The Defense Production Act can be an effective tool to bring U.S. industrial might to bear on broader national security challenges, including those in technology. If updated and used to its full effect, the DPA could be leveraged to encourage development and governance of artificial intelligence. And debate about the DPA’s use for AI purposes can serve to shape and condition expectations about the role the law’s authorities should or could play, as well as to identify essential legislative gaps.

As multinational collaboration on emerging technologies takes center stage, U.S. allies and partners must overcome the technological, bureaucratic, and political barriers to working together. This report assesses the challenges to multinational collaboration and explains how joint projects centered on artificial intelligence applications for military logistics and sustainment offer a viable path forward.

CSET submitted this comment to the Commerce Department’s Bureau of Industry and Security on how to address concerns about the security of semiconductor supply chains in regions where natural disasters, geopolitical events or other factors might cause serious disruptions.

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.

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.

CSET submitted the following comment to the Department of Homeland Security regarding a fixed time period of admission for nonimmigrant students, exchange visitors and representatives of foreign information media.

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.