  This essay seeks to tie together thoughts on the political economy of
academia, the inequities in access to the academic means of production and
decolonial practice in data empowerment. To demonstrate this I will provide a
brief analysis of the neo-colonial, extractive practices of the Western
Academy, introduce concepts around decolonial AI practice and then use these to
form an investigative framework. Using this framework, I present a brief case
study of the AirQo project in Kampala, Uganda. The project aims to deploy a
low-cost air pollution sensor network across the city, using machine learning
methods to calibrate these sensors against reference instruments, providing
high-quality air pollution data at a far lower cost.
