I am currently focusing on research that shapes critical and complex conversations about AI development and deployment. While my studies focused on how AI co-design spaces could be improved to capture diverse perspectives in the Agtech ecosystems in the global north, I am currently focusing on AI sociotechnical systems in agrifood systems in Africa. My recent roles in FAO, the Centre for Epistemic Justice Foundation and Athena Infonomics, have contributed in shaping inclusion modalities and strategies for the historically marginalized groups, including smallholder farmers, rural women and youth, with the aim of ensuring that AI benefits are shared across different actors in African Agrifood landscape. 

Part of my research findings show that pre-existing cultural and systemic norms, that perpetuate exclusion practices, are complexly entangled in the way AI solutions are designed and deployed in the agri-food systems in Africa. This situation is further exacerbated by the digital divide between different but complexly intertwined groups e.g., large-scale vs smallholder farmers, male vs female, youth vs older farmers etc. Furthermore the limited knowledge about how AI applications work, complicates issues of data governance, data accountability and data justice, with farmers having limited information about how their data may be used, managed, as well as what is the value of that data and how it may be accessed and/or shared. Thus, currently, AI effectiveness in Africa is narrowly defined along the lines of relevance and scalability, as opposed to the ultimate social, and economic transformation it may bring to the smallholder and the last mile farmer. These issues seem to be compounding the already existing social justice issues in the Africa food systems, making AI a tool that only benefits a few. This also risks the future of Africa’s food security, given that over 80% of food in Africa is produced by smallholder farmers.

AI provides an opportunity for African smallholder farmers to benefit from improved farm level-decision-making, as well and improved policy, in the big data economy. However, this opportunity is feasible, if development of AI centres on the needs, interests and values of the smallholder, while balancing this with different business interests. Active co-designing of the tools and the frameworks that govern the tool and data is critical to sustainable AI driven futures in Africa Agrifood systems.