Drawing on rhetorical genre studies, we explore research article abstracts created by generative artificial intelligence (AI). These synthetic genres—genre-ing activities shaped by the recursive nature of language learning models in AI-driven text generation—are of interest as they could influence informational quality, leading to various forms of disordered information such as misinformation. We conduct a two-part study generating abstracts about (a) genre scholarship and (b) polarized topics subject to misinformation. We conclude with considerations about this speculative domain of AI text generation and dis/misinformation spread and how genre approaches may be instructive in its identification.
CITATION STYLE
Mehlenbacher, B., Balbon, A. P., & Mehlenbacher, A. R. (2024). Synthetic Genres: Expert Genres, Non-Specialist Audiences, and Misinformation in the Artificial Intelligence Age. Journal of Technical Writing and Communication. https://doi.org/10.1177/00472816231226249
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