Artificial Intelligence and Post-Hierarchical Leadership in Higher Education: Responsibility, Reflection, and Ethical and Epistemic Learnings
Abstract
This article proposes a conceptual model of post-hierarchical leadership for higher education in the era of generative artificial intelligence (GenAI). As GenAI transforms the processes of knowledge production, distribution, and validation, it becomes urgent to rethink leadership not as positional authority but as ethical and epistemic responsibility. GenAI, understood as an agent of socio-technical framing, reorganizes the conditions under which knowledge is recognized, posing ethical and cognitive challenges for academic institutions. In response, the Leadership Tree Model (LTM) is integrated, offering an ecological and regenerative vision of leadership as a living system based on interdependence, reflection, and continuous learning. By combining the logic of the epistemic frame with the ecological paradigm of LTM, a leadership practice focused on the responsible management of knowledge is proposed, where humans and artificial intelligence co-govern the flows of meaning.
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