Artificial Intelligence (AI) is the main driver of the Fourth Industrial Revolution (4IR). And while it is not a new concept – for decades computers have been programmed by humans to make decisions on available facts. But what is different now, as technology advances every day, is an evolution in machine learning.

Developing economies need to embrace Artificial Intelligence according to local conditions.

Machines are now developing what is known as “tactic knowledge”, which is essentially how the human mind works. And this will only improve with the explosion of data.

According to the Worldwide Web Foundation much focus has been on countries leading the AI revolution, while middle and low-income countries, such as South Africa, are being left behind.

In its AI report on the road ahead for these countries, it argues that given local complexities, it is key to further develop local networks and South-South cooperation. Also, it needs to be ensured that the interests and values of the those living in these countries are taken into account by global companies developing core AI advances, or leveraging on AI to execute tasks in these countries.

The report titled Artificial Intelligence: The Road Ahead in Low and Middle-Income Countries notes that while the discourse around technology is becoming universal, social and economic contexts are just as crucial.

Research by McKinsey estimates that AI is contributing to a transformation of society “happening 10 times faster and at 300 times the scale” of the Industrial Revolution. So, it only makes sense that these countries start embracing AI and spotting opportunities because there many benefits such as deepening democracy, improving service delivering and growing their economies.


On employment, economic growth and the redistribution of wealth, the document says that AI is already enabling a wave of innovation across many sectors of the global economy. It helps businesses use resources more efficiently, and enables entirely new business models to be developed, often built around AI’s ability to interrogate large data sets.

Many businesses in low and middle income countries will benefit from these capabilities, such as small entrepreneurs developing new businesses. It cites an example in Nigeria where uses natural language processing and other AI-based technology to provide mobile banking and conversational payment services to users who are unfamiliar or unable to interact with traditional browser-based online banking systems, but can interact with a familiar text-based messaging system.

While sometimes controversial, across the continent micro-credit platforms are leveraging AI to define how to measure risk when potential clients do not have a traditional credit ’footprint’.

AI is also used for fraud detection and to optimise operations as part of these platforms.

“These advancements promise to provide further dynamism to local economies by reducing transaction costs associated with lack of information. This applies to the issue of basic government data. There are expectations that AI may help to cost-effectively improve the quality of national statistics (for example on employment and wealth) that are needed for good economic planning and policy making,” the document reads.

But there are very real concerns about how AI will affect unemployment. In 2016 the World Bank Development Report estimated that automation will be happen on a much larger scale than in developed countries. Some reasons for this are that many low and middle income countries lack the communication, energy and other infrastructures that are required to support highly automated industries.

Also, regulation (local and/or global) will directly impact the evolution and adoption of these technologies in ways that are difficult to foresee

There are all worries that automation will increase the gender gap. Only 14% of women are in full-time formal employment – an indicator of a ‘good’ job – compared with 33% of men across 17 countries in the Middle East, Northern Africa, and Sub-Saharan Africa.

The document also warns that the concentration of skills in certain countries and global companies could lead to a situation where other (native) companies are crowded out.

It cites Uber as example. Currently the value produced by platforms like Uber are split between the company that owns the app and the drivers. If self-driving cars powered by AI are introduced, income will be redistributed away from drivers.

“This could result in a situation where value produced in low and middle income countries is extracted into high income countries, echoing the exploitation of minerals and natural resources in Africa by Western countries in the nineteenth century,” the paper warns.


On the strengthening of democracy, in many countries citizens still generally need to read or speak English, French, Portuguese or another colonial language, which is often the main language of government.

But this is a major barrier to fully participate politically and economically for those who speak an indigenous language or who are illiterate.

“AI-based automated translation and voice recognition systems could have significant impact in countries with multiple languages… These systems could also have an impact in places with high levels of illiteracy, allowing people to engage with the government or public service provision interfaces by spoken rather than by written means,” the paper reads.

In South Africa, the Centre for Artificial Intelligence Research (CAIR), is working in the area. By enabling greater access of minority language speakers – South Africa has 11 official languages – to public services and publicly available information, those who are democratically marginalised, will be able to better engage in democratic processes.

“One challenge to these approaches is that machine translation models tend to be refined with scale of usage, and currently mainly rely on written language to train the models. This may not be viable for some less widely used languages yet, but machine translation models already exist for some of the more widely spoken languages in low and middle income countries.” the document says.

It does, however, warn that there are several ways in which AI could undermine democracy, including authoritarian regimes using it for surveillance such as targeting political opponents based on personal data.

These risks could become greater as smartphone penetration increases.

It can also be used to identify and deny services to certain demographics. Such as example is in Ethiopia, where the state operator EthioTelecom has a monopoly on internet access. The report says authorities have intermittently shut down mobile phone and internet connections, blocked social media, and used evidence from these channels to implicate and charge dissidents and critics.

AI is also often used to spread ‘fake news’ and misinformation around elections.


While AI is being punted to improve service delivery, AI and automation may also threaten the funding of centrally-delivered public services, the paper warns.

Low and middle income countries traditionally have larger informal economic sectors than richer countries, with many workers being paid in cash, making it difficult to identify the income tax base and effectively collecting this tax. This often leads to many of these countries relying on flat consumption taxes, such as VAT, as they are easier to collect.

“If automated agents, such as chatbots or mechanical robots, perform the majority of work then the potential tax base is eroded further, leading to lower government revenues and ability to spend on the delivery of public services,” the document reads.

“(Also) these goods and services should not just be available to those who can pay for them. Particular consideration of how systems can be made accessible to the lowest income groups and marginalised populations is paramount to ensuring that inequalities are not entrenched by this technology.”


The report says it is paramount that these countries develop skills and deliver programmes so that they can maximise the benefits of AI. This must happen on all levels of society.

For poor communities, it says STEM (science, technology, engineering and math) skills could lead to economic empowerment. For programmes intended to work under government supervision, the limited capacity of these governments must be kept in mind.

It says there are already initiatives to combat skills-based inequality, often geared towards marginalised groups. African-led NGO #iamthecode supports women and girls in learning how to code through STEAMD (Science, Technology, Engineering, Arts, Mathematics and Design). It aims to reach one million girls by 2030.

In South Africa, a group of data analysts primarily based at Barclays Africa in Johannesburg, have set up the ‘Africa Success’ initiative. It uses AI to provide mentorship, resilience training and educational support to underprivileged youth in three townships.

“Although programmes like these are valuable, there is a need for larger scale rollout and government investment in STEM,” it says.


A number of recommendations have been made for areas of action.

They include creating bridges between developers in low and middle income countries and high income countries, and provide economic support to AI developers from low and middle income countries to attend global AI conferences.

The necessary resources (technical, financial and human) need to be provided to embed closer relationships, collaboration and partnerships between AI initiatives in these countries.

It is also essential that the interests of low and middle income countries are represented in key debates and decisions relating to AI.

It urges the facilitation of access to open, good quality data to enable the development of AI technologies, while ensuring personal data is not misused

The foundation also calls for systems of liability, accountability (including the ‘right to an explanation’), justification, and redress for decisions made on the basis of AI, to be ensured.

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