Lacuna Fund
Lacuna Fund Transitions to Partners in Africa and Latin America
A lacuna is a gap or missing part. Lacuna Fund, a multi-funder, multi-stakeholder collaboration, was formed in 2020 to fill gaps in data used to train Machine Learning (ML) models and make ML and AI more representative, accurate, equitable, and accessible to underserved communities globally. Lacuna Fund has enabled the creation of over 75 new ML datasets in agriculture, climate, health, and low-resource languages! 44 of these datasets are now available via the Datasets page of this website. Many of these are being used in low-and middle-income countries to solve urgent problems in their communities.
We are delighted to announce that in July 2025, we are transferring the leadership and management of Lacuna Fund to partner institutions in Africa and Latin America, including ACTS-African Centre for Technology Studies, CENIA, Chile’s National Centre for Artificial Intelligence, Masakhane, and University of Pretoria Data Science for Social Impact Research Group and African Institute for Data Science and AI.
Please note that this site is no longer being updated. The content reflects the state of Lacuna Fund’s work in July 2025. This site will be available until a new online presence and data repository are established so that the community can continue to access the datasets and resources created through this initiative. Please check these sites for updates in the future: University of Pretoria Data Science for Social Impact Research Group and African Institute for Data Science and AI.
Many thanks to the foundations and donors that made this fund possible!
Lacuna Fund began as a funder collaborative between The Rockefeller Foundation, Google.org, and Canada’s International Development Research Centre, but it has since evolved into a multi-stakeholder engagement supported by a range of development, philanthropic, and research institutions.
Our Voice in Data
Machine learning has shown great potential to address critical needs, but in low- and middle-income contexts globally, a lack of unbiased, labeled data puts the benefits out of reach. Lacuna Fund is the world’s first collaborative effort to directly address this problem.
Guided by machine learning professionals worldwide, Lacuna Fund provided data scientists, researchers, and social entrepreneurs with the resources they need to either produce new labeled datasets to address an underserved population or problem, augment existing datasets to be more representative, or update old datasets to be more sustainable.
Image: USGS/Landsat