Abstract

DAY, Suzanne  and  RENNIE, Stuart. Data science research in sub-Saharan Africa: Ethical considerations in crowdsourcing for community engagement. S. Afr. j. sci. [online]. 2023, vol.119, n.5-6, pp.1-4. ISSN 1996-7489.  http://dx.doi.org/10.17159/sajs.2023/14911.

SIGNIFICANCE: There is an increasing movement to 'digitise' health-related data on the African continent, and to improve local health and health systems using cutting-edge data analytics. While these big data initiatives may be beneficial, and engagement is needed to help maintain public trust in data science, the introduction of new digital technologies raises ethical concerns and challenges for engagement. In this Commentary, we focus on the ethics of using crowdsourcing as an approach to increasing community engagement in data science. We map out key areas of ethical concern related to data science and argue that crowdsourcing serves as a promising strategy for identifying ways in which communities can become more engaged in data science initiatives.

Keywords : data science; ethics; crowdsourcing; community engagement; sub-Saharan Africa.

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