Nischwitz, Lena MarcellaHaupt, JosefWeigelt, Aurora-ZoeChuang, Lewis L2024-10-082024-10-082024https://dl.gi.de/handle/20.500.12116/44883This study validates Lorenz’s Kindchenschema features by using a commercial text-to-image generator (Midjourney v.5.2) to generate stimulus material that depicted either animals or objects with or without the text prompts for “cute” and “anthropomorphic”. In an online study human participants evaluated the presence of Kindchenschema features in said images. Our results show their increased presence and perception in AI-generated images created with the prompt “cute” compared to those explicitly excluding it, as well as the systematically prioritisation of features such as “large, deep-set eye” and “rounded body shapes” in cute images. Whereas “round, protruding cheeks”, traditionally considered essential by Lorenz, ranks lower. Furthermore, the anthropomorphisation of subjects reduces the likelihood of Kindchenschema features, highlighting constraints in AI-generated stimuli. This research demonstrates the potential of AI-tools to objectively quantify and test theoretical concepts as represented in popular culture.enAnthropomorphismBaby SchemaCutenessCuteness AestheticDiffusion ModelKindchenschemaLarge Language ModelMidjourneyText-To-Image GenerationText/Conference Paper10.1145/3670653.3677512