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Towards an Artificial Intelligence Readiness Index for Africa

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Digital-for-Development: Enabling Transformation, Inclusion and Sustainability Through ICTs (IDIA 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1774))

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Abstract

The applications and benefits of Artificial Intelligence (AI) for socio-economic development are immense. AI is projected to contribute approximately USD 15.7 trillion to the global Gross Domestic Product (GDP) by 2030. However, countries need to be prepared to harness such benefits. Hence, assessing the AI readiness of a country is paramount. Africa is currently the only continent without an AI readiness index tailored to its needs. It relies on the existing global indices, which may not accurately measure the progress attained by individual African countries because of the different levels of development and unique context. This paper proposes an AI readiness index for Africa. It starts by exploring what the AI readiness index needs of Africa are, examines the extent to which existing AI readiness indices meet the needs, and then looks at indicators that should constitute the AI readiness index for Africa.

The study employed a systematic literature review that aimed to explore the AI readiness needs for Africa and the extent existing indices meet these. The review focused on papers published on the AI readiness index between January 2018 to August 2022. The search strategy retrieved 301 papers, of which seven papers were selected for a detailed analysis. The study revealed that the existing indices partially meet AI readiness needs for Africa. The study also found that AI readiness index dimensions pertinent to Africa’s requirements are: Vision, Governance and Ethics, Digital Capacity, Size of the Technology Sector, Research and Development, Education, Infrastructure, Data Availability, general level of employment, employment in Data Science and AI roles, and Gross Domestic Product-Per Capita Purchasing Power Parity. This study contributes to the knowledge of AI readiness for Africa and globally. The results of this study will benefit governments, researchers, and practitioners of AI and its applications.

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Notes

  1. 1.

    https://static1.squarespace.com/static/58b2e92c1e5b6c828058484e/t/5f7747f29ca3c20ecb598f7c/1601653137399/AI+Readiness+Report.pdf.

References

  1. ESCAP, U.: Artificial Intelligence in Asia and the Pacific (2017). https://www.unescap.org/resources/artificial-intelligence-asia-and-pacific. Accessed 10 Aug 2022

  2. Arakpogun, E.O., Elsahn, Z., Olan, F., Elsahn, F.: Artificial intelligence in Africa: challenges and opportunities. In: Hamdan, A., Hassanien, A.E., Razzaque, A., Alareeni, B. (eds.) The fourth industrial revolution: implementation of artificial intelligence for growing business success. SCI, vol. 935, pp. 375–388. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-62796-6_22

    Chapter  Google Scholar 

  3. Rossi, F.: Building trust in artificial intelligence. J. Int. Aff. 72(1), 127–134 (2018)

    Google Scholar 

  4. Haseeb, M., Mihardjo, L.W., Gill, A.R., Jermsittiparsert, K.: Economic impact of artificial intelligence: new look for the macroeconomic assessment in Asia-Pacific region. Int. J. Comput. Intell. Syst. 12(2), 1295 (2019)

    Article  Google Scholar 

  5. Susar, D., Aquaro, V.: Artificial intelligence: opportunities and challenges for the public sector. In Proceedings of the 12th International Conference on Theory and Practice of Electronic Governance, pp. 418–426 (2019)

    Google Scholar 

  6. Oxford Insights: Government AI Readiness Index (2019). https://www.oxfordinsights.com/ai-readiness2019. Accessed 22 July 2022

  7. Gillham, J.: The macroeconomic impact of artificial intelligence. Price water house Coopers (2018). https://doi.org/10.13140/RG.2.2.21506.38083

  8. Jain, S.: US $320 billion by 2030. The potential impact of AI in the Middle East (2018). https://www.pwc.com/m1/en/publications/potential-impact-artificial-intelligence-middle-east.html. Accessed 28 July 2022

  9. Chen, N., Christensen, L., Gallagher, K., Mate, R., Rafert, G.: Global economic impacts associated with artificial intelligence. Anal. Group 1–23 (2016)

    Google Scholar 

  10. APET: Africa’s Socio-Economic Development AI for Africa (2018)

    Google Scholar 

  11. Vernon, D.: Robotics and artificial intelligence in Africa [regional]. IEEE Robot. Autom. Mag. 26(4), 131–135 (2019)

    Article  Google Scholar 

  12. ESCAP, U.: Artificial intelligence in the delivery of public services (2019). https://www.unescap.org/publications/artificial-intelligence-delivery-public-services. Accessed 10 Aug 2022

  13. Oxford Insights: Government AI Readiness Index (2017). https://www.oxfordinsights.com/government-ai-readiness-index2021. Accessed 21 July 2022

  14. Oxford Insights: Government AI Readiness Index (2021). https://www.oxfordinsights.com/ai-readiness2021. Accessed 22 July 2022

  15. Daniel, Z., et al.: The AI index 2021 annual report (2021). https://hai.stanford.edu/ai-index-2021. Accessed 09 July 2022

  16. Daniel, Z., et al.: The AI index 2022 annual report (2022). https://hai.stanford.edu/ai-index-2022. Accessed 09 July 2022

  17. International Institute of Communications: Artificial intelligence in the Asia-Pacific region (2020). https://www.iicom.org/wp-content/uploads/IIC-AI-Report-2020.pdf. Accessed 13 Aug 2022

  18. Moher, D., et al.: Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) statement. Syst. Rev. 4(1) (2015). https://doi.org/10.1186/2046-4053-41

