June 23, 2023

Qondi Moyo

The Fourth Industrial Revolution is in full swing, bringing with it a wave of technological advancements that have the potential to reshape industries and economies across the globe. Artificial Intelligence (AI) is at the forefront of this revolution, promising to transform various sectors and drive inclusive growth. In Africa, could the adoption of AI and related technologies accelerate the continent’s development and help to achieve the United Nations Sustainable Development Goals (SDGs)?

The Potential of AI in Africa

By 2030, AI is projected to contribute a staggering $15.7 trillion to global GDP, with $6.6 trillion coming from increased productivity and $9.1 trillion from consumption effects. AI has the potential to fundamentally change the way businesses operate, drive innovation, and improve the lives of millions of people across Africa. Some of the key sectors that could benefit from AI include healthcare, agriculture, education, and finance. There are already a number of applications of AI in Africa, especially towards health, water supply, clean energy forecasting, climate change predictions, economics and finance, as well as governance.

During a lecture hosted by United Nations University Institute for Natural Resources in Africa (UNU-INRA), Nature Speaks: Artificial Intelligence and Growth, at the University of Ghana on 25 May 2023, Professor Tshilidzi Marwala, Rector of the UNU and former Vice-Chancellor of the University of Johannesburg, shared insights on how Artificial Intelligence can contribute to the achievement of the sustainable development goals in Africa, as discussed below.

How is AI being applied in Africa towards achieving the SDGs?

The adoption of AI and related technologies in Africa could have the potential to significantly impact the achievement of the United Nations Sustainable Development Goals (SDGs). By driving economic growth, improving access to quality education and healthcare, and promoting sustainable agriculture, AI can play a crucial role in addressing some of the continent’s most pressing challenges.

Health and medical applications (SDG 3)

Professor Marwala revealed that “during Covid, AI was used to predict the peaks of the pandemic”. At the University of Johannesburg, scientists predicted the first wave of covid-19 in South Africa, before it had spread widely across the country. AI enables predictions to be made given limited data. Using a Bayesian inference with the compartmental SIR models, AI scientists were able to support public health policymakers to quantify the impact of government interventions, allowing them to plan ahead. Therefore, AI can be pivotal in improving global health and well-being towards achieving SDG3.

Water (SDG 6)

AI can also be used to forecast water demand to enable water supply entities to provide adequate supply of clean and safe water to meet consumer needs. This is essential to ensuring human rights to water and sanitation, and SDG 6. AI enables the monitoring of water quality to detect contaminants, pollutants, and alterations in water quality. Early detection may be beneficial in the prevention of waterborne diseases and the protection of water supplies.
AI and clean energy forecasting (SDG 7 & 13)
Accelerating clean energy adoption requires accurate modelling of renewable energy supply to meet rising demand. Studies have used AI to forecast wind speed for energy harvested using windmills to ensure accurate measurements of wind power supply. This forecasting will go a long way in managing renewable resources and ensuring steady and affordable clean energy supply towards achieving SDGs 7 and 13.

AI and Climate Change (SDG 13 & 15)

Climate science can also make use of AI to support weather predictions. This can be useful for predicting water levels and the risk of flooding or, conversely, the risk of drought and desertification. Detecting flooding and drought is particularly important for agricultural planning. Accurate predictions can support adaptation measures and help government officials and policymakers to plan and prepare in order to minimise the negative impacts. AI has the potential to facilitate the creation of climate models that simulate the complex interactions that can impact climate change in Africa. It can support data analysis using historical data, climate variables, and satellite imagery in conjunction with AI algorithms to improve the accuracy and reliability of climate predictions concerning rainfall patterns, extreme events, and temperature change. For a continent whose economies depend on climate, predictive abilities will facilitate anticipatory planning and assist demand-side constituency groups, farmers, and policymakers in making strategic decisions and identifying potential risks.

AI and economics (SDG 8)

AI has redefined aspects of economics and finance, enabling complete information, reduced margins of error and better market outcome predictions. In economics, price is often set based on aggregate demand and supply. However, AI systems can enable specific individual prices based on different price elasticities. This reduces market information asymmetries and supports market competition for better price equilibrium outcomes and better choices to support economic growth and SDG 8.

AI and governance (SDG 16)

Governments require accurate predictions to plan ahead and make good governance choices. An area that has benefitted from the use of AI, is in predictions of the outbreak of war and conflict based on risk and other variables. This intelligence can result in measures to prevent conflict or minimise the spread and damage caused.

AI and international relations (SDG 16 & 17)

In our globalised and ever-digitalising world, AI is relevant and utilised under several aspects of international relations, such as trade, international finance, technological transfer, human rights, as well as power and international politics.

Opportunities

AI innovation in Ghana

Special Advisor to the Government of Ghana, Dr. Hilde Opuku, discussed Ghana’s progress towards the SDGs positing that, “By introducing digitalisation we [Ghana] can leapfrog.” Mentioning further that, “Ghana is not doing bad on the Fourth Industrial Revolution’. Indeed, Ghana has made significant strides towards developing artificial intelligence technologies from a local context, especially in the area of FinTech where Ghana is spearheading other African countries. Additional digital and AI innovations can be found in the health sector, for example services supplying medical supplies using drone technology. AI is also quite prevalent in agriculture, with tools developed to help farmers track weather patterns, monitor production conditions and plan agricultural practices more efficiently. There are also language technologies using AI to translate information into local languages. However, there is a lack of data to optimise AI technologies.

