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This theoretical paper systematically investigates the impact of artificial intelligence (AI) software on supervisor-graduate student relationships (SGSR) from a socio-technical systems perspective. It proposes the concept of ‘technology acceptance alignment’ across three dimensions—capability, purpose, and pacing—to explain how the match between supervisors and students determines whether AI functions as a ‘relationship optimizer’ or a ‘defect amplifier’. The core mechanism lies in reshaping the dimensions of ‘influence’ and ‘intimacy’ through empowering supervisors, regulating students, setting rules, and mediating interactions. Applying the influence-intimacy typology across eight relationship types, the analysis reveals that under appropriate use, AI helps each type overcome inherent limitations; under misaligned use, it exacerbates existing vulnerabilities. The study proposes a multi-level strategy involving relational contracts, differentiated interventions, and institutional support, emphasizing the principle of ‘prioritizing the relationship while leveraging technology’ to ensure AI serves human development and the academic community.
Zhang et al. (Tue,) studied this question.