Reconfiguring the Supervisor-Student Relationship in the Age of Artificial Intelligence: Challenges, Opportunities, and Governance Paths

Abstract

Generative artificial intelligence is profoundly reshaping the operational logic of postgraduate supervisor-student relationships. As AI becomes embedded in research practices, the traditional dyadic interaction between supervisor and student is transforming into a triadic structure of “supervisor-AI-student,” giving rise to multiple educational predicaments: the epistemic authority of supervisors is progressively diluted; students develop intellectual inertia and their capacity for independent critical thinking deteriorates; and the interpersonal emotional bonds between supervisor and student are steadily weakened. At the same time, however, AI also presents opportunities for reconstruction: automation of routine tasks liberates supervisors’ time for higher-order guidance; data-driven feedback enables precision-tiered mentoring; the traditional master-apprentice model is propelled toward a human-AI collaborative paradigm; and a new, open, and shared supervisory ecosystem begins to take shape. Grounded in the fundamental objective of fostering virtue through education, this paper develops a four-dimensional collaborative governance framework: clarifying the boundaries of AI technological intervention, refining supporting institutional mechanisms and supervisor evaluation systems, simultaneously cultivating AI digital literacy among both supervisors and students, and reconstructing a humanistic supervisory culture and community. The paper argues that the crux of reconfiguring the supervisor-student relationship in the age of AI lies not in technology adoption per se, but in striking a balance between enablement and regulation, adhering to the educational mission and ensuring that technology serves rather than dissolves the core values of the supervisory relationship.