Emerging Digital Technologies Ecosystems in Kenya and South Africa: States of Maturity 2023
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Date
2023-09
Authors
Ogot, Madara
Hanlin, Rebecca
Muthee, Margaret
Mlilo, Wandile
Njunguna, Samuel
Journal Title
Journal ISSN
Volume Title
Publisher
University of Nairobi and University of Johannesburg
Abstract
Data generation is growing exponentially, driven by the rapid increase in devices such as mobile phones, computers, sensors, etc., connected to the Internet and thus to databases. The new data sources and technologies (e.g. machine learning algorithms) "can identify patterns in observed data, build explanatory models, and make predictions quicker and with more accuracy than humans". Emerging digital technologies (EDT) and X-Data-based applications, for example, have been used to develop mitigation measures against Malaria, Zika, and Dengue Fever in India, identify lower-priced generic drugs in South Africa (SA) and tackle flooding in Indonesia. However, these algorithms are mainly created in developed countries and often lack transparency arising from intellectual property rights, thus hindering the realisation of the enormous potential EDT/X- Data-based applications have in addressing socio-economic challenges faced by developing countries, where data literacy levels are also often insufficient to leverage on data-driven approaches fully. In addition, where applications do exist, they are often not broadly accessible, especially for vulnerable and marginalised groups and persons with disabilities in areas with slow internet connections.
This study unpacks the generic term "big data" into four overlapping categories of data: big data, open data, user-generated data and real-time data, and collectively refers to them as "X-Data". Reaping the full benefits of X-Data requires the development of supportive systems, including more approaches to collect, aggregate, analyse, and visualise data, as well as building the capacity of communities involved in data generation, governance, and usage. Such systems are often limited or absent in developing countries, thus creating new digital divides between developing and developed countries. Whereas the access to technology gap is narrowing, gaps in social integration and the impact of technology are increasing. Further, barriers persist in the use and uptake of X-Data by decision-makers, including competing data sources, quality of data, limited awareness of data existence, and inadequate transformation of data into useful information or tailoring it to match decision-makers needs.
EDTs are often used together and include artificial intelligence (AI), blockchain, Geographic Information Systems (GIS), Internet of Things (IoT), and big data analytics. AI includes systems, techniques and methods that incorporate human-level intelligence at much faster speeds, for example, data mining (including artificial neural networks, Bayesian networks and support vector machines), machine learning, natural language processing, computer vision, and expert systems. Collectively, they provide enhanced data analytics, better decision-making, and improved predictive analysis.
Kenya and South Africa have for the past few years ranked high in Sub-Saharan Africa (Kenya: 4/41 in 2020 and 3/41 in 2021 and 2022; and South Africa: 2/41 in 2020, 2021 and 2022) and reasonably well globally (Kenya: 71/172 in 2020, 78/160 in 2021 and 90/181 2022; and South Africa: 58/172 in 2020, 68/160 in 2021 and 68/181 in 2022) on the Government AI Readiness Index. The index evaluates how ready a government is to implement AI in delivering public services. However, the Sub-Saharan African countries have the lowest average scores on households with internet access and the cost of the cheapest internet-enabled device relative to Gross Domestic Product (GDP) per capita.
The definition of GIS is a computer system for capturing, storing, checking, and displaying data related to positions on Earth's surface. GIS can show different data types on one map, such as streets, buildings, and vegetation, enabling easier visualisation, analysis, and understanding of patterns and relationships. The hardware and software systems incorporate many data types, including cartographic, photographic and digital data.
Big data combines structured, semi-structured and unstructured data collected by organisations. Big data analytics mines this data for information for machine learning projects, predictive modelling, and other advanced analytic applications to create value. Characteristics include great variety, high volume and the need for faster processing times. Blockchains are decentralised databases that permanently, without third parties, record user transactions. The transactions are cryptographically chained (thus cannot be altered) and shared with the linked users.
A definition of IoT is a network of things embedded with sensors, software, and other technologies. They connect and exchange data with other devices and systems through the Internet. Using low-cost computing, the internet cloud, big data analytics and mobile technologies, physical objects (ranging from everyday household appliances to complex industrial applications) can share and collect data with minimal human intervention.
This study took a deep dive into and assessed the maturity level of the EDT ecosystems in Kenya and South Africa, focussing on their applications in the context of X-Data. It builds upon the United Kingdom (UK), Foreign Commonwealth Development Organization (FCDO) – Funded project, Emerging technologies in Kenya and South Africa - A Landscape Analysis.
Description
Keywords
Emerging Digital Technologies, Kenya, South Africa
Citation
M. Ogot, R. Hanlin, M. Muthee, W. Kelly, S. Njunguna, L. Omondi, R. Muriuki (2023), Emerging Digital Technologies Ecosystems in Kenya and South Africa: States of Maturity 2023, University of Nairobi and University of Johannesburg