Centring the Margins: Mapping AI Systems as Systems of Power

This paper introduces a method of critically mapping AI as an assemblage of social relations. This approach is rooted in the principles of centring the margins and highlighting power structures. Viewing an AI or algorithmic system as a wide-reaching network of social relations, including their impacts on different groups and contexts, enables consideration of how AI is embedded within different discourses and domains of power while emphasising the impact on those most affected. The paper provides a discussion of the critical framing of the project, the principles, processes and templates for mapping AI in this way, and three examples of algorithmic systems in public sector contexts that have been discontinued, are in use now or are being proposed for future use. A discussion of uses and limitations is provided, situating the method beyond a descriptive or analytical tool towards a critical approach to identifying locations for intervention in harmful or unjust uses of algorithmic systems.

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Publication Details

Journal
Proceedings of the AAAI/ACM Conference on AI Ethics and Society
Published
2025-10-15
DOI
https://doi.org/10.1609/aies.v8i1.36557
Primary Topic
Economic and Technological Innovation
Type
article
Field-Weighted Citation Impact
0.00
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article

Centring the Margins: Mapping AI Systems as Systems of Power

Garfield Benjamin
Proceedings of the AAAI/ACM Conference on AI Ethics and Society
Economic and Technological Innovation
article

Centring the Margins: Mapping AI Systems as Systems of Power

Garfield Benjamin
article en

Abstract

This paper introduces a method of critically mapping AI as an assemblage of social relations. This approach is rooted in the principles of centring the margins and highlighting power structures. Viewing an AI or algorithmic system as a wide-reaching network of social relations, including their impacts on different groups and contexts, enables consideration of how AI is embedded within different discourses and domains of power while emphasising the impact on those most affected. The paper provides a discussion of the critical framing of the project, the principles, processes and templates for mapping AI in this way, and three examples of algorithmic systems in public sector contexts that have been discontinued, are in use now or are being proposed for future use. A discussion of uses and limitations is provided, situating the method beyond a descriptive or analytical tool towards a critical approach to identifying locations for intervention in harmful or unjust uses of algorithmic systems.

Proceedings of the AAAI/ACM Conference on AI Ethics and SocietyVol. 8(1)
University of Cambridge (GB)
Openalex Percentile: Top 62%
Economic and Technological Innovation
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