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Case Studies on AI Skills Capacity-building and AI in Workforce Development in Africa

Table of Contents
  • Executive Summary
  • Suggested Citation
Executive Summary #

It is generally accepted that the deployment of AI in Africa will generate new employment opportunities (through new types of jobs), accelerate organisational efficiency (through automated processes and decision-making) and improve public service delivery (through more responsive and personalised attention) in well-prepared settings (Pillay, 2018). However, existing infrastructure and skills gaps inhibit the ability of African countries to leverage the potential of AI, in terms of scientific contributions to AI development, local production of AI-based goods and services, and use of AI to deliver public services. For example, in the context of an already unequal society in which employment opportunities tend to be less readily accessible to people in resource-constrained environments, the efficiency-related benefits of integrating AI into existing systems will also bypass these populations. Furthermore, as is occurring in other parts of the world, the introduction of AI is likely to lead to critical challenges such as misuse or uncritical acceptance of biased automated decision-making (Gwagwa Arthur et al., 2020; Trajtenberg, 2018).

The ability to face these challenges will largely be influenced by the extent to which nations have nurtured an appropriately skilled workforce, not only with technical skills but also with the knowledge and training to govern the deployment of AI. However, in spite of a growing community of Africa-based AI enthusiasts (Snow, 2019), developing a home-grown talent base to execute this vision remains a challenge due to infrastructural and educational system limitations. A recent review of AI capacity in Africa (Butcher et al., 2021) identified numerous capacity challenges including lack of AI experts and lecturers; limited capacity of educational institutions; poor funding for AI research, infrastructure and entrepreneurship; and male dominance in the AI community. Diversity challenges are also evident, especially gender-related but also in terms of other groups such as people with disabilities (Butcher et al., 2021; Centre for Intellectual Property and Information Technology Law, n.d.).

Despite the recognition of a skills gap in Africa, knowledge about the actual state of AI skills across the continent is quite thin, as is knowledge about institutions and initiatives working to fill the gap (apart from a few notably well-publicised programmes such as the African Masters of Machine Intelligence in Rwanda). Few measures of capacity exist, with current tools often depending on proxy indicators (e.g., Government AI Readiness index) or having limited data on Africa (e.g., the AI Index, AI Talent Report). Equally unclear is the extent to which and how AI technology itself is being utilised within programmes aimed at boosting employment or building workforce capacity across economic sectors. The two case studies presented in this report contribute to narrowing the knowledge gap on AI skills capacity building and AI use in workforce development in Africa, especially as it relates to the public sector. 

The Africa AI Accelerator provides a case of AI as an output of capacity-building activities (developing a workforce able to create, deploy and govern AI products and systems), while the Harambee Youth Accelerator is a case study of AI as an input to development agendas (using AI to improve general labour force participation or educational outcomes). The cases address skills and capacity challenges from the perspectives of entrepreneurship and employment – two critical components of most national economic development plans – and formulated with some degree of collaboration between the public and private sector…

To read the rest of the executive summary as well as the entire policy paper, please download it below.

** Research for this policy paper was conducted under the auspices of RIA’s AI4D project supported by the IDRC.

**Download the full paper

Suggested Citation #

Sey, A., & Mudongo, O. (2021). Case Studies on AI Skills Capacity-building and AI in Workforce Development in Africa. Research ICT Africa. https://researchictafrica.net/publication/case-studies-on-ai-skills-capacity-building-and-ai-in-workforce-development-in-africa/

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Updated on 16th Aug 2022
Table of Contents
  • Executive Summary
  • Suggested Citation
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Research ICT Africa, a digital policy, regulation and governance think tank, is a not-for profit organisation under section 21 – REG NO. 2009/017831/08 – PBO NO. 930034057