Ernest Mwebaze (UN Global Pulse): ML4D: what works and how it works - case studies from the developing world

Present advances in Artificial Intelligence and Machine Learning offer unique opportunities for solving impactful developing world problems. At the AI and Data Science research lab at Makerere University and UN PulseLab Kampala in Uganda, we have 8 years of trying to marry good computational techniques with good developing world problems. In this talk I will give some examples of some of the projects we are working on or have worked on. These will include automating disease diagnosis in crops and humans, crowd-sourcing surveillance, traffic monitoring and using public radio data to infer humanitarian crises. I will talk about the relative strengths of the different types of data that can be reliably collected in the developing world and some deployment options that (seem to) work.