Dear Colleagues,
We wanted to share the call for proposals for an edited collection about Generative AI, refusal, and writing studies. Proposals are due January 31, 2025. (The full timeline is below.) You can find the full CFP here: https://docs.google.com/document/d/1ErZ57-liRaoQlVDjzcrshXoZsKlxgTAW_dxP0DZ1iMU/edit?tab=t.0.
Please reach out if you have any questions.
Sincerely,
Megan and Maggie
Call for Proposals: EDITED COLLECTION, Unprompted
Due Date: January 31, 2025
Unprompted: Pedagogies, Theories, and Futures of GenAI Refusal in Rhetoric and Writing Studies
Edited by Maggie Fernandes and Megan McIntyre, University of Arkansas
Overview
Since the release of ChatGPT in fall 2022, scholars and teachers of writing, rhetoric, and technical and professional communication have had wide-ranging conversations about the impact of large language models (LLMs) and generative AI tools on teaching, learning, and literacy, including the ethical challenges surrounding these tools. Such possibilities and ethical dilemmas have been explored in the MLA-CCCC working papers on writing and AI and the recent collections TextGenEd: Teaching with Text Generation Technologies, and Teaching and Generative AI, among other emergent research and resources.
Despite generative AI’s devastating implications for climate crisis (Hogan and Lepage-Richer, 2024), linguistic oppression (Bender, et al., 2021; Owusu-Ansah, 2023), and racial justice (Noble, 2018; Benjamin, 2019) among other documented harms, there has thus far not been widespread disciplinary discussions about more critical refusal, rejection, resistance, and skepticism related to these tools and technologies. More skeptical engagement – which we understand as a disposition of questioning, mistrust, and doubt that informs the actions we (don’t) take – is needed. To this end, we ask: what kind of critical AI literacies and approaches might originate from refusal? How can we foster critical awareness of these writing technologies that centers harm mitigation?
Building onRefusing Generative AI in Writing Studies: A Quickstart Guide (Sano-Franchini, McIntyre, and Fernandes, 2024), this edited collection seeks a wide variety of refusal-based approaches that allow us to respond to the current generative AI moment while also leaning into what we know about teaching writing. Therefore, we invite 300-500 word proposals for an edited collection focused on teaching, writing, and working in the age of Generative AI. We especially invite proposals that take up the question of generative AI-resistant arguments, theories, and pedagogies alongside the following topics:
- Race, gender, sexuality, and/or disability justice and/or equity (Noble 2018; Benjamin, 2019)
- Linguistic oppression and injustice (Kynard, 2023; Owusu-Ansah, 2023)
- Environmental justice and digital damage (Edwards, 2020; Hogan and Lepage-Richer, 2024)
- Labor concerns (Merchant, 2023), especially for TAs, contingent, and non-tenure-track faculty
- Writing program and course goals or outcomes (Beck, et al., 2024)
- Generative AI in/and professional and technical writing programs, courses, and contexts
- Specific pedagogical approaches or course assignments
- Intellectual property, data privacy, and/or surveillance (Woods and Wilson, 2021)
- Educational technology, learning management systems, and the corporatization of higher education (Bjork, 2024; Nelson and Vee, 2022)
Edited Collection Sections
Proposers should identify one of the following sections within which their chapter might best fit.
- Theories of refusal, resistance, rejection, and skepticism: these chapters will focus on the theoretical and evidence-based arguments for refusing, rejecting, or promoting skepticism about the role of generative AI in writing classrooms, programs, and theories.
- Pedagogies and policies of refusal for rhetoric and writing studies: these chapters will focus on specific practices for generative AI refusal, rejection, or skepticism and include classroom activities, writing and/or reading assignments, or specific classroom policies and their rationale.
- Reflections and responses to the current conversation in rhetoric and writing studies: these chapters will offer reflections and responses to current and recent conversations in rhetoric, composition, writing studies, and technical and professional communication about generative AI.
Submission Instructions
Please send proposals of up to 500 words as well as an 8 source bibliography to Maggie Fernandes (mbfern) and Megan McIntyre (mm250) by January 31, 2025. All proposals should include a discussion of which of the sections above authors believe their work best fits into. We’ll respond by February 15, 2025.
Please include the following author information:
- Your name(s)
- Your affiliation(s)
- Your email(s)
Timeline
- Proposal Submission Deadline: January 31, 2025
- Acceptance Notifications Sent: February 28, 2025
- Full Drafts Due: June 15, 2025
- Feedback on Drafts Sent: August 1, 2025
- Revised Drafts Due: October 1, 2025
- Manuscript Submitted to the Press: December 1, 2025
References
Bender, Emily. M., Timnit Gebru, Angelina McMillan-Major, & Schmargaret Shmitchell. (2021). On the dangers of stochastic parrots: Can language models be too big?. In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency, 610-623
Benjamin, Ruha. (2019). Race after technology: Abolitionist tools for the new Jim Code. John Wiley & Sons.
Bjork, Collin. (18 Sept 2024). Clones in the classroom: why universities must be wary of embracing AI-driven teaching tools. The Conversation. https://theconversation.com/clones-in-the-classroom-why-universities-must-be-wary-of-embracing-ai-driven-teaching-tools-238977
Edwards, Dustin W. (2020). Digital rhetoric on a damaged planet: Storying digital damage as inventive response to the Anthropocene. Rhetoric Review, 39(1), 59-72.
Hogan, Mél. & Théo LePage-Richer. (2024). Extractive AI. Climate Justice and Technology Essay Series. McGill University.
Kynard, Carmen. (December 11, 2023). When Robots Come Home to Roost: The Differing Fates of Black Language, Hyper-Standardization, and White Robotic School Writing (Yes, ChatGPT and His AI Cousins). Blog post. http://carmenkynard.org/when-robots-come-home-to-roost/
Merchant, Brian. (2023). Blood in the machine: The origins of the rebellion against big tech. Hachette.
Nelson, S.L., and Annette Vee. (2022). “The View From ‘Zoom University’: Surveillance and Control in Higher Ed’s Pandemic Pedagogy Pivot.” enculturation: A Journal of Rhetoric, Writing, and Culture,34 https://enculturation.net/zoom_university.
Noble, Safiya U. (2018). Algorithms of oppression: How search engines reinforce racism. NYU Press.
Owusu-Ansah, Alfred L. (2023.) Defining Moments, Definitive Programs, and the Continued Erasure of Missing People. Composition Studies 51.1, p. 143–148.
Sano-Franchini, Jennifer, Megan McIntyre, and Maggie Fernandes. Nov. 2024. “Refusing GenAI in Writing Studies: A Quickstart Guide.” Refusing Generative AI in Writing Studies. refusinggenai.wordpress.com
Wise, Beck, Lisa Emerson, Ariella Van Luyn, Bronwen Dyson, Collin Bjork, & Susan E. Thomas. (2024). A scholarly dialogue: writing scholarship, authorship, academic integrity and the challenges of AI. Higher Education Research & Development, 43(3), 578-590.
Woods, Charles, and N. Wilson. (2021). The rhetorical implications of data aggregation: becoming a ‘dividual’ in a data-driven world. The Journal of Interactive Technology and Pedagogy, 19.
Dr. Megan McIntyre
Director, Program in Rhetoric and Composition
KIMP 328A
Department of English
University of Arkansas