In science and technology, U.S. federal prize competitions are a way to promote innovation, advance knowledge, and solicit technological solutions to problems. In this report, the authors identify the unique advantages of such competitions over traditional R&D processes, and how these advantages might benefit artificial intelligence research.

Created through a joint partnership between CSET and the AI Education Project, the AI Education Catalog aims to raise awareness of the AI-related programs available to students and educators, as well as to help inform AI education and workforce policy.

CSET submitted this comment to the Office of Science and Technology Policy and the National Science Foundation to support the work of the National Artificial Intelligence Research Resource (NAIRR) Task Force to develop an implementation roadmap that would provide AI researchers and students across scientific disciplines access to computational resources, high-quality data, educational tools, and user support.

Software vulnerability discovery, patching, and exploitation—collectively known as the vulnerability lifecycle—is time consuming and labor intensive. Automating the process could significantly improve software security and offensive hacking. The Defense Advanced Research Projects Agency’s Cyber Grand Challenge supported teams of researchers from 2014 to 2016 that worked to create these tools. China took notice. In 2017, China hosted its first Robot Hacking Game, seeking to automate the software vulnerability lifecycle. Since then, China has hosted seven such competitions and the People’s Liberation Army has increased its role in hosting the games.

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.

CSET research staff discussed the potential for OpenAI's GPT-3 and other content generation systems to be used as tools for turbocharging disinformation.

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.

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.