Co-creating eco-visualizations: a human–AI collaborative pipeline for data-driven visual design

Abstract

Communicating complex environmental phenomena requires forms of visualization that go beyond analytical accuracy to support engagement, interpretation, and reflection. Eco-visualization addresses this challenge by combining data representation with aesthetic and narrative elements, but its creation often demands technical skills. This paper presents a Human–AI co-creative pipeline for the design of eco-visualizations, in which AI acts as an active collaborator throughout the visual creation process. The approach integrates generative image creation, AI-assisted segmentation, and data-driven color mapping into a structured workflow that supports iterative interaction between human and AI. We implement this pipeline as a web-based system and evaluate it through a user study with a mixed-method approach. Results show that while the system is perceived as engaging and conceptually innovative, users experience notable usability challenges and cognitive load during interaction. These findings highlight key tensions in Human–AI co-creation, particularly between control and ease of use. Overall, this work contributes a concrete design approach to Human–AI collaboration in eco-visualization and provides empirical insights that inform the development of more accessible and effective co-creative tools for communicating complex environmental data.