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As generative AI rapidly enters higher education, it is often celebrated for its capabilities: instant responses, tireless availability, and accelerated productivity. Yet, beneath these conveniences lies a subtler transformation in the temporal dimension of learning. This paper argues that by compressing the time between question and answer, GenAI introduces a new norm of immediacy – an expectation that learning should be instant, seamless, and unambiguous. I examine the pedagogical and emotional costs of this shift, including the marginalization of reflection, incubation, and open-ended inquiry, as well as heightened anxiety, burnout, and compulsive tool use. These changes are situated within broader neoliberal and rationalist logics that prioritize productivity and clarity over depth and uncertainty. Rather than rejecting GenAI, I call for the intentional design of delay, friction, and reflection in AI-mediated learning environments.
Yulu Hou (Mon,) studied this question.
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