Hosted by the Global Partnership for Sustainable Development Data and the United Nations Economic Commission for Africa
Governments across Africa are asking their national statistical offices for data that is more timely, more detailed, and easier to act on. They need it to plan, track the SDGs, respond to climate change and deliver public services. At the same time, NSOs have access to more kinds of data than before, including administrative records, Earth observation, mobile phone data and data produced by citizens.
AI, machine learning and data science can help NSOs make use of those sources. They can automate parts of statistical production, improve data quality and combine sources that used to be handled separately. In recent years, several African NSOs have built data science capacity through a collaboration between UNECA and the Global Partnership with technology partners including NVIDIA, Dell Technologies and Future Tech Enterprises. That work has included advanced training and new computing infrastructure, and it is starting to change how some offices produce statistics.
This session looks at what happens after the pilot. Data science teams from the NSOs of Ghana, Kenya, Rwanda and Senegal will each present one real use case, covering the problem, the data and technology used, the value it delivered, and the biggest obstacle to scaling it. Telecom operators will discuss how their data can support public policy while protecting privacy, and what a lasting partnership with an NSO could look like. The session closes with a discussion, chaired by Prof. Sam Annim, Director of ACS-UNECA, on where NSOs should lead within national AI and digital transformation efforts.