The Higher Education System in the Face of the Generative AI Revolution: A Luhmannian Perspective

Our research examines the evolving role of generative AI, particularly Large Language Models (LLMs) like ChatGPT, in higher education. Rooted in social systems theory, the study investigates how the communicative framework of higher education autopoietically responds to the rise of new technological systems such as generative AI. From a Luhmannian perspective, generative AI can be seen as an environmental irritant that prompts the system to adapt while preserving its internal operational logic. By observing its environment—comprising psychic systems and technological irritations—the higher education system achieves its own self-referentiality. This process includes reconsidering traditional assessment methods, reevaluating academic integrity policies, and shifting the role of educators from content delivery to facilitators of critical thinking and AI literacy.

To support this theoretical background, the research explores the tensions between progressive student adoption of AI and the slower, more cautious responses from traditional academic structures, such as administration and teaching staff. Using qualitative methods and drawing on 30 in-depth interviews with students, teaching staff, and administrators, the research addresses how generative AI, in conjunction with human agency as an irritant, drives academic communication to reshape itself (re-entry).