Case study reveals cultural representation failure modes in South Asian communities, highlighting how generative text-to-image models reproduce systemic marginalization.
This case study presents a community-centered evaluation of South Asian cultural representations in text-to-image (T2I) models. We identify several failure modes and locate them within participantsâ reporting of their existing experiences of social marginalization. We thus show how generative artificial intelligence (AI) can reproduce an outsidersâ 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 nuance to existing evaluative frameworks, and deepens our understanding of the culturally specific ways in which generative 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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Qadri et al. (2024) studied this question.
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