Data Privacy and Ethics in AI-Driven Applications in Nigeria: A Review

Abstract

Nigeria’s rapid adoption of AI across fintech, telecoms, health, and public services promise faster delivery, wider inclusion, and operational efficiency. Yet the same surge magnifies real-world harms when data practices, model governance, and security controls are weak. This review argues that Nigeria’s legal and institutional footing has improved through the Nigeria Data Protection Act (NDPA) 2023 and the establishment of the Nigeria Data Protection Commission (NDPC), but risks persist where “paper compliance” substitutes for end-to-end lifecycle implementation. Key gaps include excessive data collection, opaque data sharing, weak vendor accountability, insecure data/model pipelines, and high-stakes automated decisions with limited transparency or redress. We synthesize safeguards for high-risk deployments credit scoring, biometric identification, clinical decision support, and law-enforcement analytics emphasizing lawful-basis discipline, minimization and retention limits, encryption and access control, documentation of models and datasets, fairness testing, continuous monitoring, and meaningful human oversight with appeal pathways. Finally, we propose a staged, resource-aware roadmap: baseline data mapping and DPIAs, security and contracting hardening, then institutionalized audits, ethics review, and sectoral codes. Trustworthy AI in Nigeria depends on accountable governance, not ambition alone. Keywords: Nigeria; AI ethics; privacy; NDPA 2023; NDPC; governance; biometric data; fintech; health data; fairness; accountability.