The Current Conversation About Generative AI/LLMs

This section offers a curated overview of the vast public conversation happening around Generative AI/LLMs. Focused on both teaching in general and the teaching of writing specifically (as well as a collection of articles touching on critical issues associated with Generative AI/LLMs technologies), these resources may be informative for you and can also be used with your students as you navigate this technology together.

Generative AI/LLMs and the Teaching of Writing

  • Bruder, Anne. "What ChatGPT Means for How We Teach Writing." Education Week, Janaury 4, 2023.
    Written in the early days of ChatGPT’s arrival in classrooms, this opinion piece lays out how the author has already replaced traditional writing assignments with “thesis-seeking and exploratory assignments that began with students’ curious observations, buzzing questions, and scraps of speculation.” The author does some early speculation about how she might deal with generative AI tools like ChatGPT in service of these assignments.
  • Chow, Andrew R. “ChatGPT May Be Eroding Critical Thinking Skills, According to a New MIT Study.” Time, June 25, 2025.
    An overview of a study that got a lot of attention when it was released as a preprint in 2025. The study found that use of ChatGPT for writing activities was associated with less creative and original writing, less neural activity indicating short- and long-term memory of the final writing product, and, eventually, shifts in writing behaviors, with study subjects over time simply copying-and-pasting ChatGPT output to stand in for their own writing. The results of the study raise questions regarding the use of generative AI tools as part of educational experiences.
    To read the original study (which is a preprint), go to: Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task (PDF).
  • Gero, Katy Ilonka "AI Reveals the Most Human Part of Writing." Wired, December 2, 2022.
    This article was published in the days following ChatGPT’s release in November 2022 but before the public debates around generative AI’s impact on writing and creativity took shape. The author explores how the use of generative AI tools at various stages of the writing process impacts concerns over authenticity, authorship, and intent.
  • Goodlad, Lauren M. E. and Samuel Baker. “Now the Humanities Can Disrupt AI.” Public Books, February 20, 2023.
    This essay provides some background on the history of AI, the way that LLMs are trained and how they work, and the business models of the companies that make these tools, and ultimately argues that humanists “are ideal ‘domain experts’ for the current juncture.” The authors conclude, “The point is not for educators to kill ChatGPT on the mistaken assumption that it obviates the need for humanistic labor, knowledge, and experience. Rather, precisely because it does no such thing, the time has come to cut through the hype, and claim a seat at the table where tech entrepreneurs are already making their pitch for the future.” A wide ranging essay written in the early days after ChatGPT’s release.
  • Laquintano, Tim, Carly Schnitzler, & Annette Vee. An Introduction to Teaching with Text Generation Technologies. WAC Clearinghouse, August 2023.
    A collection of essays that represent “early experiments in pedagogy with generative text technology, including but not limited to AI.” The collection includes 34 undergraduate-level writing assignments.
  • McMurtrie, Beth. "AI and the Future of Undergraduate Writing."
  • O’Rourke, Meghan. “I Teach Creative Writing: This is What AI is Doing to Students.” New York Times, July 18, 2025. 
    A wide-ranging opinion essay on the author’s personal experience using generative AI for various writing tasks, and the concerns this subsequently raised for her as she observed the impact that the use of these tools had on her communications, her connection to her writing, and her sense of self. O’Rourke reflects on what these tools could mean for her students and posits, “That may be, from the humanist’s perspective, the most pernicious thing about A.I.: the way it simulates mastery and brings satisfaction to its user, who feels, at least fleetingly, as if she did the thing that the technology performed.”
  • Peer & AI Review + Reflection (PAIRR) (From the UC Davis University Writing Program)
    Five part curricular intervention that incorporates both peer and AI feedback in the writing process.
  • Sano-Franchini, Jennifer, Megan McIntyre, & Maggie Fernandes. “Refusing GenAI in Writing Studies: A Quickstart Guide.” (Refusal Blog).
    A guide for adopting a pedagogical stance of refusal of generative AI within the writing classroom. The authors write that this is “our effort as rhetoric, composition, and writing studies scholars to make the case for refusal as a disciplinary and principled response to the emergence of generative AI technologies.”
  • Schatten, Jeff. "Will Artificial Intelligence Kill College Writing?" Chronicle of Higher Education, vol. 69, no. 3, Sept. 2022, pp. 40–41.
  • Special double issue (9.1 and 9.2, Spring 2025) from The Peer Review, a fully online, open-access, multimodal scholarly journal that promotes the work of emerging writing center researchers. The articles included in the special issue include best practices for instructors, student perspectives, and tool demos. 

