Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This is the second installment of a two-part series of data snapshots that explores export control data from the Bureau of Industry and Security (BIS), namely the 2021 and 2022 yearly reports for trade with China and Hong Kong.

Antimicrobial resistance (AMR) is one of the world’s most pressing global health threats. Basic research is the first step towards identifying solutions. This brief examines the AMR research landscape since 2000, finding that the amount of research is increasing and that the U.S. is a leading publisher, but also that novel solutions like phages and synthetic antimicrobial production are a small portion of that research.

Read our translation of draft Chinese technical documentation for generative AI that establishes very specific oversight processes that Chinese AI companies must adopt in regard to their model training data, model-generated content, and more.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This is the first installment of a two-part series of data snapshots that explores export control data from the Bureau of Industry and Security (BIS), namely the 2021 and 2022 yearly reports for trade with China and Hong Kong.

This report summarizes recent DOD digital workforce trends as an update to our 2021 report. We expanded our definition of AI talent to include data, analytics, software, and AI, referred to here as the “digital workforce,” to be more aligned with Department needs and current workforce planning efforts. We find that the Department of Defense continues to struggle with their ability to define, identify, develop, assign, promote, and retain digital talent.

AI capabilities are evolving quickly and pose novel—and likely significant—risks. In these rapidly changing conditions, how can policymakers effectively anticipate and manage risks from the most advanced and capable AI systems at the frontier of the field? This Roundtable Report summarizes some of the key themes and conclusions of a July 2023 workshop on this topic jointly hosted by CSET and Google DeepMind.

How can policymakers credibly reveal and assess intentions in the field of artificial intelligence? Policymakers can send credible signals of their intent by making pledges or committing to undertaking certain actions for which they will pay a price—political, reputational, or monetary—if they back down or fail to make good on their initial promise or threat. Talk is cheap, but inadvertent escalation is costly to all sides.

CSET submitted the following comment in response to a Request for Information (RFI) from the White House's Office of Science and Technology Policy about potential changes to the Policies for Federal and Institutional Oversight of Life Sciences Dual Use Research of Concern (DURC) and Recommended Policy Guidance for Departmental Development of Review Mechanisms for Potential Pandemic Pathogen Care and Oversight (P3CO).

Australia, Canada, Japan, the United Kingdom, and the United States emphasize principles of accountability, explainability, fairness, privacy, security, and transparency in their high-level AI policy documents. But while the words are the same, these countries define each of these principles in slightly different ways that could have large impacts on interoperability and the formulation of international norms. This creates, what we call the “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.”

This explainer overviews techniques to produce smaller and more efficient language models that require fewer resources to develop and operate. Importantly, information on how to leverage these techniques, and many of the subsequent small models, are openly available online for anyone to use. The combination of both small (i.e., easy to use) and open (i.e., easy to access) could have significant implications for artificial intelligence development.