An Exploratory Analytical Framework for Artificial Intelligence-Driven Interactive Art Installations

Abstract

Interactive art is a form in which aesthetic content emerges through audience participation within technology-based installations designed for interactive engagement. Recent developments in AI have increasingly shaped this field, influencing audience participation, the dynamic interplay between installations and algorithms, and the formation of aesthetic experience. However, relatively little research has examined how AI affects these design dimensions in interactive art. To address this gap, this study proposes the exploratory 4A framework, comprising audience participation, art object embodiment, AI inquiry and response, and aesthetic experience. Rather than advancing a wholly new theory of interaction, the framework extends earlier models by treating AI as an analytically distinct entity to examine the technical and experiential conditions specific to AI-driven artworks. Drawing on publicly available documentation, we analyzed three artworks presented at the CVPR 2024 AI Art Gallery as illustrative cases to demonstrate the framework’s application. The analyses elaborate interpretive design propositions concerning AI temporality, modality conversion, and AI-mediated aesthetic experience. These propositions suggest potential approaches to designing AI-driven interactive installations, while the framework provides a structured basis for further analysis. The study’s limited case selection and documentary basis highlight the need for broader application, framework refinement, and empirical investigation of audience experience.