How do people living in rural villages in Togo feel about the use of emerging technologies in humanitarian aid? This work reports on the privacy concerns of people living in rural Togo related to the use of machine learning models trained on phone data to allocate cash assistance to people living in poverty, highlighting an innovative method -- sociotechnical visuals -- to explain complex technical concepts so that people living in rural villages with limited literacy, formal education, and familiarity with digital tech could provide meaningful input.

The digital world suffers from a profound linguistic disparity, particularly in Africa where a lack of local language content and traditional, Global North-led language technology models fail to meet community needs, often resulting in data extraction and inequitable solutions. In an 18-month research project, in collaboration with the Distributed AI Research Institute (DAIR), we highlight a powerful alternative: a growing grassroots movement of community-based language technology initiatives across Africa that adopt a bottoms-up approach, prioritizing local needs and incorporating indigenous philosophies.