CSET Research Fellow Saif M. Khan testified before the Senate Foreign Relations Committee for its hearing, "Advancing Effective U.S. Policy for Strategic Competition with China in the Twenty-First Century." Khan spoke to the importance of U.S. leadership in semiconductor and artificial intelligence technology.

As the U.S. military integrates artificial intelligence into its systems and missions, there are outstanding questions about the role of trust in human-machine teams. This report examines the drivers and effects of such trust, assesses the risks from too much or too little trust in intelligent technologies, reviews efforts to build trustworthy AI systems, and offers future directions for research on trust relevant to the U.S. military.

It’s widely understood that Beijing invests significant resources in shoring up its science and technology prowess, but the extent and flows of the Chinese government’s public investments in S&T are not as well known. This project tracks publicly available information about the budgets of more than two-dozen high-level Chinese government entities, including those that support science, technology, and talent recruitment.

China operates a number of party- and state-sponsored talent programs to recruit researchers -- Chinese citizens and non-citizens alike -- to bolster its strategic civilian and military goals. CSET has created a tracker to catalog publicly available information about these programs. This catalog is a work in progress; if you have further information on programs currently not included in it -- or if you spot an error -- please complete the form at http://bit.ly/ChineseTalent

Is there a rift between the U.S. tech sector and the Department of Defense? To better understand this relationship, CSET surveyed U.S. AI industry professionals about their views toward working on DOD-funded AI projects. The authors find that these professionals hold a broad range of opinions about working with DOD. Among the key findings: Most AI professionals are positive or neutral about working on DOD-funded AI projects, and willingness to work with DOD increases for projects with humanitarian applications.

See our original translation of a document that lays out the PRC government’s priorities for developing China’s civilian space infrastructure through 2025. It recommends that China reduce its reliance on foreign civilian satellite technology, but also advocates for continued use of international exchanges and technology transfer as ways to catch up to more technologically advanced countries in space infrastructure.

See our original translation of a speech that Xi delivered to a meeting of academics in 2020 that he convened to solicit input for China’s upcoming 14th Five-Year Plan.

National security leaders view AI as a priority technology for defending the United States. This two-part analysis is intended to help policymakers better understand the scope and implications of U.S. military investment in autonomy and AI. It focuses on the range of autonomous and AI-enabled technologies the Pentagon is developing, the military capabilities these applications promise to deliver, and the impact that such advances could have on key strategic issues.

This brief examines how the Pentagon’s investments in autonomy and AI may affect its military capabilities and strategic interests. It proposes that DOD invest in improving its understanding of trust in human-machine teams and leverage existing AI technologies to enhance military readiness and endurance. In the long term, investments in reliable, trustworthy, and resilient AI systems are critical for ensuring sustained military, technological, and strategic advantages.

The Pentagon has a wide range of research and development programs using autonomy and AI in unmanned vehicles and systems, information processing, decision support, targeting functions, and other areas. This policy brief delves into the details of DOD’s science and technology program to assess trends in funding, key areas of focus, and gaps in investment that could stymie the development and fielding of AI systems in operational settings.