This work examines the question of whether it is possible to educate artificial intelligence, focusing primarily on large language models as the currently most advanced and widely used form of generative artificial intelligence. It is based on the enactivist theory of embodied becoming and the autopoietic paradigm of education, which is presented alongside the concept of aligning artificial intelligence. The work is based on conceptual research using a narrative review of the literature, which included sources from the fields of pedagogy, sociology, philosophy, cognitive science and artificial intelligence. In this paper, we present three main findings. Current large language models cannot be educated if we understand education through the dimensions of embodied becoming, language formation, moral judgement and subjectification. The processes of alignment and education are by no means equivalent. The former represents optimisation towards a predetermined goal, whilst the latter is an open-ended, dialogical process of becoming a subject. Nevertheless, the ethical goals of education can inform the design of future artificial intelligence models towards the development of multimodal systems that will be at least partially embodied. The concept of education is inadequate for describing current processes of regulating artificial intelligence and remains tied to the specific conditions of human becoming.
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