Ethics and Bias in AI-Driven Education and Security Management in Nigerian Schools

Abstract

Artificial intelligence (AI) is increasingly being introduced into Nigerian schools through educational technologies 
such as: adaptive learning platforms, automated grading, etc. And also through the adoption of certain security 
systems such as (CCTV surveillance, access control, threat-detection analytics). While these applications sought to 
improve learning outcomes and safer school environments, they also raise critical ethical concerns and the risk of 
algorithmic bias – challenges that are particularly acute in the Nigerian context. On this premise, this paper examines 
the historical and emerging use of AI in Nigeria’s education sector, identifies types of algorithmic bias relevant to 
Nigerian schools (data bias, model bias, decision bias), and analyses the ethics of student surveillance and data 
privacy under recent Nigerian data protection laws. The researchers, discussed the cultural, legal, and infrastructural 
challenges of deploying AI ethically in Nigeria, by drawing emphasis with case studies of local initiatives (e.g. 
Nigerian edtech startups, biometric attendance pilots). Finally, the researchers, offered recommendations for 
Nigerian policymakers, school administrators, and AI developers to foster responsible, equitable AI in Nigerian 
educational system and security management. Our analysis is grounded in scholarly research and international 
guidelines, as well as Nigeria-specific examples, to provide a comprehensive, culturally informed perspective.