Abstract

1O.B. Okuwa and 2O.J. Akintande
1Nigerian Institute of Social and Economics Research, Ibadan, Oyo state, Nigeria.
2Computational Statistical Unit, Department of Statistics, University of Ibadan, Oyo state, Nigeria.

Abstract
Data plays a crucial role in development planning of any nation. The dearth, sparsity and inaccessibility of data in African nations have created huge gaps in the development process and human capital development of these countries. Lack of data harmony from various data-generating institutions complicated the problem leading to the inconsistent repository of data for planning purposes and human capital development. Consequently, there is need to integrate and harmonized available data using rigorous models that will address major development challenges – such as unemployment, uncoordinated commerce, high inflation, societal unrest, insecurity/terrorism, natural disasters, infrastructural deficiencies, brain drain, maternal and child mortality, literacy and life expectancy issues in Africa region. Africa is endowed with great human resources that can drive structural transformation; however, these huge human resources and its potentials have not been fully tapped and explore due to lack of harmony in data coordination and collaborations. Countries like China and India have explored their human capital resources to drive economic growth and development in the last few decades, setting them on the path of structural and economic transformation among global economic powerhouses. This paper explores the potential of Artificial intelligence and Machine learning in harmonizing the gaps in data coordination in Africa. The paper also explores how modern tools can be harnessed to promote formidable multidisciplinary collaboration within and among nations in Africa. Thus, the study systematically explores how AI/ML can help African nations achieve human capital development by creating a likely correlation of variables derived from the developed nations. And using AI/ML to measure the key drivers of human capital development across these powerhouses - to promote data-driven policy modelling in Africa and Nigeria.