Reframing AI Design Through African Women’s Livelihood Intelligence: A Review and Conceptual Framework for SME Contexts

Jacqueline Akelo Gogo, Emma Muturi, Victoria Oguntosin
Proceedings of IndabaX Nigeria 2026: Building Scalable AI That Works: From Research to Deployment in Resource-Constrained Environments, PMLR 319:191-204, 2026.

Abstract

This paper develops a conceptual and methodological foundation for designing inclusive, context-aware AI systems grounded in women’s livelihood practices within small and medium enterprises (SMEs). Drawing on feminist economics, sustainable livelihoods, value-sensitive design, and feminist HCI, the paper synthesises knowledge on how women navigate constraints related to care, safety, informality, and resource access. A multi-layered conceptual framework connects livelihood practices with sociotechnical systems and AI development. The proposed research design combines qualitative inquiry and participatory methods to translate women’s lived experiences into AI design principles and evaluation metrics, advancing a novel research agenda for equitable AI in women-led African SMEs.

Cite this Paper

BibTeX
@InProceedings{pmlr-v319-gogo26a, title = {Reframing {AI} Design Through {African} Women’s Livelihood Intelligence: A Review and Conceptual Framework for {SME} Contexts}, author = {Gogo, Jacqueline Akelo and Muturi, Emma and Oguntosin, Victoria}, booktitle = {Proceedings of IndabaX Nigeria 2026: Building Scalable AI That Works: From Research to Deployment in Resource-Constrained Environments}, pages = {191--204}, year = {2026}, editor = {Folorunso, Sakinat and Ogundokun, Roseline and Oladipo, Francisca}, volume = {319}, series = {Proceedings of Machine Learning Research}, month = {11--14 May}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/v319/main/assets/gogo26a/gogo26a.pdf}, url = {https://proceedings.mlr.press/v319/gogo26a.html}, abstract = {This paper develops a conceptual and methodological foundation for designing inclusive, context-aware AI systems grounded in women’s livelihood practices within small and medium enterprises (SMEs). Drawing on feminist economics, sustainable livelihoods, value-sensitive design, and feminist HCI, the paper synthesises knowledge on how women navigate constraints related to care, safety, informality, and resource access. A multi-layered conceptual framework connects livelihood practices with sociotechnical systems and AI development. The proposed research design combines qualitative inquiry and participatory methods to translate women’s lived experiences into AI design principles and evaluation metrics, advancing a novel research agenda for equitable AI in women-led African SMEs.} }
Endnote
%0 Conference Paper %T Reframing AI Design Through African Women’s Livelihood Intelligence: A Review and Conceptual Framework for SME Contexts %A Jacqueline Akelo Gogo %A Emma Muturi %A Victoria Oguntosin %B Proceedings of IndabaX Nigeria 2026: Building Scalable AI That Works: From Research to Deployment in Resource-Constrained Environments %C Proceedings of Machine Learning Research %D 2026 %E Sakinat Folorunso %E Roseline Ogundokun %E Francisca Oladipo %F pmlr-v319-gogo26a %I PMLR %P 191--204 %U https://proceedings.mlr.press/v319/gogo26a.html %V 319 %X This paper develops a conceptual and methodological foundation for designing inclusive, context-aware AI systems grounded in women’s livelihood practices within small and medium enterprises (SMEs). Drawing on feminist economics, sustainable livelihoods, value-sensitive design, and feminist HCI, the paper synthesises knowledge on how women navigate constraints related to care, safety, informality, and resource access. A multi-layered conceptual framework connects livelihood practices with sociotechnical systems and AI development. The proposed research design combines qualitative inquiry and participatory methods to translate women’s lived experiences into AI design principles and evaluation metrics, advancing a novel research agenda for equitable AI in women-led African SMEs.
APA
Gogo, J.A., Muturi, E. & Oguntosin, V.. (2026). Reframing AI Design Through African Women’s Livelihood Intelligence: A Review and Conceptual Framework for SME Contexts. Proceedings of IndabaX Nigeria 2026: Building Scalable AI That Works: From Research to Deployment in Resource-Constrained Environments, in Proceedings of Machine Learning Research 319:191-204 Available from https://proceedings.mlr.press/v319/gogo26a.html.

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