Author : Micheal Nayebare
Affiliated organizations : ResearchGate, Carnegie Mellon University Africa
Date of publication : 2019
Type of publication : Article
In the next five years we will witness a shift in artificial intelligence (AI) within Africa, specifically around policy issues that are likely to emerge from some of the current trends in AI and from the general technology ecosystem both in Africa and the West. Therefore, in this article I take Miles and Bryson’s definition of policy as “a set of decisions that societies, through their governments, make about what they do and do not want to permit and what they do or do not want to encourage”.They argue a particular technology does not need to be fully mature to have its policy guidelines developed and implemented. These policies can be drafted in the early stages of developing the technology. However, is this approach universal across all economies?
African context and culture
Africa is home to about 1.2 billion people of which 226 million are youth with an average age of 19 years according to the United Nations Development Programme (UNDP). In terms of landmass, it can fit the USA or China and India with more room to spare. The continent is however not a single country, it has more than 50 democracies with people who speak different languages that include Arabic, English, French, and Portuguese. African culture, especially in Sub-Saharan Africa, differs from that of the West.
In the next five years we will witness a shift in artificial intelligence (AI) within Africa, specifically around policy issues
Technology development of whatever kind should not disregard placing humanity at its core. It is in the nature of the African people to want to help. From a cultural standpoint, this could be partly the reason why remittances and mobile payments are successful in Africa. Although this narrative is ideal, I think there is a greater need to understand how this fabric of communal love is changing. Otherwise we will run into the danger of pouring new wine into old wine skins. And thus, exposing the risk of incompatibility because the technology is trying to identify cultural trends that are no longer in existence.
AI and its applications in Africa
In Africa major developments in AI will be centered on solving real-world problems affecting ordinary people’s lives. These will include policies that favor advancement of AI talent, support operations in industries like telecommunications, encourage research in health and agriculture, guide data collection and protection, and lastly address issues of online misinformation. The majority of these will be AI relevant policies followed by indirect AI policies. Where AI-relevant policies are those that do not directly target AI development, their existence has an effect on progress in AI such as education. While indirect policies, like data protection or regulation, indirectly affect AI development.
It is possible progress in AI in Africa could be led by the private sector
I foresee most of the policies will emerge out of interactions between stakeholders (international AI labs, researchers, and investors) and government institutions with aligned interests. African governments with immature AI strategies are likely to play the role of regulation and authorization of AI development. It is possible progress in AI in Africa could be led by the private sector due to lack of funding and a limited AI-skilled workforce in most government institutions.
Leading AI companies, like Google and Facebook, are moving at a much faster pace in AI development than most African governments are. In addition, they have the resources to push for advancements. These companies will be a part of the policy formulation process with other stakeholders. However, if this is the path taken then we ought to think about how AI is going to be governed and regulated. In order to do this better, there is a need to have a clear understanding of different AI categories, like AGI (artificial general intelligence), and how this differs from AI in general or superintelligence. There will be a need for regulation and oversight in order to avoid misuse.
To the best of my knowledge, there is no well-documented strategy for AI in Africa as there is in Europe, Canada, the U.S., and China. In my experience, these strategies are nationalistically mission driven with achievable goals like growth of a competitive AI workforce, AI weaponry dominance, and improving AI’s industrial capacity. I do not think Africa is likely to have a single AI strategy.
“I do not think Africa is likely to have a single AI strategy”
In the case of Nigeria there is the National Agency for Research in Robotics and Artificial Intelligence (NARRAI), whose focus is to train Nigerians to use skills in AI to quicken the country’s economic growth. But does this approach account as strategy? AI has the ability to change the way of life, even in Africa, and already is. Therefore African leaders need to develop and deploy national AI strategies that have long-term outcomes. Different countries could benefit from the interactions organized by Transform Africa and formulate their own strategies.
The data ecosystem
Large volumes of data are crucial in training AI systems. In Africa, telecommunications service providers and government institutions are some of the biggest data custodians on the continent. This means governments have to formulate favorable policies that avail enough data for research and innovation. Or they at least need to seek out collaborations that encourage collections of data using autonomous systems. For example, Inmarsat signed a memorandum of understanding (MOU) with Smart Africa (a consortium of 22 countries). The MOU is meant to provide supportive infrastructure for Internet of Things (IoT) using Inmarsat’s LoRaWAN network.
Kigali, Rwanda’s capital city, is to be the flagship smart city and a model for all other African countries. Once in place, the network will ease collection of sensor data. In addition, Kenya launched an open-data initiative that wanted to make government datasets available for free and create accountability. Such initiatives geared toward enabling autonomous data collection and data availability systems are key to AI’s progress in Africa. Also, there is a need to have mechanisms in place that ensure data is correct and accurate. In addition, data protection and regulations are needed in order to avoid misuse. Governments must understand that a lack of data can severely hurt AI development.
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