Design Generative AI for Practitioners: Exploring Interaction Approaches Aligned with Creative Practice
Xiaohan Peng, Wendy E. Mackay, Janin Koch

TL;DR
This paper explores new interaction methods for integrating Generative AI into design practice, emphasizing distributed control and dynamic alignment to better support creative workflows.
Contribution
It introduces three novel interaction approaches that distribute control across different stages, aligning AI more closely with designers' intentions and creative processes.
Findings
Interaction approaches enable better AI alignment with design intent
AI can adopt proactive or reactive roles based on creative needs
Distributed control improves designer-AI collaboration
Abstract
Design is a non-linear, reflective process in which practitioners engage with visual, semantic, and other expressive materials to explore, iterate, and refine ideas. As Generative AI (GenAI) becomes integrated into professional design practice, traditional interaction approaches focusing on prompts or whole-image manipulation can misalign AI output with designers' intent, forcing visual thinkers into verbal reasoning or post-hoc adjustments. We present three interaction approaches from DesignPrompt, FusAIn, and DesignTrace that distribute control across intent, input, and process, enabling designers to guide AI alignment at different stages of interaction. We further argue that alignment is a dynamic negotiation, with AI adopting proactive or reactive roles according to designers' instrumental and inspirational needs and the creative stage.
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Taxonomy
TopicsDesign Education and Practice · Ethics and Social Impacts of AI · Innovative Human-Technology Interaction
