In the game of visual telephone, one player draws a picture and describes it to another player, who must then attempt to draw the picture based only on the verbal description. Researchers have made artificial intelligence (AI) models play the game. In a new study published in Patterns, researchers paired two AI models and set them loose for 100 rounds of visual telephone. But no matter how diverse or specific the starting prompt, the AIs repeatedly converged on the same 12 generic, often Eurocentric motifs—what the researchers call “visual elevator music.”

Team algorithmically generated 100 text prompts to seed games of visual telephone. The prompts were deliberately unusual and distinct. Across the hundreds of resulting trajectories, the AIs defaulted to 12 dominant motifs. When the researchers extended the experiment to 1000 iterations, most image sequences remained stuck once they reached one of the 12 dominant motifs. In one case, however, a trajectory abruptly jumped after several hundred steps, moving from a snow-covered house to cows in a field and then to a quaint town. But how often such jumps occur, or whether some visual endpoints are more stable than others, remains unclear.

Source https://www.science.org/content/article/when-creating-images-ai-keeps-remixing-same-12-stock-photo-cliches

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