Mawa Keita is a New York–based designer and healthcare IT professional whose work explores the intersection of artificial intelligence, language, and global health. Her practice is grounded in a central question: how can AI systems learn to understand communities that have historically been left out of the data that shapes them?

Her thesis focuses on designing AI for multilingual, low-resource contexts, with an emphasis on Guinea, West Africa. Through projects like VOXcommons, she creates participatory systems for language documentation and voice-based data collection; approaches that center community knowledge as both source and authority.

Her work aims to lay the foundations for more equitable digital health technologies by building systems that listen, adapt, and are shaped by the people they serve.