A High-Level Structured Methodology for Development of AI Systems in Africa

Evans Ejike Woherem; Joshua Kayode Odeyemi

doi:doi:10.11648/j.iotcc.20241203.11

Methodology Article |

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A High-Level Structured Methodology for Development of AI Systems in Africa

Evans Ejike Woherem^*, Joshua Kayode Odeyemi

Published in Internet of Things and Cloud Computing (Volume 12, Issue 3)

Received: 15 July 2024 Accepted: 20 August 2024 Published: 30 August 2024

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Abstract

AI is a potential game changer for Africa to address the specific challenges she faces in sectors like healthcare, climate change and water-related issues. However, the regulation of AI is still largely underdeveloped in Africa with some existing policies and frameworks still being young. Therefore, as the adoption of AI systems spreads across Africa, so does the need for a structured methodology to guide organizations in either developing new AI systems or onboarding existing ones while maintaining the quality and ethicality of these systems. This paper aims to develop a holistic methodology that provides comprehensive guidance to companies considering to develop new AI systems or onboard existing systems. The goal is to support the development and deployment of AI systems tailored to the specific needs of Africa. The proposed methodology employs a lifecycle approach that integrates both Agile and Waterfall frameworks. By combining the adaptive flexibility of Agile with the structured progression of Waterfall, this methodology ensures adaptability and thoroughness throughout the AI system's development and implementation phases. The integration of these methodologies offers a robust, adaptable framework that can be tailored to the unique demands of AI projects in Africa, from design to implementation, deployment as well as maintenance phases, thereby maximizing the potential impact of AI technologies in the region.

Published in	Internet of Things and Cloud Computing (Volume 12, Issue 3)
DOI	10.11648/j.iotcc.20241203.11
Page(s)	40-49
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

AI, AI in Africa, Ethical AI, AI Methodology, Sustainable Development, AI Policy

References

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[5]	Gunning, D., & Aha, D. (2019). DARPA’s explainable artificial intelligence (XAI) program. AI magazine, 40(2), 44-58. https://doi.org/10.1609/aimag.v40i2.2850
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[7]	Khan Mohammad Habibullah, Gregory Gay, and Jennifer Horkoff. 2023. Non-functional requirements for machine learning: an exploration of system scope and interest. In Proceedings of the 1st Workshop on Software Engineering for Responsible AI (SE4RAI '22). Association for Computing Machinery, New York, NY, USA, 29–36. https://doi.org/10.1145/3526073.3527589
[8]	Konidena, B. K.., Malaiyappan, J. N. A., & Tadimarri, A. (2024). Ethical Considerations in the Development and Deployment of AI Systems. European Journal of Technology, 8(2), 41–53. https://doi.org/10.47672/ejt.1890
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APA Style

Woherem, E. E., Odeyemi, J. K. (2024). A High-Level Structured Methodology for Development of AI Systems in Africa. Internet of Things and Cloud Computing, 12(3), 40-49. https://doi.org/10.11648/j.iotcc.20241203.11

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ACS Style

Woherem, E. E.; Odeyemi, J. K. A High-Level Structured Methodology for Development of AI Systems in Africa. Internet Things Cloud Comput. 2024, 12(3), 40-49. doi: 10.11648/j.iotcc.20241203.11

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AMA Style

Woherem EE, Odeyemi JK. A High-Level Structured Methodology for Development of AI Systems in Africa. Internet Things Cloud Comput. 2024;12(3):40-49. doi: 10.11648/j.iotcc.20241203.11

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@article{10.11648/j.iotcc.20241203.11,
  author = {Evans Ejike Woherem and Joshua Kayode Odeyemi},
  title = {A High-Level Structured Methodology for Development of AI Systems in Africa
},
  journal = {Internet of Things and Cloud Computing},
  volume = {12},
  number = {3},
  pages = {40-49},
  doi = {10.11648/j.iotcc.20241203.11},
  url = {https://doi.org/10.11648/j.iotcc.20241203.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.iotcc.20241203.11},
  abstract = {AI is a potential game changer for Africa to address the specific challenges she faces in sectors like healthcare, climate change and water-related issues. However, the regulation of AI is still largely underdeveloped in Africa with some existing policies and frameworks still being young. Therefore, as the adoption of AI systems spreads across Africa, so does the need for a structured methodology to guide organizations in either developing new AI systems or onboarding existing ones while maintaining the quality and ethicality of these systems. This paper aims to develop a holistic methodology that provides comprehensive guidance to companies considering to develop new AI systems or onboard existing systems. The goal is to support the development and deployment of AI systems tailored to the specific needs of Africa. The proposed methodology employs a lifecycle approach that integrates both Agile and Waterfall frameworks. By combining the adaptive flexibility of Agile with the structured progression of Waterfall, this methodology ensures adaptability and thoroughness throughout the AI system's development and implementation phases. The integration of these methodologies offers a robust, adaptable framework that can be tailored to the unique demands of AI projects in Africa, from design to implementation, deployment as well as maintenance phases, thereby maximizing the potential impact of AI technologies in the region.
},
 year = {2024}
}

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TY  - JOUR
T1  - A High-Level Structured Methodology for Development of AI Systems in Africa

