Universities can build more inclusive computer science programs by addressing the reasons that students may be deterred from pursuing the field. This blog post explores some of those reasons, features of CS education that cause them, and provides recommendations on how to design learning experiences that are safer and more exploratory for everyone.

On August 9, 2023 the Biden administration announced an executive order to restrict certain U.S. investments in China’s key technology sectors, including artificial intelligence. This blog post proposes implementing investment restrictions related to AI for national security using a list-based end-user approach that builds upon existing list-based tools.

The much-anticipated National Cyber Workforce and Education Strategy (NCWES) provides a comprehensive set of strategic objectives for training and producing more cyber talent by prioritizing and encouraging the development of more localized cyber ecosystems that serve the needs of a variety of communities rather than trying to prescribe a blanket policy. This is a much-needed and reinvigorated approach that understands the unavoidable inequities in both cyber education and workforce development, but provides strategies for mitigating them. In this blog post, we highlight key elements that could be easily overlooked.

Drawing from prior CSET research, this blog post describes different domestic and international initiatives the Chinese government and companies are pursuing to shore up investment in AI and meet China’s strategic objectives, as well as indicators to track their future trajectories.

How can we measure the reliability of machine learning systems? And do these measures really help us predict real world performance? A recent study by the Stanford Intelligent Systems Laboratory, supported by CSET funding, provides new evidence that models may perform well on certain reliability metrics while still being unreliable in other ways. This blog post summarizes the study’s results, which suggest that policymakers and regulators should not think of “reliability” or “robustness” as a single, easy-to-measure property of an AI system. Instead, AI reliability requirements will need to consider which facets of reliability matter most for any given use case, and how those facets can be evaluated.

Existing U.S. government tools and approaches may help mitigate some of the issues worrying AI observers. This blog post describes long-standing “catch-all” controls, administered by the Department of Commerce’s Bureau of Industry and Security (BIS), and how they might be used to address some of these threats.

In the second of a series of publications, CSET and CNAS outline one avenue the U.S. government could pursue to cut off China’s access to cloud computing services in support of military, security, or intelligence services end use(r)s. The authors discuss pros, cons, and limitations.

In the first of a series of publications, CSET and CNAS outline one potential avenue for the U.S. government to cut off Chinese access to controlled chips via cloud computing, as well its pros, cons, and limitations.