Stealth technology was one of the most decisive developments in military aviation in the last 50 years. With U.S. technological leadership now under challenge, especially from China, this issue brief derives several lessons from the history of Stealth to guide current policymakers. The example of Stealth shows how the United States produced one critical technology in the past and how it might produce others today.

Six Chinese universities have relationships with Advanced Persistent Threat (APT) hacking teams. Their activities range from recruitment to running cyber operations. These partnerships, themselves a case study in military-civil fusion, allow state-sponsored hackers to quickly move research from the lab to the field. This report examines these universities’ relationships with known APTs and analyzes the schools’ AI/ML research that may translate to future operational capabilities.

In May 2020, the White House announced it would deny visas to Chinese graduate students and researchers who are affiliated with organizations that implement or support China’s military-civil fusion strategy. The authors discuss several ways this policy might be implemented. Based on Chinese and U.S. policy documents and data sources, they estimate that between three and five thousand Chinese students might be prevented from entering U.S. graduate programs each year.

Foreign investors comprise a significant portion of investors in top U.S. AI startups, with China as the leading location. The authors analyze investment data in the U.S. AI startup ecosystem both domestically and abroad, outlining the sources of global investment.

Corporate investors are a significant player in the U.S. AI startup ecosystem, funding 71 percent of top U.S. AI startups. The authors analyze the trends in top corporate funders and the startups receiving corporate money.

The countries with the greatest capacity to develop, produce and acquire state-of-the-art semiconductor chips hold key advantages in the development of emerging technologies. At present, the United States and its allies possess significant leverage over core segments of the supply chain used to produce these chips. This policy brief outlines actions the United States and its allies can take to secure that advantage in the long term and use it to promote the beneficial use of emerging technologies, such as artificial intelligence.

As the United States seeks to maintain a competitive edge in artificial intelligence, the strength of its AI workforce will be of paramount importance. In order to understand the current state of the domestic AI workforce, Diana Gehlhaus and Santiago Mutis define the AI workforce and offer a preliminary assessment of its size, composition, and key characteristics. Among their findings: The domestic supply of AI talent consisted of an estimated 14 million workers (or about 9% of total U.S. employment) as of 2018.

U.S. research security requires trust and collaboration between those conducting R&D and the federal government. Most R&D takes place in the private sector, outside of government authority and control, and researchers are wary of federal government or law enforcement involvement in their work. Despite these challenges, as adversaries work to extract science, technology, data and know-how from the United States, the U.S. government is pursuing an ambitious research security initiative. In order to secure the 78 percent of U.S. R&D funded outside the government, authors Melissa Flagg and Zachary Arnold propose a new, public-private research security clearinghouse, with leadership from academia, business, philanthropy, and government and a presence in the most active R&D hubs across the United States.

As states turn to AI to gain an edge in cyber competition, it will change the cat-and-mouse game between cyber attackers and defenders. Embracing machine learning systems for cyber defense could drive more aggressive and destabilizing engagements between states. Wyatt Hoffman writes that cyber competition already has the ingredients needed for escalation to real-world violence, even if these ingredients have yet to come together in the right conditions.

Many factors influence where U.S. tech multinational corporations decide to conduct their global artificial intelligence research and development (R&D). Company AI labs are spread all over the world, especially in North America, Europe and Asia. But in contrast to AI labs, most company AI staff remain concentrated in the United States. Roxanne Heston and Remco Zwetsloot explain where these companies conduct AI R&D, why they select particular locations, and how they establish their presence there. The report is accompanied by a new open-source dataset of more than 60 AI R&D labs run by these companies worldwide.