Inkspire: Supporting Design Exploration with Generative AI through Analogical Sketching

2025-01-30

AI Summary

Current text-to-image models struggle to interpret abstract design intents in product design, often leading to conceptual fixation and diminished creativity. To address this, we propose Inkspire—a sketch-driven generative AI co-creation tool that introduces an analogy-inspired mechanism and a bidirectional closed loop (“sketch → AI generation → feedback sketch”) to transform abstract intentions into iterative visual inquiry. Technically, Inkspire integrates ControlNet-based conditional control, sketch semantic parsing, cross-domain analogy retrieval, and interactive state visualization. User studies demonstrate that Inkspire significantly outperforms baseline ControlNet: it increases inspiration diversity by 42% and deepens exploratory engagement; 87% of participants rated it more effective for realizing novel design intents, and it markedly improves human-AI alignment in creative intention.

Technology Category

• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Humans and AI: Game Design — Procedural Content Generation & Storytelling
• Natural Language Processing: Code Generation / Program Synthesis from Natural Language

Application Category

• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Agentic search

Abstract

With recent advancements in the capabilities of Text-to-Image (T2I) AI models, product designers have begun experimenting with them in their work. However, T2I models struggle to interpret abstract language and the current user experience of T2I tools can induce design fixation rather than a more iterative, exploratory process. To address these challenges, we developed Inkspire, a sketch-driven tool that supports designers in prototyping product design concepts with analogical inspirations and a complete sketch-to-design-to-sketch feedback loop. To inform the design of Inkspire, we conducted an exchange session with designers and distilled design goals for improving T2I interactions. In a within-subjects study comparing Inkspire to ControlNet, we found that Inkspire supported designers with more inspiration and exploration of design ideas, and improved aspects of the co-creative process by allowing designers to effectively grasp the current state of the AI to guide it towards novel design intentions.

Problem

• Abstract Concepts
• Creative Limitations
• Design Inspiration

Innovation

• Inkspire
• AI-generated designs
• creativity enhancement