Poor Data Quality in Sub-Saharan Africa and Implications on Ethical AI Development

In Simona Chiodo, David Kaiser, Julie Shah & Paolo Volonté (eds.), Improving Technology Through Ethics. Springer Nature Switzerland. pp. 83-92 (2024)
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Abstract

This chapter explores the issue of poor data qualityData qualityin Sub-Saharan AfricaSub-Saharan Africa and its potential impact on the development of ethical artificial intelligenceArtificial Intelligence (AI) (AI) systems. The region faces significant challenges in terms of data collectionData collection, storage, and accessibility, which can hinder the progress of AI applications. Moreover, the ethical considerations surrounding AI development, such as fairnessFairness, transparencyTransparency, and bias, become more pronounced in the context of inadequate data qualityData quality. This book chapter examines the root causes of poor data quality in Sub-Saharan AfricaSub-Saharan Africa, its implications for AIArtificial Intelligence (AI), and suggests strategies to address these challenges, fostering the responsible and ethical development of AI technologies in the region.

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