The first session centred on whether an AI tutor bot should be introduced. The conversation quickly shifted to different understandings of responsibility and to the roles of lecturers, policymakers and the university. Some participants viewed responsibility as protecting students, while others focused on safeguarding educational quality or felt it meant experimenting with AI to prepare students for the future. Concerns were also raised about dependence on Big Tech and potential inequalities.

The second session explored the use of AI in grading, prompted by a dilemma about high workloads. Lecturers noted that providing feedback is part of their craftsmanship and professional duty but acknowledged that AI could help free up time for direct contact with students. Students emphasised that accurate feedback matters most, and that the absence of feedback can be a bigger issue. The discussion broadened to topics such as the role of feedback in learning, the purpose of writing and how to prepare students for a future that remains uncertain.

Although viewpoints initially seemed opposed, participants often shared similar concerns once they understood each other’s motivations. Facilitators encourage continuing these conversations to explore what good education requires in a context where AI plays an increasingly prominent role.