AU  - Evans Ejike Woherem
AU  - Joshua Kayode Odeyemi
Y1  - 2024/08/30
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AB  - AI is a potential game changer for Africa to address the specific challenges she faces in sectors like healthcare, climate change and water-related issues. However, the regulation of AI is still largely underdeveloped in Africa with some existing policies and frameworks still being young. Therefore, as the adoption of AI systems spreads across Africa, so does the need for a structured methodology to guide organizations in either developing new AI systems or onboarding existing ones while maintaining the quality and ethicality of these systems. This paper aims to develop a holistic methodology that provides comprehensive guidance to companies considering to develop new AI systems or onboard existing systems. The goal is to support the development and deployment of AI systems tailored to the specific needs of Africa. The proposed methodology employs a lifecycle approach that integrates both Agile and Waterfall frameworks. By combining the adaptive flexibility of Agile with the structured progression of Waterfall, this methodology ensures adaptability and thoroughness throughout the AI system's development and implementation phases. The integration of these methodologies offers a robust, adaptable framework that can be tailored to the unique demands of AI projects in Africa, from design to implementation, deployment as well as maintenance phases, thereby maximizing the potential impact of AI technologies in the region.

VL  - 12
IS  - 3
ER  -

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Author Information

Evans Ejike Woherem

Digital Africa Global Consult, Abuja, Nigeria

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Joshua Kayode Odeyemi

Department of Mathematics, University of Abuja, Abuja, Nigeria

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Plain Text BibTeX RIS

APA Style

Woherem, E. E., Odeyemi, J. K. (2024). A High-Level Structured Methodology for Development of AI Systems in Africa. Internet of Things and Cloud Computing, 12(3), 40-49. https://doi.org/10.11648/j.iotcc.20241203.11

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ACS Style

Woherem, E. E.; Odeyemi, J. K. A High-Level Structured Methodology for Development of AI Systems in Africa. Internet Things Cloud Comput. 2024, 12(3), 40-49. doi: 10.11648/j.iotcc.20241203.11

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AMA Style

Woherem EE, Odeyemi JK. A High-Level Structured Methodology for Development of AI Systems in Africa. Internet Things Cloud Comput. 2024;12(3):40-49. doi: 10.11648/j.iotcc.20241203.11

Copy | Download

@article{10.11648/j.iotcc.20241203.11,
  author = {Evans Ejike Woherem and Joshua Kayode Odeyemi},
  title = {A High-Level Structured Methodology for Development of AI Systems in Africa
},
  journal = {Internet of Things and Cloud Computing},
  volume = {12},
  number = {3},
  pages = {40-49},
  doi = {10.11648/j.iotcc.20241203.11},
  url = {https://doi.org/10.11648/j.iotcc.20241203.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.iotcc.20241203.11},
  abstract = {AI is a potential game changer for Africa to address the specific challenges she faces in sectors like healthcare, climate change and water-related issues. However, the regulation of AI is still largely underdeveloped in Africa with some existing policies and frameworks still being young. Therefore, as the adoption of AI systems spreads across Africa, so does the need for a structured methodology to guide organizations in either developing new AI systems or onboarding existing ones while maintaining the quality and ethicality of these systems. This paper aims to develop a holistic methodology that provides comprehensive guidance to companies considering to develop new AI systems or onboard existing systems. The goal is to support the development and deployment of AI systems tailored to the specific needs of Africa. The proposed methodology employs a lifecycle approach that integrates both Agile and Waterfall frameworks. By combining the adaptive flexibility of Agile with the structured progression of Waterfall, this methodology ensures adaptability and thoroughness throughout the AI system's development and implementation phases. The integration of these methodologies offers a robust, adaptable framework that can be tailored to the unique demands of AI projects in Africa, from design to implementation, deployment as well as maintenance phases, thereby maximizing the potential impact of AI technologies in the region.
},
 year = {2024}
}

Copy | Download

TY  - JOUR
T1  - A High-Level Structured Methodology for Development of AI Systems in Africa

AU  - Evans Ejike Woherem
AU  - Joshua Kayode Odeyemi
Y1  - 2024/08/30
PY  - 2024
N1  - https://doi.org/10.11648/j.iotcc.20241203.11
DO  - 10.11648/j.iotcc.20241203.11
T2  - Internet of Things and Cloud Computing
JF  - Internet of Things and Cloud Computing
JO  - Internet of Things and Cloud Computing
SP  - 40
EP  - 49
PB  - Science Publishing Group
SN  - 2376-7731
UR  - https://doi.org/10.11648/j.iotcc.20241203.11
AB  - AI is a potential game changer for Africa to address the specific challenges she faces in sectors like healthcare, climate change and water-related issues. However, the regulation of AI is still largely underdeveloped in Africa with some existing policies and frameworks still being young. Therefore, as the adoption of AI systems spreads across Africa, so does the need for a structured methodology to guide organizations in either developing new AI systems or onboarding existing ones while maintaining the quality and ethicality of these systems. This paper aims to develop a holistic methodology that provides comprehensive guidance to companies considering to develop new AI systems or onboard existing systems. The goal is to support the development and deployment of AI systems tailored to the specific needs of Africa. The proposed methodology employs a lifecycle approach that integrates both Agile and Waterfall frameworks. By combining the adaptive flexibility of Agile with the structured progression of Waterfall, this methodology ensures adaptability and thoroughness throughout the AI system's development and implementation phases. The integration of these methodologies offers a robust, adaptable framework that can be tailored to the unique demands of AI projects in Africa, from design to implementation, deployment as well as maintenance phases, thereby maximizing the potential impact of AI technologies in the region.

VL  - 12
IS  - 3
ER  -

Copy | Download