Praxis: A Writing Center Journal • Vol. 23, No. 4 (2026)

Review of Writing Centers and AI: Generating Early Conversations. Edited by Elisabeth H. Buck and Joshua Botvin, WAC Clearinghouse, 2026.

Mary Hedengren
Brigham Young University
mary.hedengren@gmail.com

Buck, Elisabeth H. and Botvin, Joshua, editors. Writing Centers and AI: Generating Early Conversations. WAC Clearinghouse, 2026. 348 pages, doi: 10.37514/PER-B.2026.2791.

There probably aren’t many Writing Center Professionals (WCPs) who haven’t lost at least a few hours of sleep worrying about the implications of widespread access to Generative AI (GenAI). What will we do if student writers come in with pieces that violate their instructors’ AI policies? Will instructors expect us to police student writing? What if tutors begin to rely on AI for feedback in their consultations? Are our centers in line with our institutions’ expectations? Will anyone see the point in coming to a writing center when there’s an overly friendly chatbot willing to look at writing any time, day or night? Speaking of the middle of the night, is it already 2 am?

With any new technological advancement there are often more questions than answers, but Writing Centers and AI: Generating Early Conversations is a crucial starting point for dialogue. Edited by Elisabeth H. Buck and Joshua Botvin, the collection includes a variety of voices. The anthology represents voices from highly selective institutions like Columbia (Adams and Baker) and Emory (Cheatle) to open-enrollment ones like Utah Valley University (Bell); private institutions (e.g. Velez, Branham, Rea, and Rister) and public (e.g. Hedge and Collins, Hallman Martini); American and Canadian (Friesen and Buettner); women’s colleges (Cleary and Rymer) and HBCUs (Anderson, Bramwell, Omogbadegun, and Yuli). It’s generous that entries in the collection include robust descriptions of their particular institutions’ characteristics to highlight how different they are and also how they all still wrestle with defining a relationship between GenAI and their centers.

If WCPs are perhaps uniquely stressed about AI and their centers, a common thread in Writing Centers and AI: Generating Early Conversations is that we are also uniquely situated to be the ones opening discussions about GenAI in the university. Because writing centers occupy that delicious third space between classrooms and institutions, we can be a hub for generating conversations in our own writing communities.  A number of chapters began by surveying their communities to get a pulse on how students, tutors, instructors, and others are approaching AI (Hallman Martini; Fledderjohann and Perkins; Bleakney, Jablon, and Rosinski; Marcum and Bell; Johnson and Perdue; Velez, Branham, Rea, and Rister), even including questions about AI use in standard intake forms (Cochran, Pilloid and Smith). Other centers even put together events, workshops and forums to openly discuss GenAI on their campuses (Girdharry, Cleary and Rymer). There is so much discussion about the discussion because the topic is so new and there are so many perspectives to sort out.

Individual contributors within the collection vary in their personal approach to using AI. They range in perspective from “AI refusal” in teaching (Botvin) to enlisting GenAI as a “third collaborator” in their process of writing a chapter for this volume (Friesen and Buettner). Ellen Cecil-Lemkin and Lisa Marvel Johnson classify themselves as “techno-optimistic,” recognizing that writers are interdependent, never independent (212-3). Amanda M. May concludes that for herself AI can be both “useful” in some cases and “unethical” in all cases: the best is to be at least “transparent” in where and how AI is being used (191). These personal beliefs in AI use, like many of our most closely held convictions, can come into play in our work within our writing centers.

This collection gives many examples of how writing centers become a touchpoint between student writers and GenAI. Hallman Martini relates the nightmare situation: a tutor includes AI-generated feedback in an asynchronous consultation and the student writer is enraged and insulted. Although, as Hallman Martini points out, “we do not have a 15-week semester” to train consultants in all the nuances of AI-generated writing (84), we can do much to set expectations and teach strategies for using AI in our writing centers. May herself demonstrates how tutors and student writers can benefit from playing with AI-generated writing, creating examples that demonstrate and respond to disciplinary writing (193) or grammatical concepts (194-5). Mason and Dvorak make a twist on “human-in-the-loop” (HITL) approaches to AI use by repositioning the human from an editor or mere stamp of approval to putting the machine in the loop, and giving the human the majority of the agency.  Crull and Stillman pair (or PAIRR: Peer and AI Review and Reflection) tutors with AI to create “triangulation” in the feedback network (242).  Such collaborations allow tutors to model critical appraisal of AI feedback for student writers. We get to set the parameters, create the culture, and train tutors and student writers to work with, alongside, and against AI-generated texts.

