This brief examines trends in patents generated through federally funded research, otherwise known as Bayh-Dole patents. We find that while Bayh-Dole patents make up a small proportion of U.S. patents overall, they are much more common in certain fields, especially in biosciences and national defense related fields. Academic institutions are major recipients of Bayh-Dole patents, and the funding landscape for patent-producing research has shifted since Bayh-Dole came into effect in 1980.

Artificial intelligence that makes news headlines, such as ChatGPT, typically runs in well-maintained data centers with an abundant supply of compute and power. However, these resources are more limited on many systems in the real world, such as drones, satellites, or ground vehicles. As a result, the AI that can run onboard these devices will often be inferior to state of the art models. That can affect their usability and the need for additional safeguards in high-risk contexts. This issue brief contextualizes these challenges and provides policymakers with recommendations on how to engage with these technologies.

This data brief examines South Korea’s progress in its development of artificial intelligence. The authors find that the country excels in semiconductor manufacturing, is a global leader in the production of AI patents, and is an important contributor to AI research. At the same time, the AI investment ecosystem remains nascent and despite having a highly developed AI workforce, the demand for AI talent may soon outpace supply.

Foundation models could eventually introduce several pathways for undermining state security: accidents, inadvertent escalation, unintentional conflict, the proliferation of weapons, and the interference with human diplomacy are just a few on a long list. The Confidence-Building Measures for Artificial Intelligence workshop hosted by the Geopolitics Team at OpenAI and the Berkeley Risk and Security Lab at the University of California brought together a multistakeholder group to think through the tools and strategies to mitigate the potential risks introduced by foundation models to international security.

CSET submitted the following comment in response to a Request for Information (RFI) from the National Science Foundation (NSF) about the development of the newly established Technology, Innovation, and Partnerships (TIP) Directorate, in accordance with the CHIPS and Science Act of 2022.

Jenny Jun's testimony before the House Foreign Affairs Subcommittee on Indo-Pacific for a hearing titled, "Illicit IT: Bankrolling Kim Jong Un."

The current AI-for-cybersecurity paradigm focuses on detection using automated tools, but it has largely neglected holistic autonomous cyber defense systems — ones that can act without human tasking. That is poised to change as tools are proliferating for training reinforcement learning-based AI agents to provide broader autonomous cybersecurity capabilities. The resulting agents are still rudimentary and publications are few, but the current barriers are surmountable and effective agents would be a substantial boon to society.

Israel has by far the largest AI ecosystem in the Middle East as measured in AI companies and financial investments, and foreign investors play a critical role in Israel’s AI market growth. This issue brief finds that AI investments in Israel have mostly originated from the United States. To date, Chinese investors have played a limited role in funding Israel’s dynamic AI companies. But understanding the risk of Chinese investments into the Israeli AI ecosystem will be important for the national security of both the United States and Israel.

Progress in artificial intelligence (AI) depends on talented researchers, well-designed algorithms, quality datasets, and powerful hardware. The relative importance of these factors is often debated, with many recent “notable” models requiring massive expenditures of advanced hardware. But how important is computational power for AI progress in general? This data brief explores the results of a survey of more than 400 AI researchers to evaluate the importance and distribution of computational needs.

Artificial intelligence systems are rapidly being deployed in all sectors of the economy, yet significant research has demonstrated that these systems can be vulnerable to a wide array of attacks. How different are these problems from more common cybersecurity vulnerabilities? What legal ambiguities do they create, and how can organizations ameliorate them? This report, produced in collaboration with the Program on Geopolitics, Technology, and Governance at the Stanford Cyber Policy Center, presents the recommendations of a July 2022 workshop of experts to help answer these questions.