How do people experience the images created by generative artificial intelligence? An exploration of people's perceptions, appraisals, and emotions related to a Gen-AI text-to-image model and its creations

Amon Rapp, Chiara Di Lodovico, Federico Torrielli, Luigi Di Caro

Abstract:

Generative Artificial Intelligence (Gen-AI) has rapidly advanced in recent years, potentially producing enormous
impacts on industries, societies, and individuals in the near future. In particular, Gen-AI text-to-image models
allow people to easily create high-quality images possibly revolutionizing human creative practices. Despite their
increasing use, however, the broader population’s perceptions and understandings of Gen-AI-generated images
remain understudied in the Human-Computer Interaction (HCI) community. This study investigates how in-
dividuals, including those unfamiliar with Gen-AI, perceive Gen-AI text-to-image (Stable Diffusion) outputs.
Study findings reveal that participants appraise Gen-AI images based on their technical quality and fidelity in
representing a subject, often experiencing them as either prototypical or strange: these experiences may raise
awareness of societal biases and evoke unsettling feelings that extend to the Gen-AI itself. The study also un-
covers several “relational” strategies that participants employ to cope with concerns related to Gen-AI,
contributing to the understanding of reactions to uncanny technology and the (de)humanization of intelligent
agents. Moreover, the study offers design suggestions on how to use the anthropomorphizing of the text-to-image
model as design material, and the Gen-AI images as support for critical design sessions.