Recent announcements from both Pentagon and Congressional leaders offer significant opportunity for rapidly delivering autonomous systems technology at-scale for U.S. Warfighters well into the future. Dr. Jaret Riddick, CSET Senior Fellow and former Principal Director for Autonomy in USD(R&E) offers his perspective on DOD’s Replicator Initiative and recent legislative proposals about DOD autonomy.

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.

Large language models (LLMs) could potentially be used by malicious actors to generate disinformation at scale. But how likely is this risk, and what types of economic incentives do propagandists actually face to turn to LLMs? New analysis uploaded to arXiv and summarized here suggests that it is all but certain that a well-run human-machine team that utilized existing LLMs (even open-source ones that are not cutting edge) would save a propagandist money on content generation relative to a human-only operation.

On July 21, the White House announced voluntary commitments from seven AI firms to ensure safe, secure, and transparent AI. CSET’s research provides important context to this discussion.

Recent discussions of AI have focused on safety, reliability, and other risks. Lost in this debate is the real need to secure AI against malicious actors. This blog post applies lessons from traditional cybersecurity to emerging AI-model risks.

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.