My personal relationship with AI is deeply rooted in tension, guilt, and the structural realities of teaching. My instinctive reaction toward AI is one of avoidance and disgust because I value learning as a deeply human process grounded in discussion, reflection, struggle, and relationship building. Still, my relationship with AI emerged from the material conditions of my teaching practice. During my first year of teaching (this year), I entered the classroom with no prior experience, no instructional coach, no curriculum, and no time. I was responsible for managing two grades, multiple subjects, and intervention responsibilities simultaneously. In one class alone, I had ten students with IEPs and no idea how to meaningfully accommodate and support them. At the same time, I was also in graduate school working toward both my teaching certification and my master's degree. Within these conditions, AI became less of a choice and more of a tool for survival.
The guilt I feel surrounding AI seems sociologically significant because it reflects a tendency to individualize responsibility for structural problems. Rather than recognizing the institutional conditions that created unsustainable demands, I found myself internalizing the pressure and viewing my use of AI as a personal deficiency. I questioned whether relying on AI meant I was taking shortcuts or somehow failing to embody the ideal image of a competent teacher. I felt as though I should know what to do and how to do it at all times, in every facet of the classroom.
The guilt also feels connected to broader expectations embedded within educational culture. Teaching often exists within a form of grind culture that normalizes overwork and self-sacrifice, where exhaustion becomes interpreted as commitment and burnout becomes invisible labor that is simply assumed of teachers. Under these conditions, asking for support or relying on tools can feel like a personal weakness rather than a response to structural strain. Yet this framing obscures broader realities surrounding educational labor and the increasing expectations placed on teachers. In many ways, my experience mirrors Gallant and Rettinger's argument that behavior should be understood through contexts and systems that shape it rather than through simplistic moral judgements (Gallant & Rettinger, 2013). This work pushed me to think beyond whether an action is inherently right or wrong and instead examine the conditions that make certain choices appear necessary.
At the same time, part of my discomfort with AI stems from recognizing its potentially harmful consequences. I view education as a form of liberation and empowerment rather than simply a process of delivering information. I believe education should equip students with the ability to question systems, develop literacy, think critically, and analyze the social forces shaping their lives. These are not simple academic skills; they are skills I view as imperative for participation, agency, and survival within society. Because of this, I worry about the ways AI may encourage efficacy over depth, instant answers over productive struggle, and productivity over meaningful learning. I worry about students becoming increasingly disconnected from very difficult, but very necessary process of developing their own voices, constructing arguments, and grappling with complexity. I also worry about broader social implications: whose knowledge is privileged within AI systems, whose perspectives become marginalized, and who ultimately benefits from growing dependent on these technologies.
Despite these concerns, I have relied on AI this year. This contradiction feels uncomfortable, but is important to acknowledge. Ferlazzo's argument resonates with me because he positions AI as a support tool rather than a replacement for educators (Ferlazzo, 2025). For me, AI did not replace teaching, but it did reduce many of the still overwhelming administrative and planning burdens that threatened to make my first year of teaching unsustainable. AI helped me generate differentiated resources, think through accommodations, and organize materials in ways that I otherwise struggled to while trying to stay afloat. It helped me to preserve energy for the most challenging parts of teaching that also felt the most human: relationships, discussion, student regulation, and student connection.
My relationship with AI feels defined by ongoing negotiation rather than certainty. I find myself caught between critique and dependence. I recognize the potential harms and remain uneasy about the broader implications of AI, yet I also recognize that under my current conditions of teaching, stepping away from it can feel unrealistic. Rather than asking whether AI is inherently good or bad, I find myself asking what social conditions make reliance on AI feel necessary and what that dependence reveals about the systems in which we live and work.
References
Ferlazzo, L. (2025, June 18). AI can save teachers time and stress. Here’s how. Education Week.
Gallant, T. B., & Rettinger, D. A. (2025). The opposite of cheating: Teaching for integrity in the age of AI. University of Oklahoma Press.
