Composing With Generative AI
A Special Issue for Computers and Composition
Volume 71: March 2024
Edited by Nupoor Ranade and Douglas Eyman
Deadline: 14 July 2023
In the very first issue of Computers and Composition, Hugh Burns (1983), in "A Note on Composition and Artificial Intelligence," argued that many qualitative issues faced by English composition instructors who teach using software tools may be resolved through ongoing research in the field of artificial intelligence. When students learn to use writing tools effectively, writing becomes a powerful instrument for composition and learning, but at the same time, the introduction of advanced technologies has generated debates about their effectiveness and appropriateness for writing pedagogy. Until recently, the question of how tools built on Natural Language Processing (NLP) or Generative AI impact writing and composition has not been a key focus of publications in the field of Computers and Writing. But with the release of ChatGPT in November of 2022, these questions have taken on an urgency that is being fueled by the rapid development of more and more powerful AI systems.
While AI specifically has not been a focus of research in Computers and Composition, the field certainly has produced a significant body of work on the technologies that led to our current AI-inflected landscape. For example, several works on data-driven technologies, algorithms, automated writing and assessment have been published in the journal in the last 10 years, including special issues on Digital Technologies, Bodies, and Embodiments co-edited by Scott Sundvall and Phil Bratta (2019), Composing Algorithms: Writing (with) Rhetorical Machines co-edited by Aaron Beveridge, Sergio C. Figueiredo, and Steven K. Holmes (2020), and Rhetorics of Data co-edited by Les Hutchinson and Maria Novotny (2021). Our community of scholars has widely researched different writing technologies from the point of view of their potential uses within and outside writing classrooms, collaboration opportunities, perspective on global discussions, and potential of technologies to do harm to various populations. This special issue call seeks work that continues from these critical foundations when researching AI, including (but not limited to) Large Language Models such as GPT.
AI tools like GPT can be used for a range of language-based tasks, including language translation, content summarization, question answering in conversational formats, and even creative writing. Its ability to improve any workflow makes it a potentially invaluable asset. The current capabilities of AI tools align with Burns’ predictions, as he suggested that the two fields where most advancement would occur would be natural language processing and predictive text or “intelligent computer-instruction” (p. 3). Now 30 years later, we now have access to GPT-4, a seemingly intelligent Generative AI that can plough through oceans of data to create new content on demand in text and multimedia formats. Automated writing technologies and the ones that use NLP algorithms are not new. Spell checkers for word processing software were introduced in the 1980s, and NLP was first used to write an essay in 1984 (Henrickson, 2019). Until 2015, NLP tools were most popular in journalism, but as they are getting better each day, their use in other disciplines has exploded. This popularity has made scholars assess the opportunities and challenges that come with AI adoption in our lives, but much of the current conversation appears to fall into two main oppositional camps that see AI as a path to either dystopian or utopian futures – and most of these conversations has not addressed or taken account of prior research in our field.
Just as predictive keyboards, spell checkers and auto-correct have transformed how, and what, we write even before 2009 when Grammarly was released, our field is particularly well-suited to addressing the impact of new writing technologies on writing studies research and composition pedagogies. Early research publications in other fields have described several limitations of using AI and GPTs in for education and learning more generally, such as the systems’ lack of contextual understanding, damage caused by bias in training data, and impacts on privacy (Chang & Kidman, 2023; Qadir, 2022; Floridi, 2023; Baidoo-Anu & Owusu Ansah, 2023), but we see a pressing need to address AI’s impact on writing studies more specifically. Thus, in this special issue, we want to explore how we can engage with AI writing technologies in composition research and teaching.
Specifically, we are interested in submissions that address questions such as the following:
- What are the most appropriate theoretical and methodological approaches for rhetorical consideration of using AI tools for writing practice?
- How will AI writing technologies change the way we assess student learning and growth?
- How can we balance the productive capacities of AI to help students learn alongside challenges to academic integrity these tools might encourage?
- What do AI writing tools teach us about human-nonhuman collaboration? How can AI tools help us highlight the aspects of feedback loops, and human-in-the-loop design of communication technologies and decision making?
- How can teachers navigate the effective and ethical use of AI technology to prevent biases and harm to the already marginalized populations?
- How might we leverage our field’s past research about writing technologies as we consider the affordances, constraints, and challenges of AI?
This is by no means an exhaustive list of questions, and we welcome submissions that take up other considerations of AI’s impact on writing studies writ large.
Proposals
Individuals and co-authors are invited to submit a 300–450-word proposal that clearly identifies the conscious and critical use of AI writing technologies in writing and research practices relevant to our field. Proposals should briefly provide an overview of the projected article, as well as explain its contribution to the discipline. Proposals should be submitted as a .doc or .docx file, attached to an email to Nupoor Ranade (nranade) and Doug Eyman (deyman). The subject line should read "Special Issue Proposal: Composing with Generative AI." Queries are encouraged and should be posed via email to Nupoor Ranade (nranade) and Doug Eyman (deyman).
Timeline
- Initial Proposals due: July 14, 2023
- Preliminary decision to authors: July 21, 2023
- Drafts of 6,000-8,000 words due: September 1, 2023
- Reviewer comments delivered to authors: October 2, 2023
- Article revisions due: November 1, 2023
- Copyediting and Final Correspondence with authors: November, 2023
- Upload of Final Contributions for March 2024 release: December 1, 2023
References
Baidoo-Anu, D., & Owusu Ansah, L. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Available at SSRN 4337484.
Burns, H. (1983). A note on composition and artificial intelligence. Computers and Composition, 1(1), 3-4.
Chang, C. H., & Kidman, G. (2023). The rise of generative artificial intelligence (AI) language models-challenges and opportunities for geographical and environmental education. International Research in Geographical and Environmental Education, 1-5.
Floridi, L. (2023). AI as Agency without Intelligence: On ChatGPT, large language models, and other generative models. Philosophy & Technology, 36(1), 15.
Henrickson, L. (2019). Natural language generation: Negotiating text production in our digital humanity. In Proceedings of the Digital Humanities Congress 2018.
Qadir, J. (2022). Engineering education in the era of ChatGPT: Promises and pitfalls of generative AI for education.
Douglas Eyman
Senior Editor and Publisher, Kairos: A Journal of Rhetoric, Technology, and Pedagogy