Africa: Peering Into Africa’s AI Future – a Roadmap for Digitisation – NewsEverything Africa

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Africa: Peering Into Africa’s AI Future – a Roadmap for Digitisation – NewsEverything Africa
Africa: Peering Into Africa’s AI Future – a Roadmap for Digitisation – NewsEverything Africa

Africa can convert its rich cultural, biodiversity, and mineral resources into technological assets. But it must digitise them first.

AI is a ubiquitous topic in today’s news. From revolutionising healthcare to powering the automotive industry, AI technologies hold tremendous potential to enhance the welfare of societies. But as we take a closer look at the data that powers it, a stark reality emerges: this transformative power will not be equitably distributed – particularly when comparing African and Western societies. While AI tech promises to spur innovation and economic growth by redefining how industries operate, it is also creating new forms of inequality and perpetuating historical patterns of labour division in which Africans are relegated to low-skilled and low-wage roles in the global AI value chain.

To have a voice in this revolution, African countries must strategically accelerate their investments in AI-dependent infrastructure. For countries with nascent digital landscapes, this infrastructure may include data centres, servers, and storage systems that house the vast amounts of data that most AI systems require.

Challenges related to risk appetite and red tape continue to hinder private sector investments on the continent, but there has been notable progress in funding for core projects, such as grid electricity and solar energy, which strengthen overall capacity. To ensure that AI systems of the future meet the socioeconomic needs of the people, governments and investors should prioritise data access. How? Improving the digitisation of national records across the continent is an essential first step.

The Data Dilemma

Africa has a cultural richness that has historically been undervalued, misrepresented, or neglected by global mainstream narratives. As AI algorithms learn from data, most depend on large amounts of information. This information is commonly sourced from the US, European countries, and China, all of which have well-established digital infrastructures and vast amounts of digitised national records. In comparison, for a vast majority of African nations, the digitisation of records is still in its infancy.

At its core, digitisation involves converting physical or analogue records – such as books, photographs, and artifacts – into digital formats that can be easily accessed online. But it is more than just a technical issue; it’s also a matter of voice, ethics, and representation. By democratising access to information, digitisation can give local innovators and entrepreneurs a voice in the development of context-relevant, culturally-informed, AI algorithms. Unfortunately, open data initiatives remain scarce on the continent, making it difficult to realise the full potential of AI.

Research from Open Data Barometer reveals that sub-Saharan Africa lags behind other regions when it comes to publishing and using open data for accountability, innovation, and social impact. Only two countries in the region are among the top 50 globally – Kenya at 35 and South Africa at 46 – further highlighting the need for a tailored approach. South Africa and Kenya have made some progress in digitising their records. In South Africa, various organisations have launched initiatives for historical record preservation. Kenya, on the other hand, has been working to digitise its land registry, making it easier for citizens to access information about property ownership. Nigeria is not far behind with its applications in the education sector, and, in 2018, Mauritius became the first on the continent to establish a national AI strategy. Such achievements are the building blocks for the existence of vast databases of information that can be used to develop AI algorithms.

Digitisation: A First Step, not a Silver Bullet

Digital preservation is essential for safeguarding a nation’s cultural legacy, ensuring that historical and linguistic records are captured and easily accessible. Additionally, because narrow AI systems rely on accessible data to function effectively, the digitisation process lays an important foundation by creating the necessary infrastructure.

Digitisation is often hailed as a blanket solution to a range of problems on the continent. On its own, however, digitisation is far from a silver bullet, and we need to be careful about overestimating its potential. For one, the digitisation of archival data by various organisations does not guarantee that this information will be free and open for AI to tap into. Focusing on digitisation can also be impractical in some cases as it can be costly in terms of hardware and software costs, expertise, and sustainability. While higher-income regions race ahead, many African nations are grappling with pressing development issues, making it difficult to prioritise the digitisation of archival data.

Even when there is a will to digitise, the process itself can be fraught with challenges. Digitisation expertise remains thin on the ground, and many governments struggle to build the necessary infrastructure to support the process. But “development” should not be reduced to poverty reduction. In this age of innovation, African policymakers must strategise and push for investment in capacity-building and open data policies to catch up with the rest of the world.

The Bottom Line

As the youngest, and soon to be the most populous region in the world, there are clear incentives for private sector actors to invest in the next generation of African digitisation and AI experts. The reality is that without data, most AI solutions won’t work and algorithms will be ineffective.

Western tech giants have monopolised the collection of existing data, and the exploitative worker treatment resulting from these power imbalances has already made headlines. As companies like the US-based OpenAI continue to expand their presence globally, their effectiveness in Africa should be scrutinised. But with the current reliance on these actors to sustain open data initiatives and provide both technical and financial backing, we cannot shut them out. Successful AI ventures in Africa, like iCog Labs in Ethiopia, prove that global partnerships can work well while upholding high ethical standards. Increased coordination between private sector actors and stewards like AI Expo Africa and Alliance for AI can help solidify global-local partnerships while ensuring accountability.