Ethical Issues in Artificial Intelligence Adoption in African Higher Education Institutions in Nigeria

Abstract

Purpose: The aim of the study was to investigate the ethical issues in artificial intelligence adoption in African higher education institutions. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Ethical concerns surrounding the adoption of Artificial Intelligence (AI) in African higher education institutions reveal key findings from recent studies. These include issues of data privacy, transparency in AI algorithms, and ethical implications in decision-making processes. Universities in Africa implementing AI technologies must navigate challenges such as ensuring ethical data handling and maintaining transparency in AI systems. Unique Contribution to Theory, Practice and Policy: Ethical frameworks in AI adoption, critical theory & ethics of care may be used to anchor future studies on the ethical issues in artificial intelligence adoption in African higher education institutions. Embed ethics education into AI courses and training programs across African universities. Equip students, educators, and AI developers with the knowledge and skills to identify, analyze, and address ethical dilemmas associated with AI technologies. Develop and enforce clear, context-specific AI ethics policies and regulatory frameworks at national and institutional levels. These policies should outline guidelines for data management, algorithmic transparency, and ethical review processes.