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Realizing the Potential of AI in Africa: It All Turns on Trust

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Towards Trustworthy Artificial Intelligent Systems

Part of the book series: Intelligent Systems, Control and Automation: Science and Engineering ((ISCA,volume 102))

Abstract

Most nations have recognized the disruptive influence of artificial intelligence (AI) on all aspects of their economies, from manufacturing, to services, to governance, and the potential benefits that embracing AI technologies can bring. It is no different in developing countries and it is certainly the case that the countries of Africa have embraced AI, data science, machine learning, and robotics. However, the transition from recognition of potential to realization of benefits is not a straightforward matter. In this essay, we argue that this transition depends on turning technological invention into innovation, that technological innovation cannot happen without adoption, and that adoption depends on socio-cultural factors, in general, and on trust, in particular. We draw out the implications for AI in developing countries in Africa, arguing that, for Africa to realize the potential of AI in solving economic and social problems, the advancement and deployment of AI must be driven and executed by the peoples of Africa: if it is not, there will be little trust, less adoption, and minimal benefits.

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Notes

  1. 1.

    For an overview of national AI policies and strategies globally, see [69].

  2. 2.

    Africa is a continent comprising fifty-four countries and many different cultures: it is not a homogeneous society and this needs to be borne in mind when speaking of “Africa”. Indeed, the words of Horst Köhler, former President of Germany, in his speech on the impossibility of speaking of Africa sounds a cautionary note: “I would like, if I may, to clear up one misunderstanding right away: Horst Köhler is not an Africa expert … the reality on the ground in Africa is so much more complex than written accounts suggest … the more I learned about Africa, the more I realised how much there was still to learn” [51].

  3. 3.

    To see a Zipline drone drop blood packs to a clinic in rural Rwanda, see https://bit.ly/2pfnB6l (time interval 0′ 52″–1′ 22″).

  4. 4.

    Imbizo is a Xhosa word meaning “a gathering to share knowledge” [43].

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Acknowledgements

The ideas and arguments put forward in this chapter can be traced to many sources. However, they were heavily influenced by our collective experience at Carnegie Mellon University Africa, Kigali, Rwanda. We would like to thank everyone there for making it such a special place to learn and teach. Daniel Omeiza gratefully acknowledges support by the UK’s Engineering and Physical Sciences Research Council (EPSRC) through project RoboTIPS: Developing Responsible Robots for the Digital Economy, grant reference EP/S005099/1. Charity Delmus Alupo gratefully acknowledges support by Science Foundation Ireland through the SFI Centre for Research Training in Machine Learning, grant reference 18/CRT/6183.

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Authors and Affiliations

  1. School of Business, University College Dublin & SFI Centre for Research Training in Machine Learning, Dublin, Ireland

    Charity Delmus Alupo

  2. Department of Computer Science, University of Oxford, Oxford, UK

    Daniel Omeiza

  3. Carnegie Mellon University Africa, Kigali, Rwanda

    David Vernon

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  1. Charity Delmus Alupo
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  2. Daniel Omeiza
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  3. David Vernon
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Correspondence to David Vernon .

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Editors and Affiliations

  1. Centro de Filosofia, Universidade de Lisboa, Lisbon, Portugal

    Maria Isabel Aldinhas Ferreira

  2. School of Engineering, London South Bank University, London, UK

    Mohammad Osman Tokhi

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Alupo, C.D., Omeiza, D., Vernon, D. (2022). Realizing the Potential of AI in Africa: It All Turns on Trust. In: Ferreira, M.I.A., Tokhi, M.O. (eds) Towards Trustworthy Artificial Intelligent Systems. Intelligent Systems, Control and Automation: Science and Engineering, vol 102. Springer, Cham. https://doi.org/10.1007/978-3-031-09823-9_13

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