PriMera Scientific Engineering (ISSN: 2834-2550)

Review Article

Volume 4 Issue 6

The Importance of Artificial Intelligence to Africa's Development Process: Prospects and Challenges

Censrehurd, Zemoh Yannick Tangmoh and Pefela Gildas Nyugha*

May 27, 2024

Abstract

     On a continent that is frequently portrayed in a condition of permanent crisis, development appears to be an impossibility. In fact, observers of African affairs, especially those in the West, cannot feel reassured by recent military takeovers and armed conflicts like those in Sudan and Gabon that Africa is rising—a claim once made by influential figures in world opinion like The New York Times, The Economist, and others. It appears that development is in critical need of an immediate revival. To put things in perspective, the Organization for Economic Co-operation and Development (OECD) reports that official development assistance (ODA) reached a total of USD 185.9 billion in 2021. However, the depressing results of development demonstrate the futility of international development. For instance, since 2019, the majority of the nations receiving aid from abroad have seen increases in their rates of poverty, with 50% to 70% of their people living below the poverty line (1,2).

     Situations around the world are not promising. The World Bank estimates that in 2022, there will be over 700 million individuals worldwide who are living in extreme poverty. The UN's most recent SDG 2023 progress report (1.3) presents a dismal picture. On almost 50% of the targets, there has been insufficient and weak development. Even worse, almost 30% of the SDG targets have seen either a standstill in development or a reversal in them. This contains important goals about hunger, poverty, and the environment. Moreover, the research finishes on a very concerning note: over half of the world is falling behind, and most of those falling behind reside, you guessed it, in the Global South.

Artificial intelligence (AI) is being positioned as a useful tool for accelerating development objectives and targets and repairing the flawed international development paradigm as the global development agenda suffers. International development organizations and regional partners have implemented innovative AI for development (AI4D) initiatives in a number of African nations, including those in Sub-Saharan Africa and West Africa. With all of the hype around artificial intelligence, this seems like a reasonable and necessary endeavor. However, the deficit model of development serves as the foundation for AI initiatives in Africa. This deficit argument highlights how the lack of human and technological capability is the direct cause of the Majority World's inability to progress.

     In an effort to maximize the amount of electricity available, the Responsible AI Lab (RAIL) in Ghana (1.4) is attempting to integrate efficient energy distribution models into the system. Natural language processing (NLP) is arguably one of the most promising uses of AI in the region. Emerging start-ups using development funding programs like the Lacuna Fund are attempting to create language models for indigenous African languages like Igbo, Hausa, Yoruba, Twi, Akan, and others. These models can be integrated into further applications in fields like education and healthcare. Given the regional circumstances in the majority of African nations, the advantages of these programs and apps may be obvious.

     Actually, though, large multinational corporations' CSR programs (4) and the policies of international development organizations have a significant influence on most AI development in Africa. In an effort to become future bright spots in the field of technology, these initiatives which are carried out in partnership with Big Tech and regional players like scientists and practitioners are unduly focused on developing technological solutions and local African datasets. Much time and money are being spent collecting local datasets so that machine learning models for predictive analysis can be updated based on the local context.

     But how much is known about the goals and applications of these AI programs, and which social groups and communities stand to benefit from them? How will the local context respond to these technology solutions? To put it bluntly, there isn't enough deliberate interaction with the political imaginations of the various local communities in terms of their aspirations for an AI-powered technological future1

References

  1. Allen RC. “Explaining the British Industrial Revolution from the Perspective of Global Wage and Price History”. helsinki.fi (2006).
  2. AUC/OECD (2023), Africa's Development Dynamics 2023: Investing in Sustainable Development, AUC, Addis Ababa/OECD Publishing, Paris.
  3. Blinov S. “Causes of the British Industrial Revolution”. Munich Personal RePEc Archive: Munich, Germany (2014).
  4. Davids YD and Gouws A. Explaining Poverty: A Comparison between Perceptions and Conditions of Poverty in South Africa (2010).
  5. Davis P and Sanchez-Martinez M. A Review of the Economic Theories of Poverty. National Institute of Economic and Social Science (2014).
  6. Dunga H. The Impact of Technological Revolution on Poverty: A Case of South Africa; IDEAS, 2019. Ideas.repec.org
  7. Guterres A. Report of the Secretary-General on SDG Progress 2019: Special Edition; United Nations Publications: Herndon, VA, USA (2019): 1-64.
  8. https://acetforafrica.org/
  9. https://acetforafrica.org/
  10. https://african.business/2024/02/finance-services/africas-eurobonds-market-roars-back-to-life
  11. https://bootcamp.cvn.columbia.edu/blog/what-is-fintech/
  12. https://botpopuli.net/ai-is-africas-new-development-mantra-but-can-it-fix-development/
  13. https://conference.ai4d.ai/
  14. https://conference.ai4d.ai/
  15. https://journals.co.za/doi/abs/10.10520/EJC-7171f88f4
  16. https://peafrinsights.co.za/zande-africa/
  17. https://peafrinsights.co.za/zande-africa/
  18. https://rail.knust.edu.gh/
  19. https://unstats.un.org/sdgs/indicators/regional-groups.
  20. https://unstats.un.org/sdgs/report/2023/. ISBN: 978-92-1-101460-0
  21. https://www.businessnewsdaily.com/4679-corporate-social-responsibility.html
  22. https://www.deeplearning.ai/resources/natural-language-processing/
  23. https://www.elibrary.imf.org/display/book/9781557752321/ch017.xml
  24. https://www.mdpi.com/2071-1050/13/11/5788
  25. https://www.minohealth.ai/
  26. https://www.oecd-ilibrary.org/development/africa-s-development-dynamics-2023_3269532b-en
  27. https://www.oecd-ilibrary.org/development/africa-s-development-dynamics-2023_3269532b-en
  28. https://www.power-technology.com/data-insights/power-plant-profile-menchum-hydropower-project-cameroon/?cf-view
  29. https://www.un.org/en/climatechange/what-is-renewable-energy
  30. Mhlanga D. Financial Inclusion and Poverty Reduction: Evidence from Small Scale Agricultural Sector in Manicaland Province of Zimbabwe (2020).
  31. Mhlanga D and Ndhlovu E. Socio-economic Implications of the COVID-19 for Smallholder Livelihoods in Zimbabwe. Preprints (2020).
  32. Schwab K. The Fourth Industrial Revolution. What It Means and How to Respond? (2016).
  33. See the “Report of the Inter-Agency and Expert Group on Sustainable Development Goal Indicators” (E/CN.3/2019/2), annex I.
  34. The complete list of indicators. https://unstats.un.org/sdgs/indicators/indicators-list/.
  35. The discussion note. “Update of the regional groupings for the SDG report and database” of 31 October 2016 describes the details of this change.