The challenges of AI in Africa

Despite its vast potential, the adoption and implementation of AI in Africa face several challenges, including a lack of relevant technical skills, inadequate basic and digital infrastructure, insufficient investment in research and development, and a need for more flexible and dynamic regulatory systems.

The skills gap

The lack of relevant technical skills, particularly among young people, is a major barrier to the adoption of AI in Africa. This skills gap is preventing the continent from fully harnessing the potential of transformative technologies and industries.

The Digital Revolution is well underway globally, and there is a fear that Africa will be left behind as the digital gap grows. “The digital divide is much broader than AI because you need devices, and as governments and as the African Union, we need to think about moving some of the manufacturing of these devices to the African continent,” Professor Marwala remarked.

Data limitations

The success of AI applications depends on the availability of high-quality and diverse data. In Africa, there is a significant challenge in ensuring that AI systems are trained on data that accurately reflects the local population and addresses the unique challenges faced by the continent. Moreover, the lack of structured data ecosystems in Africa can impede the development and implementation of AI-powered solutions, further exacerbating the digital divide between the global north and south.

According to Professor Marwala, “On the African continent, we are not collecting as much data as we are supposed to collect, and much of the data we collect in Africa often tends to be incomplete”. In addition, much of the data collected is gathered in the global North, so machines have limited understanding of the African context. Professor Marwala noted that “the algorithms made in the North assume the data is complete. How do we design AI that is able to work even in the presence of missing information?”

Linked to this is access to data. Marwala suggested that governments, telecoms companies, and regulators must all work towards enabling access to data at fair pricing.

Research and development

Investment in research and development is critical for driving innovation and fostering the growth of AI technologies in Africa. However, the continent lags behind in this area, with limited funding available for AI-related projects. To overcome this challenge, Africa must develop innovative financial instruments to fund human capital development.

Displacement of jobs

There is a fear that the growth of AI and automation will lead to a displacement of jobs. “The fast pace of automation of the manufacturing sector is impacting the future of work,” Marwala remarked. However, there is a general consensus that it is impossible to reverse this trend. Instead, “We need to adopt them [AI technologies] into production value chains to increase productivity and strengthen production. We need to capacitate ourselves to be able to play this role,” Marwala suggested further.

Looking ahead

Artificial intelligence presents a unique opportunity for Africa to leapfrog into the Fourth Industrial Revolution and drive large-scale transformation. To fully harness the potential of AI, Africa must address the challenges above.

It is important to incentivise the adoption of technologies in Africa to ensure the continent participates in the Fourth Industrial Revolution. At the same time, these technologies must be understood, including their drawbacks.

The German Ambassador to the Republic of Ghana, Dr. Daniel Kroll, closed the lecture by stressing that there is a need for more education in mathematics and informatics. He also mentioned the need to increase the African footprint in shaping the regulation field of artificial intelligence.

Africa’s fast-growing and young population presents opportunities for economic growth and competitive innovation. At the same time, rapid urbanisation and its impact on employment, energy, industry, and environment must be managed. Dr. Fatima Denton, UNU-INRA Director, said, “We must focus on cities given the number of people in Africa that live in slums, but also cities are a big contributor to global emissions as one-third of global emissions are produced in cities.”

Professor Chris Gordon warned, “Without managing natural resources, we in Africa are very vulnerable”.

References

1.     Sizing the prize. What’s the real value of AI for your business and how can you capitalise? PwC. Available online: https://www.pwc.com/gx/en/issues/data-and-analytics/publications/artificial-intelligence-study.html
2.     Mbuvha, Rendani, and Tshilidzi Marwala. Bayesian inference of COVID-19 spreading rates in South Africa. PloS one vol. 15,8 e0237126. 5 Aug. 2020, doi:10.1371/journal.pone.0237126
3.     I. S. Msiza, F. V. Nelwamondo and T. Marwala, Artificial Neural Networks and Support Vector Machines for water demand time series forecasting, 2007 IEEE International Conference on Systems, Man and Cybernetics, Montreal, QC, Canada, 2007, pp. 638-643, doi: 10.1109/ICSMC.2007.4413591.
4.     Rendani Mbuvha, Wilson Tsakane Mongwe, Tshilidzi Marwala, Separable Shadow Hamiltonian Hybrid Monte Carlo for Bayesian Neural Network Inference in wind speed forecasting, Energy and AI, Volume 6, 2021,100108, ISSN 2666-5468, https://doi.org/10.1016/j.egyai.2021.100108
5.     Marwala, Tshilidzi, and Evan Hurwitz. Artificial intelligence and economic theory: skynet in the market. Vol. 1. Cham: Springer International Publishing, 2017.
6.     Marwala, Tshilidzi, and Monica Lagazio. Militarized conflict modeling using computational intelligence. Springer Science & Business Media, 2011.
7.     Ndzendze, B., & Marwala, T. (2023). Artificial Intelligence and International Relations. In Artificial Intelligence and International Relations Theories (pp. 33-54). Singapore: Springer Nature Singapore.
8.     Haroon Bhorat, Landry Signé, Zaakhir Asmal, Jabulile Monnakgotla, and Christopher Rooney (2023). Digitalization and digital skills gaps in Africa: An empirical profile. Brookings Institution. Available here: https://www.brookings.edu/research/digitalization-and-digital-skills-gaps-in-africa-an-empirical-profile/
9.     Ade-Ibijola, A., Okonkwo, C. (2023). Artificial Intelligence in Africa: Emerging Challenges. In: Eke, D.O., Wakunuma, K., Akintoye, S. (eds) Responsible AI in Africa. Social and Cultural Studies of Robots and AI. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-08215-3_5