Mussgnug, Alexander and Leonelli, Sabina (2024) A critical framing of data for development: Historicizing data relations and AI. [Preprint]
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Abstract
In times where the use of big data and AI has progressed from an ambitious promise to a formative part of development work, we seek to contextualize and anchor data for development applications and its criticisms to foundational scholarship on the historical trajectory and contemporary implications of datafication and AI. In this contribution, we review Nick Couldry and Ulises A. Mejias’s The Costs of Connection, analyzing the entanglement of capitalism, coloniality, and datafication and connecting these ideas to Matteo Pasquinelli’s labor theory of AI in his work The Eye of The Master. Seeking a two-way exchange between technical and socio-cultural scholarship, we touch upon how an understanding of the longue durée of datafication and development can attune us to the complex entanglements that must be considered when responsibly innovating development applications as well as how these broader framings might benefit from closer consideration of the practical, technical and social challenges of research practices on the ground.
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Item Type: | Preprint | |||||||||
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Additional Information: | Forthcoming in Development and Change | |||||||||
Keywords: | AI, data for development, international development, data colonialism, big data, critical data studies | |||||||||
Subjects: | General Issues > Data General Issues > Ethical Issues General Issues > History of Science Case Studies General Issues > Science and Society General Issues > Science and Policy General Issues > Technology |
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Depositing User: | Mr Alexander Mussgnug | |||||||||
Date Deposited: | 26 Jul 2024 13:35 | |||||||||
Last Modified: | 29 Jul 2024 10:34 | |||||||||
Item ID: | 23731 | |||||||||
Subjects: | General Issues > Data General Issues > Ethical Issues General Issues > History of Science Case Studies General Issues > Science and Society General Issues > Science and Policy General Issues > Technology |
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Date: | 2024 | |||||||||
URI: | https://philsci-archive.pitt.edu/id/eprint/23731 |
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