study in the United States, CSET experts examine which forms of collaboration, and with which Chinese universities, pose the greatest risk to U.S. research security.

Based on an in-depth analysis of artificial intelligence and machine learning systems, the authors consider the future of applying such systems to cyber attacks, and what strategies attackers are likely or less likely to use. As nuanced, complex, and overhyped as machine learning is, they argue, it remains too important to ignore.

As demand for cybersecurity experts in the United States has grown faster than the supply of qualified workers, some organizations have turned to artificial intelligence to bolster their overwhelmed cyber teams. Organizations may opt for distinct teams that specialize exclusively in AI or cybersecurity, but there is a benefit to having employees with overlapping experience in both domains. This data brief analyzes hiring demand for individuals with a combination of AI and cybersecurity skills.

Machine learning may provide cyber attackers with the means to execute more effective and more destructive attacks against industrial control systems. As new ML tools are developed, CSET discusses the ways in which attackers may deploy these tools and the most effective avenues for industrial system defenders to respond.

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.

Since 2016, China has engaged in a nationwide effort to "merge" AI and neuroscience research as a major part of its next-generation AI development program. This report explores China’s AI-brain program — identifying key players and organizations and recommending the creation of an open source S&T monitoring capability within the U.S. government.

How should the United States understand and respond to China’s technologically driven mass surveillance, internment and indoctrination in Xinjiang? Dahlia Peterson offers a set of policy recommendations in a coauthored report for the Brookings Institution.

Patent data can provide insights into the most active countries, fields and organizations in artificial intelligence research. This data brief analyzes worldwide trends in AI patenting to offer metrics on inventive activity.

The current global pandemic has given China a chance to amplify its efforts to apply artificial intelligence across the public and private spheres. Chinese companies are developing and retooling AI systems for control and prevention. This data brief assesses the types of AI technologies used to fight COVID-19 and the key players involved in this industry.