Project Duration: 2023-2024
Grantor: Gender at Work, Canada.
Partners: Kumasi Hive,Ghana and International Centre of Insect Physiology and Ecology (icipe), Kenya
Grant Amount: US$ 18,910
The application of artificial intelligence (AI) is enthusiastically lauded as one of the solutions to overcome challenges to agriculture in Africa. Women dominate the agricultural work force, making up 60% – 80%, but despite this dominance and significant contributions, the productivity divide between men and women and other marginalized farmers persists across Africa. An unfavorable gender divide resulting from poor access to technology, limited access to land ownership and financial resources, and low education levels contribute to the disparity. The ability to use AI innovation is a function of multiple factors including education, digital literacy, technological and structural competence, and resources, which do not favor women and marginalized farmers. Consequently, AI is likely to further exacerbate the existing gender disparities unless mitigation measures are put in place. This proposal aims to foster gender equity in AI-enabled agricultural innovation with reference to two selected countries under the Artificial Intelligence for Agriculture and Food Systems (AI4AFS) innovation research network. The African Technology Policy Studies Network (ATPS) and its Partners, Kumasi Hive and icipe will implement the Innovation Challenge project under two distinct but interrelated work packages, namely; design by inclusion, training, and technical support to improve the adoption and use of AI technologies in AFS by women and marginalized communities in the participating countries (Work Package 1), and development of a set of best practices and recommendations for gender inclusive AI technology adoption for women and marginalized communities in AFS in Africa (Work Package 2).
Goal and Specific Objectives
The overall goal of the project is to strengthen the capacity of women and marginalized communities to benefit from the potentials of AI technologies in Agriculture and Food systems (AFS) in Africa.
The Specific Objectives are to:
Expected Outputs and Outcomes
(To be updated)