DataFeed

Algorithmic accountability – Applying the concept to different country contexts

Drawing from interviews with global experts, topic workshops and content research, this scoping paper aims to provide the reader with an understanding of algorithmic decision-making processes and the challenges they pose to our existing understanding of accountability across different contexts. It offers a map of existing technical and governance mechanisms for both identifying and addressing algorithmic harms and bias, as well as a set of recommendations and entry points for the Web Foundation and other stakeholders to contribute to this emerging field most effectively.

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Author(s)

Author(s): 
David Sangokoya

Partner Organization(s)

Data Pop Alliance, World Wide Web Foundation

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