Designing Interactions with Generative AI for Art and Creativity: A Systematic Review and Taxonomy

Generative Artificial Intelligence (GenAI) applications in artistic and creative domains have gained substantial attention of late. These intelligent interactive systems, shaped by innovations in Large Language Models (LLMs) and Vision Language Models (VLMs), are materially impacting digital creative domains. While initial work to understand this space has highlighted new models and architectures, we lack a holistic view of how interactive GenAI systems are designed for user interactions across various artistic and creative domains. In this paper, we present a systematic review of interactive GenAI system designs for art and creativity in the HCI literature (N = 189), and a detailed taxonomy of interaction paradigms with design components. We shed light on the communities of design focus and decompose the system interaction designs, mapping these characteristics to creative domains, user interaction patterns, GenAI technologies, detailing under-represented spaces, and future directions of designing interactions for GenAI creativity.

Recommended citation: Hu, X., Xing, Y., Cai, X., Zhao, Y., Cook, M., Borgo, R., & Neate, T. (2025). Designing Interactions with Generative AI for Art and Creativity: A Systematic Review and Taxonomy. In Designing Interactive Systems Conference (DIS `25) ACM. doi: 10.1145/3715336.3735843.
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