In addition to managing our own AI choices as WCPs, we are encouraged in Generating Early Conversations to consider how our expectations may affect others, including employees, students, and the general community. Violini emphasizes that non-LLM AI tools like speech-to-text can be essential for students with disabilities. For such students, so-called independent writing is “an irrelevant goal” since supports of all kinds, including technology, are often necessary to produce writing (297). For some students, creating writing that fits some standard of academic English is itself a negation of culture and history. Franklin and Falvey tell a haunting story of how a speaker of Haitian Creole found his voice celebrated in one assignment and then suddenly erased in another assignment; when he asked Grammarly to “fix” his writing, he was accused of violating AI writing policies because the final product was stilted and unnatural. 

There is a lot to discover in Writing Centers and AI: Generating Early Conversations. For many readers, a cover-to-cover reading may feel daunting, especially when there is so much to do right now in addressing AI concerns in our writing centers. The book is easy to navigate with five sections: Writing Center Professionals as Institutional and Disciplinary Leaders on Conversations about AI;  Researched Inquiries on AI and Writing Center Labor; Developing Training Materials and Praxis in Response to AI; Practices for Navigating AI with/in Writing Center Consultations; and Writing Centers’ Role in Fostering Accessible, Anti-Racist and Ethical AI Practices. Writing Center Professionals may jump to the section that relates to the stickiest issue for their writing center and learn how others have managed the problem. 

Individual chapters are self-contained enough to use for training materials with tutors, in semester-long tutoring classes, or to spark center-sponsored conversations about the role of AI writing in our wider campus communities. Ashley M. Beardsley trained consultants to find, read, and teach articles about AI-generated writing, summarizing them in a table that could be a helpful reading list for other writing center directors (183). The process Joella Cleary and Anna Rymer engaged in when planning student-led hybrid workshops at Salem College could be a blueprint for WCPs who would like to develop a similar project at their own institutions. Kristi Girdharry’s cross-campus incubator led to a table describing different ways writing center directors could proactively engage AI questions on campus, listing everything from putting together a community survey to developing campuswide AI-literacy initiatives (53-4). It is nearly guaranteed that any WCP will find at least one chapter that helps them develop goals or practices for their center or institution given the fear and potential of AI pervading our campuses. 

While the collection may feel comprehensive, editors Elisabeth H. Buck and Joshua Botvin are wise to clarify that these are only “early” conversations. Writing about AI is a moving target. When Ellen Cecil-Lemkin first became anxious about GenAI’s ability to replicate written language, she talked it over with her partner, a computer programmer. Initially, they were dismissive about the quality of computer writing, but then she writes that, “It wasn’t until … we played around with ChatGPT that we both fully realized the dramatic technological shift” that had occurred (219). Complaints about “bad” AI writing fall out of date as the systems get more sophisticated. Just as the rapid adoption of large-language model AI writing in late 2022 and early 2023 took many of us by surprise, there are undoubtedly new projects waiting in the wings. There will certainly be more conversations and possibly more editions of this collection to come.

Some readers may want to read the whole book to get a full view of the many aspects of AI writing that we must address in our centers. The scope is quite extensive. With roughly 350 pages in the edited collection, it can be tempting to bring in AI to solve the problem of getting through it all. Indeed, since the book is available through the WAC Clearinghouse website, I read it as a long PDF, toggling between my computer and iPad over different reading sessions, but whenever I scrolled too fast, the AI assistant in Adobe Acrobat would chirp helpfully, “Would you like me to summarize the text?”