The integration of Generative AI in Higher Education raises critical questions regarding its advantages and risks. Recent studies highlight its potential benefits, including fostering self-regulated learning, enabling personalized learning environments, and enhancing student engagement and accessibility (Kong & Yang, 2024; Sharma et al., 2024). Case studies across disciplines—such as language learning, computer science, and mathematics—underscore its positive pedagogical implications (Blake, 2024). However, Generative AI also presents significant limitations, such as its inability to replace the human interaction crucial in fields like social work education (Stone, 2023). Additionally, it introduces ethical concerns, including data privacy, algorithmic bias, and its impact on intellectual critical thinking (Yu et al., 2024).

Biesta’s (2009, 2020) conceptualisation of education’s purposes—qualification, socialization, and subjectification—underscores the importance of fostering autonomy, critical thinking, and ethical decision-making in students. Subjectification, with its focus on the freedom to make informed decisions, presents unique challenges in the context of AI, which excels at mimicking learning tasks but for now it seems to lack the capacity for sound judgment. As Heimans et al. (2023) posit, the widespread adoption of tools like ChatGPT prompts deeper reflection on education’s ultimate purpose: “As students begin to use ChatGPT for their writing, questions will no doubt arise about what they have learnt. But… will ‘what is education for’ become a question more likely to be asked now as a result?”

In this talk we will present the UoG guidelines on Gen AI and we will look into preliminary data through the lens of comparative research on Generative AI in Higher Education. Specifically, the project analyses the perspectives of educators in two contrasting systems: the Italian education system, known for its didactic approach (Mariotti et al., 2019), and the UK system, rooted in a social constructivist model emphasizing active, experience-based learning (Perkins, 1991) and is part of the world wide project: “AI in higher education, training and adult education – an international survey” led by Dr Zan Chen, Institute for Adult Learning, Singapore which involves 18 countries.