RFP: Labeled datasets for agriculture in Sub-Saharan Africa

[Hannah Kerner]

Machine learning has shown great potential to revolutionize everything from how farmers increase their crop yields, to how governments communicate with their citizens during natural disasters, to how healthcare providers respond to global pandemics. But in low- and middle-income contexts globally, a lack of labeled and unbiased data puts the benefits of machine learning out of reach.

The Lacuna Fund is a new initiative launched today that will provide data scientists, researchers, and social entrepreneurs in low- and middle-income contexts globally with the resources they need to either produce new datasets to address an underserved population or problem, augment existing datasets to be more representative, or update old datasets to be more sustainable.

The first RFP for Agriculture is now open, with proposals to create transformative labeled datasets to fill data gaps in agriculture due September 3, 2020. You can find the text copy of the RFP here, or linked at lacunafund.org/apply. Please consider applying and/or amplifying through your networks!

Thank you,

Hannah Kerner (Technical Advisory Panel)