Generative AI/LLMs and Teaching

For guidance put together with the UMass community in mind, visit the Center for Teaching & Learning’s GenAI Resource Collection and the AI at UMass page.

Critical Issues to Consider Regarding Generative AI/LLM Technologies

Critiques of Generative AI/LLM technologies are wide-ranging and touch on many different kinds of social and material impacts. Below we provide resources that can help you get started in learning more about some of these issues. Consider with your colleagues and students: how might these issues factor into our assessments of whether and how we might address and/or use Generative AI/LLMs in our classrooms?

Problems rooted in how LLMs have been trained and developed:

  • Bender, Emily, et al. “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” FAccT, 2021.
    The authors articulate a variety of environmental, social, and linguistic harms that necessarily follow from large language models (LLMs) like ChatGPT. This influential (and infamous!) 2021 paper presaged much of the conversation that’s sprung up since ChatGPT’s release. The authors also propose solutions to the problem of “bigness” in LLMs that they identify.
  • Chiang, Ted. “ChatGPT is a Blurry JPEG of the Web.” The New Yorker, February 9, 2023.
    In this frequently cited essay, the author explores how the way in which ChatGPT was developed has resulted in an “approximation” of the web (and world). The author wonders, “What use is there in having something that rephrases the web?” The author considers what this means for writing with LLMs.
  • Rettberg, Jill Walker. “ChatGPT is Multilingual but Monocultural.” December 6, 2022.
    Published in the weeks directly after ChatGPT’s release, this essay explains what text ChatGPT was trained on and how cultural biases and values have been embedded through that data and further training by the developers. “But,” the author wrote back in 2022, “this won’t last. By playing with ChatGPT, we’re training it to align more with our values. We’re giving OpenAI a vast, human-labelled dataset showing what responses we like and don’t like.” Could serve as a conversation starter regarding the role that users play in shaping emerging technologies.

Generative AI’s environmental impact:

  • Mahoney, Adam. "America’s Digital Demand Threatens Black Communities with More Pollution." Capital B, February 25, 2025.
    This article outlines how the environmental harms associated with growing demands for AI are already disproportionately harming Black communities—the very communities whose jobs are most vulnerable to AI integration. From the article: "Across the country, low-income Black communities face the harshest pollution exposure from these plants, while Black workers are disproportionately in roles most vulnerable to AI and automation. A McKinsey & Company analysis warns that if AI growth continues at its current pace, the wealth gap between Black and white households could widen by $43 billion annually within the next two decades because of disparities in who it serves.”
  • Zewe, Adam. “Explained: Generative AI’s environmental impact.” MIT News, January 17, 2025. 
    A good overview of the environmental impact that increased demand for generative AI technologies is having, particularly on electricity demands and water consumption.

Use of generative AI in technologies used in war/warfare:

Generative AI’s impact on labor:

  • Perrigo, Billy. “Exclusive: OpenAI Used Kenyan Workers on Less Than $2 Per Hour to Make ChatGPT Less Toxic.” Time, January 18, 2023.
    This investigation got a lot of attention in the early days after ChatGPT’s release. The reporting here reveals that the training of LLMs like ChatGPT relies on what many call the exploited and, as the article lays out, traumatizing labor of data workers around the world.
  • Explore the Pew Research Center’s research on the “Future of Work.” 
    These research reports contain great infographics you can use in the classroom to explore what US workers are reporting about whether and how AI is used in their work and their thoughts and feelings about AI and work. This research helps to dispel some myths about widespread adoption and disruption, and provides some more detail around just how and where AI is actually used in the workplace. 

"Teaching Writing in the Age of ChatGPT" was a workshop co-sponsored by the UMass Center for Teaching and Learning, the Writing Program, the Junior Year Writing Program, and the University Writing Committee.

Held in March 2023, it offered a brief overview of how technological interventions have always shaped our approach to writing instruction, and then provided guidance for dealing with the specific perils and promises raised by ChatGPT.

UMass Amherst Writing Program

Since 1982, UMass Amherst’s award-winning writing program has been an independent academic unit serving the entire campus community. 

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