Design Generative AI for Practitioners: Exploring Interaction Approaches Aligned with Creative Practice
This addresses the problem of integrating Generative AI into professional design workflows for designers, though it appears incremental as it builds on existing interaction concepts.
The paper tackles the misalignment between Generative AI output and designers' intent in creative practice by presenting three interaction approaches—DesignPrompt, FusAIn, and DesignTrace—that distribute control across intent, input, and process, enabling better guidance of AI alignment.
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.