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Reimagining Data Governance for AI

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CouvRT78

This report introduces a practical, community-centered framework for governing data reuse in the development and deployment of artificial intelligence systems in low- and middle-income countries (LMICs). As AI increasingly relies on data from LMICs, affected communities are often excluded from decision-making and see little benefit from how their data is used. This report, developed by The GovLab at NYU in partnership with Agence Française de Développement, reframes data governance through social licensing—a participatory model that empowers communities to collectively define, document, and enforce conditions for how their data is reused. It offers a step-by-step methodology and actionable tools, including a Social Licensing Questionnaire and adaptable contract clauses, alongisde real-world scenarios and recommendations for enforcement, policy integration, and future research. This report recasts data governance as a collective, continuous process – shifting the focus from individual consent to community decision-making.

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Authors
Peter Addo, Adam Zable, Andrew Zahuranec, Stefan Verhulst
Edition
78
Page number
60
ISSN
2492-2838
Collection
Technical Reports