Governing artificial intelligence means governing data: (re)setting the agenda for data justice

Research output: Contribution to journalArticleScientificpeer-review

Abstract

The field of data justice has been evolving to take into account the role of data in powering the field of artificial intelligence (AI). In this paper we review the main conceptual bases for governing data and AI: the market-based approach, the personal–non-personal data distinction and strategic sovereignty. We then analyse how these are being operationalised into practical models for governance, including public data trusts, data cooperatives, personal data sovereignty, data collaboratives, data commons approaches and indigenous data sovereignty. We interrogate these models' potential for just governance based on four benchmarks which we propose as a reformulation of the Data Justice governance agenda identified by Taylor in her 2017 framework. Re-situating data justice at the intersection of data and AI, these benchmarks focus on preserving and strengthening public infrastructures and public goods; inclusiveness; contestability and accountability; and global responsibility. We demonstrate how they can be used to test whether a governance approach will succeed in redistributing power, engaging with public concerns and creating a plural politics of AI.
Original languageEnglish
Pages (from-to)onlinefirst
JournalDialogues on Digital Society
Publication statusPublished - 23 Jan 2025

Keywords

  • data governance
  • AI
  • sovereignty
  • data commons
  • data trusts
  • data justice

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