3.2 Methodology The methodology of this study was guided by the vision to map AI ethical policies and its implication on African innovators and entrepreneurs with a focus on wide and diverse coverage in both rural and urban areas, and inclusivity in the AI innovation ecosystem. The methodology deployed both qualitative and quantitative research methods with the utilization of proprietary vocabulary to discover and extract quality information from the literature and AfriLabs’ enormous datasets of African policymakers, Governments, community service, and public sectors, and also, related stakeholders with a snowballing approach to
have wide and diverse coverage of the data. Throughout the process, iterative methods were used in each stage to review and incorporate missing and new required information and also, examine thoroughly their valuable insights on the challenges, opportunities, and impacts on African innovators and entrepreneurs leading to serve as a resource to inform and provide actionable recommendations that promote excellence in the adoption and use of AI ethical policy leading to the social-economic growth and sustainable development in Africa. The following Figure 2 briefly describes the methods that will be applied towards fulfilling the vision of this project;
Figure 2: Description of Methodology for Mapping AI Ethical Policy in Africa.
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Initial Preparation
Data Reporting and Dissemination
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Secondary Data Collection
Report data using tools such as PowerBI and Tableau & Data dissemination to AI-based AfriLabs Network, & African and Global AI Conferences and Journals.
Iterative
Primary Data Collection
Data Analysis and Synthesis
Engage African Al Stakeholders through the use of Key Informant Interviews (KIls), Focus Group Discussion (FDGs), Case Studies, Startups and Hubs Referral, Surveys and WebinarSessions.
Conduct qualitative and quantitative analysis using tools such as PowerBI, Python, and DAX to analyse and synthesize the clean collected data.
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Data Cleaning and Annotation
Data cleaning and annotation through the use of tools such as Python and Excel.
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Ethical Horizons - Mapping AI Policy in Africa May, 2024
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