Problem-solving AI grants (16 awards)

The Future of Life Institute's Problem-solving AI program announced 16 grants of $15K each, totaling $240K. The grants ran across two parallel RFPs.

The first RFP funded research on AI applied to United Nations Sustainable Development Goals, with stated topic areas including poverty, health, energy, and climate. Projects in this track look at how machine-learning tools can be adapted to bottlenecks in fields such as maternal mortality reduction, climate education, labor market analysis, and poverty measurement, with an explicit emphasis on lower- and middle-income country contexts that often sit outside the priority list of commercial AI labs.

The second RFP funded design proposals for global institutions to govern advanced AI. Named grantees in this track include Justin Bullock at the University of Washington proposing a global agency to manage AGI projects; Katharina Zuegel at the Forum on Information and Democracy in France proposing a Fair Trade AI mechanism; and Haydn Belfield at the University of Cambridge proposing an International AI Agency and a CERN for AI to centralize and monitor advanced AI development. The track is a deliberate institutional-design exercise rather than a pure policy-paper line.

The grant size ($15K per project) signals the program's role within FLI's grantmaking: a small-ticket discovery instrument that funds many short-cycle projects to surface promising lines of inquiry, which larger FLI programs (such as the Multistakeholder Engagement line at $100K to $500K per project) can later scale. In the stack the program sits at the governance and evaluation layers.