Thus far, we have considered AI’s intersections with Africa’s complex socio-economic realities as well as interrogated how and why current ethics guide-lines and debates are out of touch with these realities.We have also suggested partially addressing the continent’s AI challenges through a relational ethics of care that recognises the importance of qualities such as advocacy, inclu-sivity, participation, and plurality within AI ecosystems. Foregrounding AI as a socio-technical phenomenon does not in any way imply a dismissal of AI as either a scientific or technical field of enquiry. However, the way in which the fourth industrial revolution is emerging in Africa is clearly dis-similar to how it is evolving in the Global North (cf. Wairegi, Omino and Rutenberg,2021 p. 2) and subsequently demands an emphasis on AI for social improvement, rather than on AI for technological innovation alone (Kiemde and Kora, 2021 p.5): in a recent exhaustive and sobering assess-ment of how the fourth industrial revolution is developing in Africa, politi-cal scientist Everisto Benyera offers the caveat that it "will not end or lessen [the continent’s] challenges which are a product of centuries of being on the darker side of Euro-North American modernity" (Benyera, 2021, p.xi). To compound matters, in proposing a way forward for Africa to harness the benefits of AI, Gwagwa et al. (2021) report that Africa scores low in terms of AI readiness owing to the absence of a vision for AI deployment (Gwagwa et al., 2021, p. 5). Gadzala (2018, p.1) goes so far as to declare that for most African countries, employing AI remains an ignis fatuus, given the absence in these countries of definitive reforms as they pertain to critical issues such as data privacy, governance, and digital education.
In the previous chapter, we referred to the importance of AI-stakeholders-in-the loop. In identifying these actors or stakeholders, Wairegi, Omino and Rutenberg (2021, p.6) indicate that while primary (or expert) stakeholders such as AI developers and companies have "direct input" in the design and application of their products, secondary and tertiary stakeholders do not have this privilege. Secondary stakeholders include consumer groups and advertising companies that may enjoy some level of participation, while tertiary actors made up of the general public in all probability experience little, if any, direct involvement in AI ecosystems. All stakeholders have intrinsic value (Wairegi et al., 2021, p. 5), but the focus of this chapter falls mainly on tertiary actors, particularly on excluded or vulnerable individuals who are most at risk of being harmed through the development and deploy-ment of AI, although secondary actors are also considered, since they too often exhibit a layperson’s knowledge of AI. The questions are How do secondary and tertiary actors in Africa perceive AI in the first place? and Why does this matter? While it is easy to answer the second question, it is far more difficult to address the first, given the dearth of sources that have attempted to explicitly gauge public opinion of AI on the continent. What complicates the issue is that defining AI is not a simple task and may be clouded by the hype-filled message that it constitutes a cure-all for human problems. Obscuring the realities of what AI is and what it does is the pro-liferation of misleading metaphors employed to describe its myriad aspects. Hype around AI and the various imaginaries employed to frame it neither comport with this technology’s realities nor acknowledge Africa’s diverse, social, political, and economic landscapes.