Inventing Artificial Intelligence in Ethiopia

Abstract

Artificial Intelligence (AI) research has always been embedded in complex networks of cultural imagination, corporate business, and sociopolitical power relations. The great majority of AI research around the world, and almost all commentary on that research, assumes that the imagination, business, and political systems of Western culture and the Global North are sufficient to understand how this technology should develop in future. This article investigates the context within which AI research is imagined and conducted in the Amhara region of Ethiopia, with implications for public policy, technology strategy, future research in development contexts, and the principles that might be applied as practical engineering priorities.

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“…During the last 5 years, its role has been especially enhanced, not only in technological industries but also among huge amount of enterprises (Elam and Konsynski, 2010) (Elam & Konsynski, 2010). Considerable amount of traditional handwork activities are replaced by intelligent applications (Nourani, 2011;Munoko et al, 2020;Blackwell et al, 2021) (Blackwell et al, 2021;Bock et al, 2020;Nilsson, 1996;Pesapane et al, 2018). A large number of traditional human affairs, especially those with strong process and strong replaceability, are facing the possibility of being banned by electronic products.…”

Taking data science into the forest

“…The first of those papers, Objective Functions, Deep Learning and Random Forests , questioned the epistemological and cultural foundations of AI, advocating a contextualized, qualitative and interpretive social science of “big data”, and leading to a published paper that interrogated (In)humanity and Inequity in Artificial Intelligence (Blackwell 2019). The second of Blackwell's SFSP contributions proposed an agenda for Ethnographic Artificial Intelligence (Blackwell 2021), introducing the plans for his own fieldwork in Ethiopia, Namibia and Uganda, cut short by the Covid-19 pandemic, but leading to publication with his Ethiopian colleagues on Inventing Artificial Intelligence in Ethiopia (Blackwell, Damena and Tegegne 2021) as discussed further below.…”

“…A project undertaken by Alan Blackwell, in collaboration with colleagues in Ethiopia and the UK, extended the methods developed in Longdon's MRes project to a specific conservation context and local community. Blackwell's collaboration with AI researchers in Bahir Dar Ethiopia had previously identified the opportunity for an alternative approach to AI that they described as “broad learning” (Blackwell, Damena and Tegegne 2021), for its emphasis on including wider contexts and populations, as a contrast to the “deep learning” methods that have been developed through the extractive and exploitative commodification of data (Blackwell 2023).…”

“…This experiment in broad learning was completely reliant both on globalised infrastructures (Landsat, Google Earth Engine, Android phones, what3words), and also on the agenda of the STEM centre that associated development opportunities with technical and scientific education (our collaborator Dr Tesfa Tegegne, the principal of the STEM centre, was also the director of the BDU research centre in ICT for development). These tensions between global trends in technology research on one hand, and local autonomy and agency on the other, permeate AI research (Blackwell, Damena and Tegegne 2021), but the next case studies explore ways in which closer engagement with the forest unsettles that technically-driven perspective.…”