Collectively Reimagining Artificial Intelligence With Marginalized Communities

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Authors: Rachel Feyisayo Oluwatuyi, Vimlan Pillay, Jasmine Mazwi, Alvin Castro, Jaydon Farao, Shreyas Srivatsa, Naveen Bagalkot, Melissa Densmore
Cited by: 1
References: 113

Abstract

As artificial intelligence continues to advance, marginalized communities, particularly in Africa, remain limited in their ability to shape what AI should do, how it should be built, and how it might benefit them. This study adopted a speculative co-design approach with participants from Ocean View, a low-income community in South Africa. The aim was to elicit and facilitate collective visions to reimagine the future of AI and explore ways to make AI technologies more culturally relevant. Our findings reveal participants’ perceptions about AI, which informed a collective vision of AI designs that embed the community’s local language and culture as well as services aimed at improving the community’s economic opportunities. Based on these insights, we identified directions for ethical AI design for marginalized communities that recognise and preserve cultural identity, needs for affordable AI designs, and the potential of AI for their socio-economic advancement as trajectories within AI research.

Fields of Study & Subjects

Ethics and Social Impacts of AI ICT in Developing Communities Innovative Human-Technology Interaction

Publication details

Journal / source
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–21
Publication date
13 April 2026