Collectively Reimagining Artificial Intelligence With Marginalized Communities

Oluwatuyi, Rachel and Pillay, Vimlan and Mazwi, Jasmine and Castro, Alvin and Farao, Jaydon and Srivatsa, Shreyas and Bagalkot, Naveen and Densmore, Melissa (2026) Collectively Reimagining Artificial Intelligence With Marginalized Communities, Proceedings of Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI ’26), April 13–17, 2026, Barcelona, Spain.

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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.

Item Type:	Conference paper
Subjects:	Human-centered computing Human-centered computing > Human computer interaction (HCI) Computing methodologies Computing methodologies > Artificial intelligence Human-centered computing > Human computer interaction (HCI) > Empirical studies in HCI
Date Deposited:	18 Feb 2026 07:39
Last Modified:	18 Feb 2026 07:39
URI:	https://pubs.cs.uct.ac.za/id/eprint/1777

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