Afrocentric Data & Devices

About the video

In this video Jerry John Kponyo, the Principal Investigator and Scientific Director of the Responsible AI Lab (RAIL) in Ghana at KNUST lays out the pressing case and the urgent need for Afrocentric Data & Devices to be created and become the norm.

About the author

Prof. Jerry John Kponyo is the Dean of the Quality Assurance and Planning Office of the Kwame Nkrumah University of Science and Technology (KNUST) under the Vice-Chancellor’s Office. 

He is the former Dean of the Faculty of Electrical and Computer Engineering, KNUST. Prior to becoming Dean of the Faculty of Electrical and Computer Engineering he was Head of Electrical Engineering Department. He is currently the Project Lead of the KNUST Engineering Education Project (KEEP), a 5.5 Million Dollar Africa Center of Excellence (ACE) Impact project sponsored by the World Bank with a focus on Digital Development and Energy. 

He is Co-Founder of the Responsible AI Network (RAIN) Africa, which is a collaborative effort between KNUST and TUM Germany. Between 2016 and 2019 he was a visiting Professor at ESIGELEC, France on a staff mobility programme where he taught postgraduate courses in Business Intelligence and conducted research with staff of ESIGELEC. He has done extensive research in IoT, intelligent systems and AI and currently leads the Emerging Networks and Technologies Research Laboratory at the Faculty of Electrical and Computer Engineering, KNUST which focuses on digital development technologies research. 

Recommended resources


→  Examples of bias in Data, Wrongful convictions: Gross, S.R., Possley, M., Otterbourg, K., Stephens, K., Paredes, J. and O’Brien, B. (2022). Race and Wrongful Convictions in the United States 2022. SSRN Electronic Journal. doi:

Racial disparities in cancer prediction Dankwa-Mullan, I. and Weeraratne, D. (2022). Artificial Intelligence and Machine Learning Technologies in Cancer Care: Addressing Disparities, Bias, and Data Diversity. Cancer Discovery, 12(6), pp.1423–1427. doi:

→  Current situation with existing data, problems with NLP for Africa ‌Ife Adebara and Muhammad Abdul-Mageed (2022). Towards Afrocentric NLP for African Languages: Where We Are and Where We Can Go. doi:

→  Need for adequate cultural and infrastructural representation of Africa Alupo, C.D., Omeiza, D. and Vernon, D. (2022). Realizing the Potential of AI in Africa: It All Turns on Trust. Intelligent Systems, Control and Automation: Science and Engineering, pp.179–192. doi:



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