Where and How Far Could Artificial Intelligence Take Africa?
By Amrote Abdella
With access to high-quality broadband and cloud computing continuing to spread, organizations are recognizing artificial intelligence's (AI) ability to help with some of the continent's most pervasive problems, from reducing poverty to improving healthcare and enhancing crop yields to feed a growing population. To achieve an AI-enabled future in Africa, forward-thinking policymakers, innovative startups, technology partners, civil society groups and stakeholders all need to work together to promote a vibrant AI ecosystem in Africa - one that enables inclusive growth and provides a clear and trusted path to digital transformation writes Amrote Abdella for CIO East Africa.
The impact of artificial intelligence (AI) dominated discussions at this year’s World Economic Forum in Davos – with delegates touching on everything from ethics to democratization and workforce re-skilling.
While AI is primed to be the driving force of the Fourth Industrial Revolution, its widespread acceptance and adoption among businesses is still in early stages. 2018 was an important year in shifting current perceptions around AI, demonstrating it as a technology that is augmenting human capabilities, not replacing them, and benefiting the speed and scale of any organization, large or small.
Across the Middle East and Africa, a projected $28.3 million will be spent on developing AI solutions in the financial sector - and organizations are ramping up efforts to ensure young developers are well equipped for the task. At the recent AI Bootcamp, hosted by Data Science Nigeria and sponsored by Microsoft, for example, local developers were upskilled in using deep learning concepts to drive financial inclusion.
Developing this kind of AI capacity in Africa is essential, not only to ensure our 200 million-strong youth population is equipped for jobs of the future but also to ensure local AI systems themselves are unbiased and inclusive.
Developing the right skills and data sets
Without the skills to build homegrown applications, organizations are likely to import machine-learning algorithms developed elsewhere, which are trained on biased data sets that lack local context. This could have severe consequences in industries like healthcare.
What Africa needs is a richer pool of local data, coupled with AI applications that are built by skilled local teams with diverse demographic, gender, ethnic and socio-economic backgrounds. To achieve this, outdated processes need to be digitized, education systems need to adapt quickly, and digital literacy programmes need to be more far-reaching.
Local organizations are making good headway. The Centre for Proteomic and Genomic Research (CPGR) in South Africa recently collaborated with Microsoft to build a first-for-Africa technology platform on Azure, which is enhancing the storage and processing of African genomic datasets. With this data and computing power, the CPGR is running more ground-breaking biomedical research in local disease development and prevention.