article · Interdisciplinary Journal of Critical Communications
Artificial intelligence is increasingly used across Nigerian universities to support teaching, learning, assessment, and administration. However, this rapid deployment creates critical institutional risks, including algorithmic bias, weak data protection, ethical problems, and educational inequity. Adopting artificial intelligence without dedicated human-centred governance threatens to worsen existing structural divides within higher education. To address these vulnerabilities, a conceptual synthesis establishes a layered model known as the Human-Centred AI Governance Framework for Nigerian Higher Education. This structure places students, lecturers, and university communities at its core, supported by four main pillars: equity and inclusion, ethics and transparency, student well-being, and institutional accountability. The framework relies on essential foundations of digital infrastructure, capacity building, and robust data protection, while aligning with broader national and international governance standards to guide institutional practice and policy.
Universities risk compounding social and academic inequalities if automated technologies are deployed without adequate ethical safeguards. Establishing a clear, human-centred governance model helps ensure that educational tools protect student privacy, prevent algorithmic discrimination, and support educational fairness. This approach provides higher education leaders and regulators with structured guidance to manage technological transformation responsibly amid complex infrastructural and regulatory realities.
The abstract outlines a conceptual framework rather than a commercial technology or software product. The governance model could be used by university administrators, higher education regulators, and educational technology vendors to establish compliance standards, procurement criteria, and deployment protocols. As an early-stage conceptual review and policy synthesis, it is positioned far from immediate commercialisation, serving primarily to inform institutional strategy, regulation, and ethical product design.
AI-generated from the published abstract. Always read the original work before citing.
The accelerating uptake of artificial intelligence (AI) across Nigerian higher education promises gains in teaching, learning, assessment, and administration, yet it simultaneously exposes students and institutions to risks of inequity, ethical harm, weak data protection, and algorithmic bias. This conceptual review interrogates how human-centred AI (HCAI) can be understood, framed, and operationalised within Nigerian universities so that technological transformation strengthens rather than undermines fairness, inclusion, and student well-being. Adopting an integrative conceptual-synthesis method, the paper draws together scholarship on HCAI, the ethics of AI in education, algorithmic fairness, and the sociotechnical critique of educational technology, and reads this literature against Nigeria's infrastructural and regulatory realities. The review argues that AI adoption without a deliberate human-centred governance architecture is likely to reproduce and deepen existing educational inequalities. It proposes the Human-Centred AI Governance Framework for Nigerian Higher Education (HCAI-NHE), a layered model that positions students, lecturers, and institutional communities at the centre, supported by four pillars: equity and inclusion, ethics and transparency, student well-being, and institutional accountability, and enabled by digital infrastructure, capacity building, and data-protection foundations, all nested within national and global governance instruments. The paper concludes with recommendations for policy, institutional practice, and future research.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.51986/ijcc-2026.vol1.09
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
