Foundational Research Grants (FRG) supports the exploration of foundational technical topics that relate to the potential national security implications of AI over the long term. In contrast to most CSET research, which is performed in-house by our team of fellows and analysts, FRG funds external projects by technical teams. The program aims to advance our understanding of underlying technical issues to shed light on questions of interest from a strategic or policy perspective.

Current areas of interest include:

• AI assurance for general-purpose systems in open-ended domains: Machine learning systems are rapidly becoming larger, more complex, more capable, and more general-purpose. Existing assurance approaches for systems with automated or autonomous capabilities do not appear to be well suited to the kinds of large-scale deep learning systems that are currently being developed and deployed. FRG is interested in whether—and how rapidly—assurance approaches are likely to be developed that are suitable for such systems both now and for the long term.
• Hardware-based mechanisms for governing AI: Access to computing power is an important factor in which entities can train and run cutting-edge AI systems. Some have speculated that this could make AI chips a promising lever in governing the development and deployment of AI. FRG is interested in exploring the technical feasibility of specific proposals along these lines.
• AI security and nonproliferation: As AI systems become more capable, it will be important that their developers are able to prevent unauthorized actors from accessing or using them. FRG is interested in supporting work that could make this more feasible.

FRG grantees include:

• Anthony Corso and Mykel Kochenderfer at Stanford University, for work on the progress and outlook for the reliability of AI systems; and
• The Python Software Foundation, for work to improve security incident reporting infrastructure for the Python Package Index.
• OpenMined, for work supporting the Christchurch Call Initiative on Algorithmic Outcomes.

Open calls for research ideas:

• AI assurance for general-purpose systems in open-ended domains: full details [PDF]
  • Expressions of interest for this call are now closed.

FRG is directed by Helen Toner, with support from Andrea Guerrero, Matthew Burtell, and Thomas Woodside.