“Generative AI” and Writing in Higher Education: Editor's Introduction

Abstract This editor's introduction provides an overview of the interdisciplinary goals for an ongoing series in Critical AI devoted to the topic of “Generative AI” and writing in higher education. It also presents and develops several critical assumptions about the relationship between conflicting goals of higher education and generative AI technologies. Such technologies were designed to help experts work more efficiently, not to train novices and students to develop expertise. Prompt “engineering” should be understood as writing, not engineering, prompts with rhetorical awareness. And so-called training data for LLMs should be recognized for what it is: human expertise captured in writing. Sharing novel research about LLMs and writing—in relation to the history of writing technologies and drawing on expertise in (teaching) writing across disciplines, including from the Writing Across the Curriculum movement—can help higher education challenge the devaluation of writing and fundamental misunderstandings of writing instruction and thus help faculty and students adapt to the omnipresence of generative technologies without ceding control of the educational enterprise to tech companies. Last, the introduction briefly summarizes articles in the issue by Matthew Halm, analyzing the politics of prompt engineering, and by Emily Hall, situating the rapid adoption of “generative” technologies by universities in relation to larger trends in student surveillance.