AI Didn’t Break Our Teaching, It Revealed Our Teaching
TL;DR
It is argued that AI did not break teaching, it revealed aspects of teaching that have long required greater attention and intentionality and should be focused on clarifying the purposes of teaching and learning.
Abstract
The rapid emergence of generative artificial intelligence (AI) has prompted widespread concern about academic integrity, student learning, and the future of higher education. While AI is often framed as a disruptive force, this commentary argues that many of the challenges attributed to AI predate the technology itself. Rather than creating new problems, AI has exposed long-standing tensions embedded within higher education and communication pedagogy. Three tensions that have become increasingly visible in the presence of AI are identified: learning versus completion, efficiency versus depth, and human connection versus algorithmic mediation. First, AI challenges assumptions that the successful completion of assignments necessarily reflects meaningful learning. Second, it highlights the growing emphasis on efficiency within educational systems despite the fact that communication learning often requires reflection, revision, and sustained engagement. Third, AI underscores the relational nature of teaching by revealing the limitations of simulated interaction in comparison to authentic human communication. Communication faculty are uniquely positioned to respond to these tensions because communication education has long emphasized critical thinking, interpersonal engagement, and relational learning. Rather than responding to AI with additional policies, educators should focus on clarifying the purposes of teaching and learning. Ultimately, the article argues that AI did not break teaching, it revealed aspects of teaching that have long required greater attention and intentionality.