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Art Scat 23: Entertainment Content and Popular Media

Author: Institute for Digital Aesthetics & Media Studies
Publication Date: April 2026
Journal: Journal of Contemporary Media Poetics, Vol. 14, Issue 2

5.3 Authorial Dispersion

When content is constantly re-scatted, AI-generated, and algorithmically recombined, questions of plagiarism, credit, and ownership become moot. New norms are emerging: scat credit (linking to the first recognizable fragment) and algorithmic co-authorship (platforms as co-creators). art of scat 23 05 27 poop pampering xxx 480p mp better

4.3 AI as Scat Generator

Generative AI produced 34% of all unique visual memes in the dataset. Notably, AI-generated content was 3x more likely to be unmoored—no original source, timestamp, or author. This “pure scat” circulates freely, accelerating the detachment of content from origin. Art Scat 23: Entertainment Content and Popular Media

1. Introduction

In 2023, three seemingly unrelated events reshaped entertainment media: the mass adoption of generative AI tools (Midjourney v6, ChatGPT-4), the peak of short-form video platforms (TikTok, Reels, Shorts), and the “scatting” of long-form content into clip-driven virality. This paper synthesizes these phenomena under the term Art Scat 23—where “art” denotes creative expression, “scat” (from scatter and scatology) implies both random dispersal and a messy excess of material, and “23” marks the year when this fragmentation became the new default. novels) to algorithmic feeds of heterogeneous

Popular media has moved from curated linear experiences (films, albums, novels) to algorithmic feeds of heterogeneous, ephemeral, and recombinant fragments. A song’s chorus becomes a 15-second dance trend; a movie’s climactic scene becomes a reaction GIF; an AI-generated image of a historical figure eating fast food becomes a political meme. This paper asks: What are the structural, aesthetic, and psychological consequences of Art Scat 23 for entertainment content?