The Even Sheen of AI: Kitsch, LLMs, and Homogeneity

Abstract

The exploding use and impact of Chatbots such as ChatGPT that are based on Large Language Models urgently call for a language which is fit to clearly describe functions and problems of the production process and qualities of the Chatbots' textual and image output. Recently, the discussion about appropriate and illuminating metaphors to describe LLMs has gained momentum. As an alternative to well-established metaphors such as "hallucinating" and "bullshit", we propose "kitsch" as a new metaphor. As an internationally widespread term from literary and cultural studies, we argue that "kitsch" is particularly suitable for analytically illuminating a previously neglected feature of LLM-based images and texts: their tendency to produce homogeneous and average content, which is becoming increasingly dominant as the proportion of AI-generated content on the internet grows. This is leading to the equalisation of language, style and argument. In view of the potential negative consequences of this averaging, including for human content producers on the internet, we advocate combining methods and insights from kitsch studies with AI research, philosophy, and communication studies in order to better understand the phenomenon and develop countermeasures.