Rhetoric & AI
Key Ideas
Writing with AI is an Iterative process of determining where/how your ideas can develop and fit into the larger picture.​
Rhetoric - Art of persuasion.
Posthuman AI - We are entangled with the technologies. It’s human AND AI and the meaning they create.
Using outputs successfully involves that recognizing that the output is not just language. Language has meaning and creates new meaning. Meaning is created by an intersection of many elements, including, tone, emotion, and connections to other ideas. These elements have tangible effects on the meaning that is created, and successful rhetorical strategies account for them to create new meaning that is insightful, unique, and that relates to other sources of knowledge.
AI outputs are designed to mimic rhetorical approaches and replicate genre conventions in ways that do not necessarily match the writing situation (Omizo & Hart-Davidson, 2024). The result is a patchwork of rhetorical choices, some of which come from a tool that mimics rhetorical patterns rather than working rhetorically to create meaning.
Many people may not grasp the implications of delegating rhetorical decisions to generative AI. When they make this choice, they may opt for convenience rather than engaging with how rhetoric shapes knowledge-making.
Hart-Davidson (2018) found that AI does not actually "do" rhetoric: it mimics it. But he also observed that AI could serve as a resource for humans working to improve their rhetorical strategies.
Generative AI users would benefit from understanding how different rhetorical dimensions shape the meaning produced through generative AI and how to apply this understanding to human-AI interactions.
Another useful way of seeing the connection between rhetoric and generative AI is Wang’s (2024) post-rhetoric, which suggested that rhetoric's symbolic or semiotic foundations become de-centred with AI tools.
“The boundaries between human discourse and machine discourse no longer matter, are further blurred, or even cease to exist. As such, inventing and circulating discourses becomes an end in itself” (Wang, 2024, p. 162).
"The way knowledge gets created, taken up, circulated, and embedded within communities depends increasingly on the entanglement between people and the tools they share knowledge-making spaces with. So, writing with AI can be better seen as a spectrum of human and machine that can help avoid relying on a rhetorical output that just 'looks right'" (Eaton, forthcoming, b).
Remember
Teaching learners to assess how well their writing addresses genre and rhetorical demands could support them in determining how to engage rhetorically with generative AI.
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When AI influences rhetorical strategy, it can only work from the prompts it receives. Whatever guidance the knowledge maker provides influences the resulting meaning. Delegating rhetorical strategies to generative AI shifts some rhetorical control away from humans, requiring increased oversight into the final output. As Bearman and Ajjawi (2023) and Moulaison-Sandy (2025) have shown, working with AI expands the realm of uncertainty in the knowledge people create.