As U.S. policymakers grapple with the need to control international technology flows, this annotated bibliography distills key lessons and surveys 50 years of scholarship, government documents, and commentary. The resources it presents are at the intersection of international economics and technology and span from the Cold War to the current challenges surrounding U.S.-China relations.

Conventional wisdom suggests that cutting-edge artificial intelligence is dependent on large volumes of data. An overemphasis on “big data” ignores the existence—and underestimates the potential—of several AI approaches that do not require massive labeled datasets. This issue brief is a primer on “small data” approaches to AI. It presents exploratory findings on the current and projected progress in scientific research across these approaches, which country leads, and the major sources of funding for this research.

The United States and China are keeping an eye on Indonesia’s artificial intelligence potential given the country’s innovation-driven national strategy and flourishing AI industry. China views Indonesia as an anchor for its economic, digital, and political inroads in Southeast Asia and has invested aggressively in new partnerships. The United States, with robust political and economic relations rooted in shared democratic ideals, has an opportunity to leverage its comparative advantages and tap into Indonesia’s AI potential through high-level agreements.

To what extent does China’s cultivation of talent in cybersecurity and AI matter in terms of competitiveness with other countries? Right now, it seems to have an edge: China’s 11 World-Class Cybersecurity Schools offer more classes on artificial intelligence and machine learning than do the 20 U.S. universities certified as Centers of Academic Excellence in Cyber Operations. This policy brief recommends tracking 13 research grants from the National Science Foundation that attempt to integrate AI into cybersecurity curricula.

As dual-use technologies transform the national security landscape, the U.S. Department of Defense has established a variety of offices and programs dedicated to bringing private sector innovation into the military. However, these efforts have largely failed to drive cutting-edge commercial technology into major military platforms and systems. This report examines the shortcomings of the DOD’s current approach to defense innovation and offers recommendations for a more effective strategy.

For the first time, a Chinese company—Huawei—is set to lead the global transition from one key national security infrastructure technology to the next. How did Washington, at the beginning of the twenty-first century, fail to protect U.S. firms in this strategic technology and allow a geopolitical competitor to take a leadership position in a national security relevant critical infrastructure such as telecommunications? This policy brief highlights the characteristics of 5G development that China leveraged, exploited, and supported to take the lead in this key technology. The Huawei case study is in some ways the canary in the coal mine for emerging technologies and an illustration of what can happen to U.S. competitiveness when China’s companies do not have to base decisions on market forces.

China wants to be a “cyber powerhouse” (网络强国). At the heart of this mission is the sprawling 40 km2 campus of the National Cybersecurity Center. Formally called the National Cybersecurity Talent and Innovation Base (国家网络安全人才与创新基地), the NCC is being built in Wuhan. The campus, which China began constructing in 2017 and is still building, includes seven centers for research, talent cultivation, and entrepreneurship; two government-focused laboratories; and a National Cybersecurity School.

China’s National Cybersecurity Center (NCC) resides on a 40 km2 plot in Wuhan. As one indication of its significance, the Chinese Communist Party’s highest-ranking members have an oversight committee for the facility. Over the next decade, the NCC will provide the talent, innovation, and indigenization of cyber capabilities that China’s Ministry of State Security, Ministry of Public Security, and People’s Liberation Army Strategic Support Force hacking teams lack. Though still under construction, the NCC’s first class of graduates will cross the stage in June 2022.

Modern machine learning often relies on open-source datasets, pretrained models, and machine learning libraries from across the internet, but are those resources safe to use? Previously successful digital supply chain attacks against cyber infrastructure suggest the answer may be no. This report introduces policymakers to these emerging threats and provides recommendations for how to secure the machine learning supply chain.

Cybersecurity operators have increasingly relied on machine learning to address a rising number of threats. But will machine learning give them a decisive advantage or just help them keep pace with attackers? This report explores the history of machine learning in cybersecurity and the potential it has for transforming cyber defense in the near future.