LEVERAGING EMERGING TECHNOLOGIES TO IMPROVE SOCIAL PROTECTION DELIVERY IN NIGERIA: A SYSTEMATIC REVIEW

ABSTRACT

This systematic review evaluates how emerging technologies can strengthen Nigeria’s social protection systems, which struggle with exclusion errors, inefficiencies, and data gaps. Analysing 57 studies (2018–2023), it finds machine learning improves poverty targeting (83% accuracy in cases like Jordan) but risks bias in diverse contexts. Blockchain enhances cash transfer transparency (28% fraud reduction), though energy demands challenge scalability. Mobile money cuts costs by 30% but faces rural adoption barriers. Ethical concerns - algorithmic discrimination, privacy risks, and digital exclusion - highlight the need for safeguards. The study recommends: (1) tailoring AI models to Nigeria’s demographics, (2) hybrid blockchain solutions for low-infrastructure areas, and (3) pairing digital tools with literacy programmes. It stresses multidisciplinary collaboration to align technical solutions with socio-economic realities, urging reforms to Nigeria’s National Social Registry. By balancing innovation with inclusive governance, these technologies could advance SDG 1 (No Poverty) while mitigating risks. The findings underscore context-specific adaptation as critical for equitable impact.

Key Words: Emerging technologies, social protection, Nigeria, algorithmic bias, poverty targeting, digital inclusion