Classroom I was new to teaching at the college level when the world stopped. After spring break in 2020, the entire country (and most of the world) went into lockdown, and I experienced the educational transformation firsthand as both a student and an educator. It took less than a year for Microsoft Teams to become the digital classroom. In the shock of the global pandemic, no one dared to question this overnight catapult into digital space. The Teams classroom was the first shift, followed by the transition to the asynchronous environment, with no virtual meetings, no real-time chats, just video lectures and digital assignments. These were the quiet antecedents of the AI moment in which we find ourselves immersed today, yet no one talks about them when discussing AI in education. For the past two years, I have been grappling with what I call the Three-Body Problem. I use this metaphor as a reference to the chaotic and unpredictable nature of a universe governed by three competing forces. In education, these forces are the human (students and teachers), the machine, and the institution. While other scholars speak of wicked problems (Corbin et al., 2025) to describe the irresolvable quality of AI or the black box (Pasquale, 2015) to describe the opacity of knowledge production, the Three-Body metaphor captures the constant, shifting tension of these forces pulling against one another. In this system, there is no correct solution, only the continuous effort to maintain a stable orbit. The moment I decided to confront this problem happened while I was grading students in one of my asynchronous Art Appreciation courses in 2025. I began finding responses that were clearly AI- generated, but one stripped away all doubt. A weekly journal submission from a student read: “In the lecture, the teacher gave many good examples. One artwork that stood out to me was [insert example, such as ‘a painting made with sand and paper’ or ‘a sculpture using metal and wood’].” This was unacceptable. Throughout that summer, I found similar AI-generated responses from several students. I simply could not handle it anymore. There was something fundamentally wrong, not only with my students but with my assignments and the use of AI itself. I realized that traditional essays, journals, and other written assignments were no longer viable vessels for assessment. I started questioning everything about the usage of AI in the classroom. Was it that the student was simply throwing ideas and asking AI to organize them in a coherent format? Was it that the student shared the entire lecture with AI and attached the assignment, only for AI to return this result? Was it that the students simply lacked the English vocabulary or grammar to write a journal entry and were using AI as a language assistant or proofreading tool? For more than fifty percent of my students in the art appreciation classroom, English is not their first language. Some of them have not even been in this country for a year, and the language barrier is a significant issue. I did not have the answers to those questions, but three things were certain: the student was using AI to complete this task, the assignment was not designed for this context, and finally, the student did not take the time to read what AI returned before making a final submission. However, student usage is only one string stretching the AI problem. The second force is the institution. For the past year, we have seen a massive increase in webinars and workshops pushing faculty to embrace AI to provide enhanced feedback or to redesign courses. The incentives are everywhere, including professional development credits, fellowships, and research publications. We are told to integrate these tools, yet we are simultaneously cautioned that AI detection software is unreliable. We are given a continuous, open invitation to use a tool we never asked for, with no clear map of how to do it. 44 TRENDS 2026 PAGE
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