Mariéme Jamme is a Tech entrepreneur, activist and co-founder of Africa Gathering, a global platform bringing together entrepreneurs and others to share ideas about development in Africa.
In 2012 Southbank Centre launched Africa Utopia, a festival dedicated to bringing art, ideas and discussions on African politics, technology, education and trade from Africa and the African diaspora to audiences in the UK.
Disruptive technologies can be used to achieve social change. One of the main reasons for that is the ability that we have to capture and analyze data. In many occasions though, this “power” can be proved to be a double edged sword. Asmentioned during the discussion: “technology is a knife, you can use that to cook or to kill people“.
What does ‘development’ mean to data scientists, and how does that determine what data science can achieve within the field of international development? This essential question has been raised, in relation to certain D4D (Data for Development) projects, by some experts who further state:
Data science conducted with the aim of informing development policy must, by definition, involve an understanding of the policy area in question, and importantly the analysis must be combined with understanding of the local context. Without these characteristics, research only informs the field of data science rather than development policy.
(Taylor & Schroeder, 2015, pp. 508 & 514)
‘Data science must involve an understanding of the policy area and the local context’. Here is an interesting statement to begin with. So, let’s start with a video from the Geospatial Revolution Project.
The Sustainable Development Goals (SDGs) aim to address inequalities with an objective of “reaching the unreachable”. As mobile technology becomes more affordable, more powerful, and more accessible in low-income regions, it presents even more opportunity for governments to achieve these goals, even more so in public health.