This paper is conceptual in nature: it does not propose a fixed framework for a specific learning context; instead, it builds on research in classical and digital rhetoric, competence development, and AI literacy to argue for the necessity of a distinct Rhetorical AI Literacy. To develop such a flexible rhetorical framework, the paper outlines the fundamental literacy requirements for users and examines the interplay between human and machine communication. This paper first identifies a gap in existing AI competence frameworks – their neglect of rhetoric as an essential dimension of AI literacy – and then frames its analysis around three interconnected domains: pragmatism, offering a practical lens on AI’s evolving role in discourse and decision making; interface design, which shapes user–AI interactions; and technè, highlighting the procedural skills central to rhetorical practice. Taken together, these perspectives reconceive generative AI not merely as a technical tool but as a fundamentally rhetorical system that shapes knowledge production, argumentation, and meaning making. Then, drawing on Aristotle’s conception of technè as poiesis and Isocrates’ emphasis on rhetorical situatedness as praxis, the paper develops a production-oriented framework for Rhetorical AI Literacy. Central to this approach is the question of how human rhetorical judgment can be fostered and exercised effectively in specific contexts of collaboration with generative AI. To address this, an educational scenario is proposed – one that integrates technological, rhetorical, and ethical considerations, and structures the learning and exercise of rhetorical judgment along four dimensions: 1. Co-activity and accessibility: AI as a rhetorical partner; 2. Bullshit generators and Promptology: managing AI’s rhetorical illusions; 3. Adopting and adapting: rhetorical usage practices; 4. Human responsibility and contextual accountability. In doing so, the paper aims to illuminate the paradigmatic situation of co-activity that humans experience with generative AI systems, concluding with an outlook on promising areas of future research accessible through the lens of Rhetorical AI Literacy.
Markus Gottschling (Wed,) studied this question.