Exploratory grantmaking is intended to bring community needs and priorities into sharper focus and allow the Foundation to determine whether there is a clear strategy and potential impact in a specific area. Supported activities may include workshops and other expert convenings, early technology development and prototyping, landscape analyses, development of protocols and standards, initial research on and engagement with potential user communities, and demonstration or other proof-of-concept projects. Ideal focus areas lie at the intersection of research and technology, are sufficiently limited that the Foundation could make an impact with its available resources, and involve issues for which public or private funding is scarce or unavailable.  

AI in Science

The complexity and opacity of AI-driven research methods has raised new questions about the degree to which their results can or should be trusted to advance scientific research. Current areas of interest include: reproducibility and transparency of machine learning-enabled science; ways that the philosophy of science and related fields might help to inform the optimal uses of machine learning to produce new knowledge; and the relative value of foundation models vs. good old fashioned machine learning for scientific discovery.

Automation in Science

Advances in robotics can enable the automation of many aspects of scientific lab and field work, especially when coupled with AI to dramatically accelerate iterative cycles of discovery. Though not substantially funding the implementation of these systems at scale, we are currently exploring their optimal uses by researchers as well as the institutional structures to support them.