Synthetic Genres: Expert Genres, Non-Specialist Audiences, and Misinformation in the Artificial Intelligence Age

Author:

Mehlenbacher Brad1,Balbon Ana Patricia2,Mehlenbacher Ashley Rose1ORCID

Affiliation:

1. Department of English Language and Literature, University of Waterloo, Hagey Hall of the Humanities, 200 University Ave, Waterloo, Ontario, N2L 3G1, Canada

2. Department of Physiology, University of Toronto, Medical Sciences Building, 1 King’s College Circle, Toronto, Ontario M5S 1A8, Canada

Abstract

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.

Funder

Canada Research Chairs

Social Sciences and Humanities Research Council of Canada

Ontario Early Researcher Award

Publisher

SAGE Publications

Subject

Education,Communication

Reference57 articles.

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