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A critical framing of data for development: Historicizing data relations and AI

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
Creators:
CreatorsEmailORCID
Mussgnug, Alexandera.mussgnug@ed.ac.uk0000-0002-5951-057X
Leonelli, Sabinas.leonelli@exeter.ac.uk0000-0002-7815-6609
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
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
Date: 2024
URI: https://philsci-archive.pitt.edu/id/eprint/23731

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