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Artificial Intelligence in Higher Education: Safety, Reliability, and Risk Management in a Socio-Technical System
Volume 2026, Issue 1 (2026), pp. 1043–1052
Ibraim Didmanidze   Ia Khasaia   Nato Sherozia   Nino Jintcharadze   Nazi Jintcharadze   Aleksadre Bakuridze  

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https://doi.org/10.47459/cndcgs.2026.121
Pub. online: 13 July 2026      Type: Article      Open accessOpen Access

Published
13 July 2026

Abstract

The study conceptualizes artificial intelligence in higher education as a socio-technical system in which human cognition, institutional norms, and algorithmic processes interact. It aims to develop a model of functional differentiation that preserves students’ cognitive responsibility while enabling the safe and effective use of artificial intelligence. The study employs a mixed-methods design combining conceptual analysis with empirical data from student surveys conducted in higher education institutions in Georgia. The findings indicate that artificial intelligence enhances operational efficiency and supports academic tasks; however, its use for content generation is associated with reduced cognitive engagement and risks to knowledge reliability and academic integrity. The study concludes that clear functional boundaries, process-oriented assessment, AI literacy, and institutional governance are essential for responsible integration.

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Keywords
artificial intelligence in higher education socio-technical systems functional differentiation system reliability risk management.

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Generolo Jono Žemaičio Lietuvos karo akademija Šilo g. 5A., LT-10322 Vilnius, el.p: lka@mil.lt

General Jonas Žemaitis Military Academy of Lithuania  Šilo Str. 5A, LT-10322 Vilnius, Lithuania, e-mail: lka@mil.lt

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