Ethical Implications of Artificial Intelligence in University Education

Abstract

The integration of Artificial Intelligence (AI) in university education has emerged as a transformative force, promising to revolutionize teaching, learning, and administration. However, its rapid adoption has sparked ethical concerns, particularly in resource-constrained settings. This theoretical article examines the ethical implications of specific AI applications, including plagiarism detection tools, adaptive learning systems, and automated grading technologies within Kenyan universities. It highlights three critical areas: data privacy and security, student-lecturer dynamics, and algorithmic bias. Drawing from Kantian deontological ethics, which emphasizes duty and the inherent morality of actions, the article argues for a balanced approach to AI integration that prioritizes ethical responsibilities over mere technological expedience. Data privacy and security remain pivotal concerns, as AI systems amass extensive personal data, often without robust safeguards, exposing students to potential exploitation and breaches. The article explores the intersection of AI and student-lecturer relationships, revealing how AI-driven tools can disrupt traditional mentorship roles central to African pedagogical traditions. Furthermore, the pervasive issue of algorithmic bias is critically analysed, emphasizing its potential to perpetuate educational inequities and marginalize underrepresented groups. The article highlights the absence of localized frameworks to address these ethical dilemmas in Kenyan universities. By anchoring its analysis in Kantian ethics, this article provides a compelling framework for navigating the ethical challenges posed by AI in education, ensuring that its implementation enhances equity, accountability, and human dignity. This work contributes to ongoing discourse on the responsible use of AI in education, offering actionable insights for policy, research, and practice

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