TextGenEd Exhibit

Abstract

plagiarism has challenged educators for decades, with heightened paranoia following the advent of the Internet in the 1980's and ready access to easily copied text.But plagiarism will look like child's play next to new developments in AI-based natural-language processing (NLP) systems that increasingly appear to "write" as effectively as humans.How we theorize and contextualize these developments will guide the way we meet their challenges in all courses where writing is assigned and evaluated Here, I first revisit an article I wrote for Composition Studies in 2011, "Fraudulent Practices: Academic Misrepresentations of Plagiarism in the Name of Good Pedagogy."In that article, I argued that what counts as plagiarism in some contexts occurs with impunity across a wide range of published material.This is because definitions of plagiarism are socially constructed and tied to context-sensitive cycles of reward for the production-and therefore the ownership-of certain kinds of texts.Helping students to understand plagiarism means showing them these contextually-specific constructs of text ownership, rather than assuming that any unattributed text, published anywhere, in any form, constitutes plagiarism.I then turn to AI-based NLP systems.Teachers who learn what these systems can do usually respond with the same hand-wringing and defensive posture triggered by concerns about student plagiarism.But a social-practices interpretation again breaks open the systems' perceived threats and reveals a more nuanced and contextual approach to their challenges-and their potential acceptance and use-alongside writing produced by humans.

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