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AI’s Regimes of Representation: A Community-centered Study of Text-to-Image Models in South Asia

Authors:

Cynthia L. Bennett,

Emily DentonAuthors Info & Claims

FAccT '23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency

Pages 506 - 517

https://doi.org/10.1145/3593013.3594016

Published: 12 June 2023 Publication History

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Abstract

This paper presents a community-centered study of cultural limitations of text-to-image (T2I) models in the South Asian context. We theorize these failures using scholarship on dominant media regimes of representations and locate them within participants’ reporting of their existing social marginalizations. We thus show how generative AI can reproduce an outsiders gaze for viewing South Asian cultures, shaped by global and regional power inequities. By centering communities as experts and soliciting their perspectives on T2I limitations, our study adds rich nuance into existing evaluative frameworks and deepens our understanding of the culturally-specific ways AI technologies can fail in non-Western and Global South settings. We distill lessons for responsible development of T2I models, recommending concrete pathways forward that can allow for recognition of structural inequalities.

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FAccT '23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency

June 2023

1929 pages

ISBN:9798400701924

DOI:10.1145/3593013

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FAccT '23: the 2023 ACM Conference on Fairness, Accountability, and Transparency

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