Introduction

AI, it seems, is everywhere. And it is safe to say that recent developments in generative AI applications, starting with ChatGPT, have created a pivotal moment in our field. Some faculty find these new technologies and tools exciting and powerful agents that will improve teaching and learning activities for both students and instructors. Others are deeply resistant, citing environmental, ethical, and misinformation concerns.

Before ChatGPT was released in November 2022, Vauhini Vara published a piece in The Believer in which she used a GPT-3 application to help her write a profound, rich, and highly original piece about her sister's death. She confessed how hard it was for her to write this highly emotional piece. But ChatGPT's advanced language processing capabilities made it possible for her to publish this piece by merely providing the tool some context and conducting some editing later. Examples like this one make clear that generative AI tools have the potential to revolutionize various industries, including composition instruction. Beyond generating content, they can be used to automate tasks, engage with readers (or users) using natural language interactions, streamline workflows, and enhance productivity.

Concerns have been raised about the potential use and misuse of these tools, such as the lack of a mechanism that can test for artificial intelligence’s presence in a creative work. It came as no surprise when, within a year of ChatGPT’s launch, the Writers Guild of America went on strike and novelists like George RR Martin and Jonathan Franzen started pursuing a lawsuit against OpenAI – the company that launched ChatGPT. The ability to generate human-like text also raises ethical questions regarding the spread of misinformation and the creation of deepfakes. To address these concerns, it is crucial to approach the use of ChatGPT and related tools with caution and responsibility. The purpose of this collection is to understand some of the affordances of these tools and address concerns about their use in writing and composition fields. In a sense, this is a snapshot of our field's understanding of these tools in late 2024; this is a record that will facilitate research about what follows in terms of technological developments, regulations, and guidelines surrounding AI.

Of couse, another major challenge of engaging with a rapidly evolving technology like generative AI (or any new technology really) is that the pace of change far exceeds the speed of academic publishing. Nonetheless, while the chapters in the collection do reference older versions of this technology, at this point we haven't seen significant changes in how generative AI works, and, indeed, we believe that we are approaching a point of diminishing returns, even as the training data becomes ever more massive -- after all, no matter the input, the system cannot think, understand, evaluate, or feel in any way. It can only produce ever more human-sounding text in response to a prompt. We believe that the work presented here offers practical advice and conceptual frameworks that will remain valuable and relevant even as generative AI continues to grow.