Ishan, Vats; Tan, Chekfoung; (2025) Exploring Trust Dynamics in Higher Education: A Comprehensive Analysis of Educators’ Perceptions of Students’ Ethical Adoption of Generative AI. In: Proceedings of the 30th UK Academy for Information Systems (UKAIS) International Conference. (pp. pp. 371-395). UKAIS: Newcastle, UK.

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Abstract

Generative Artificial Intelligence (GAI) present both transformative opportunities and complex ethical challenges in the evolving Higher Education (HE) landscape. This research explores the crucial aspect of trust among educators in HE regarding the ethical use of GAI, avital factor for its successful integration into teaching and learning environments. Through a survey research approach, this study combines quantitative and qualitative analysis to assess the levels of trust educators place in students’ ethical use of GAI. The research examines key constructs such as transparency, reliability, accountability, cultural contexts, trust, and ethical alignment through descriptive and thematic analysis. This study explores two interrelated aspects: educator’s trust in students’ ethical use of GAI and educator’s trust in GAI technology itself for teaching practices. The research posits that educator’s trust in GAI may influence their trust in student’s ethical use of the technology. By clarifying these distinct yet connected focuses, the findings reveal that trust is a critical lever in the adoption and effective use of GAI in HE. The research highlights how various dimensions of trust affect educators’ engagement with GAI. These insights pave the way for the development of targeted guidelines aimed at strengthening trust and promoting an ethical framework for GAI in HE.

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