  19. Dybå, T., Dingsøyr, T.: Strength of evidence in systematic reviews in software engineering. In Proceedings of the ACM-IEEE International Symposium on Empirical Software Engineering and Measurement, Kaiserslautern, Germany (2008)

    Google Scholar 

  20. Montoya, L., Rivas, P.: Government AI readiness meta-analysis for Latin America and the Caribbean. In: Proceedings of the 2019 International Symposium on Technology in Society (2019)

    Google Scholar 

  21. Oxford Insights: Government AI Readiness Index (2020). https://www.oxfordinsights.com/ai-readiness2020. Accessed 22 July 2022

  22. Oxford Insights: Government AI Readiness Index (2021). https://www.oxfordinsights.com/ai-readiness2021. Accessed 15 Aug 2022

  23. ITU: Measuring digital development: facts and figures (2019). https://www.itu.int/en/ITU-D/Statistics/Pages/facts/default.aspx. Accessed 15 June 2020

  24. Oxford Insights: Government AI Readiness Index (2022). https://www.oxfordinsights.com/ai-readiness20222. Accessed 15 Aug 2022

  25. Szoszkiewicz, L., Mickiewicz, A.: Open data: toward achieving and measuring the sustainable development goals (2021). https://doi.org/10.1007/978-3-319-71059-4_129-1

  26. ECOSOC – Economic and Social Council: Special edition: progress towards the Sustainable Development Goals (2019). 9 May 2019. E/2019/68

    Google Scholar 

  27. ECA, UNDP, Open Data for Development Network & World Wide Web Foundation. The Africa data revolution report 2016. Addis Ababa (2017)

    Google Scholar 

  28. Youn Duermeijer, Ch., Amir, M., Schoombee, L.: Africa generates less than 1% of the world’s research; data analytics can change that. Elsevier (2018). https://www.elsevier.com/connect/africa-generatesless-than-1-of-the-worlds-research-data-analytics-canchange-that. Accessed 15 June 2020

  29. Coleman, C.: This region will be worth $5.6 trillion within 5 years – but only if it accelerates its policy reforms. In: World Economic Forum (2020). https://www.weforum.org/agenda/2020/02/africaglobal-growth-economics-worldwide-gdp/. Accessed 15 June 2020

  30. Chaudron, S., Di Gioia, R., Gemo, M.: Children (0–8) and digital technology – a qualitative study across Europe. Publications Office of the European Union. Luxembourg (2017)

    Google Scholar 

  31. Awan, U., Sroufe, R., Kraslawski, A.: Creativity enables sustainable development: supplier engagement as a boundary condition for the positive effect on green innovation. J. Clean. Prod. 226, 172–185 (2019). https://doi.org/10.1016/j.jclepro.2019.03.308

    Article  Google Scholar 

  32. Shamim, S., Zeng, J., Shariq, S.M., Khan, Z.: Role of big data management in enhancing big data decisionmaking capability and quality among Chinese firms: adynamic capabilities view. Inf. Manag. 56(6), 103135 (2019). https://doi.org/10.1016/j.im.2018.12.003

    Article  Google Scholar 

  33. West, D.M., Allen, J.R.: How artificial intelligence is transforming the world. Report, 24 April 2018 (2018). https://www.bbc.com/news/business-44849492

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Author information

Authors and Affiliations

  1. Makerere University, Makerere Hill Road, Kampala, Uganda

    Rehema Baguma

  2. The Nelson Mandela African Institution of Science and Technology, Arusha, Tanzania

    Elizabeth Mkoba

  3. Ministry of Finance, Planning and Economic Development-Resource Enhancement and Accountability Program, Apollo Kagwa Road, Kampala, Uganda

    Monica Nahabwe

  4. UN Global Pulse Lab Kampala, Plot 60, Malcolm X Drive, Kololo, Kampala, Uganda

    Martin Gordon Mubangizi, Morine Amutorine & Denis Wanyama

Authors
  1. Rehema Baguma
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  2. Elizabeth Mkoba
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  3. Monica Nahabwe
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  4. Martin Gordon Mubangizi
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  5. Morine Amutorine
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  6. Denis Wanyama
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Corresponding author

Correspondence to Rehema Baguma .

Editor information

Editors and Affiliations

  1. University of Johannesburg, Johannesburg, South Africa

    Patrick Ndayizigamiye

  2. University of Johannesburg, Johannesburg, South Africa

    Hossana Twinomurinzi

  3. University of Mpumalanga, Mbombela, South Africa

    Billy Kalema

  4. University of Johannesburg, Johannesburg, South Africa

    Kelvin Bwalya

  5. University of Mpumalanga, Mbombela, South Africa

    Mncedisi Bembe

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Baguma, R., Mkoba, E., Nahabwe, M., Mubangizi, M.G., Amutorine, M., Wanyama, D. (2023). Towards an Artificial Intelligence Readiness Index for Africa. In: Ndayizigamiye, P., Twinomurinzi, H., Kalema, B., Bwalya, K., Bembe, M. (eds) Digital-for-Development: Enabling Transformation, Inclusion and Sustainability Through ICTs. IDIA 2022. Communications in Computer and Information Science, vol 1774. Springer, Cham. https://doi.org/10.1007/978-3-031-28472-4_18

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  • DOI: https://doi.org/10.1007/978-3-031-28472-4_18

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