Machine-in-the-loop writing: Optimizing the rhetorical load

Abstract

This article offers Rhetorical Load Sharing as a theoretical framework for placing texts on a collaborative authorship spectrum spanning from human-authored text to synthetic text. It poses human-in-the-loop writing as a baseline ethical AI collaborative writing workflow that avoids offloading the entire rhetorical load to generative AI tools and argues that machine-in-the-loop writing, in which human collaborators retain majority of the rhetorical load, is an ideal AI collaborative writing model that is suitable for the technical and professional communication classroom.