Policy Briefs

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Browsing Policy Briefs by Subject "Emerging Digital Technologies"

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    Enhancing South Africa’s Emerging Digital Technologies’ Innovation Ecosystem
    (2023-09) Hanlin, Rebecca; Mlilo, Wandile
    South Africa is ranked the top innovating mainland country on the African continent in the 2022 Global Innovation Index (GII) (WIPO, 2023). It has the second highest level of funding towards research and development on the continent (currently at 62% behind Kenya at 69% of GDP) (World Bank, 2022), with over 50% of the R&D funds coming from the government as opposed to foreign actors as in many other African countries. The private sector contributes around 23% of R&D spend (DSI, 2023). The country has a vibrant start-up culture and a strong history of support for new market entrants through venture capital. One of the reasons the country ranks so highly in the GII is because it has three of the top ten highest valued venture capital (VC) deals on the continent in 2021. A significant number of VC deals in South Africa in recent years have taken place in the FinTech space. For example, JUMO, a South African-based FinTech firm, raised US$ 120 million in 2021 following a successful round of funding that raised US$ 55 million the year before (Kene-Okafor, 2021). JUMO uses artificial intelligence (AI) to power its ‘banking-as-a-service’ platform. AI is one of a suite of emerging digital technologies (EDTs) that are starting to transform the innovation space on the African continent. Other EDTs include blockchain, geographic information systems (GIS), internet-of-things (IoT), and new-generation data analytics. We term these new data analytics tools collectively as X-data. This encompasses big data, open data, user-generated data, and real-time data. As more and more companies start to embrace these EDTs, the innovation ecosystem or facilitatory environment needs to be ready to support them. This is important if South Africa is to achieve its national development goals and remain a leading economic light on the African continent. This policy brief outlines the results of a study into the status of the EDT innovation ecosystem in South Africa. It is part of a comparative study reviewing the status of the EDT innovation ecosystems in South Africa and Kenya. The policy brief findings are of value to those working in the EDT innovation ecosystem, especially those providing policy support in the areas of education, regulation and finance.
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    Strengthening the Emerging Digital Technologies Ecosystem in Kenya
    (2023-09) Ogot, Madara; Muthee, Margaret; Muriuki, Rita; Njunguna, Samuel
    The rapid increase in devices (mobile phones, computers, sensors, etc.) connected to the Internet (and thus to databases) has resulted in exponential growth in data generation and associated EDTs that can “identify patterns in observed data, build explanatory models, and make predictions quicker and with more accuracy than humans” (Pawelke et al., 2017) EDT/x-data-based applications and algorithms are mainly created in the developed countries and often lack transparency arising from intellectual property rights, thus hindering realization of the enormous potential EDT/x-data- based applications have in addressing socio-economic challenges faced by developing countries, including Kenya. Where applications exist, they are often not broadly accessible, especially for persons with disabilities, areas with slow internet connections or members of underrepresented groups. In this policy brief, the generic term “big data” is unpacked into four overlapping categories of data: big data, open data, user-generated data and real-time data, and are collectively referred to as “x-data”. EDTs are taken to include artificial intelligence (AI), blockchain, geographic information systems (GIS), the Internet of Things (IoT), and big data analytics. These methodologies are often used collectively. Gaps in support systems to develop EDT/x-data-based applications have created new digital divides between developing and developed countries. Further, barriers persist in the use and take-up of x-data by decision-makers, competing data sources, quality of data, limited aware- ness of data existence, and inadequate transformation of data into useful information or tailoring to match the decision-makers needs