fCrit: A Visual Explanation System for Furniture Design Creative Support
This work addresses the need for human-centered explainable AI in furniture design, offering a domain-specific approach for creative support, though it is incremental in applying existing HCXAI concepts to a new domain.
The paper tackles the problem of providing explainable AI critiques for furniture design by introducing fCrit, a dialogue-based system that tailors explanations to users' design language and cognitive framing, resulting in a method that supports reflective learning and formal analysis in creative practice.
We introduce fCrit, a dialogue-based AI system designed to critique furniture design with a focus on explainability. Grounded in reflective learning and formal analysis, fCrit employs a multi-agent architecture informed by a structured design knowledge base. We argue that explainability in the arts should not only make AI reasoning transparent but also adapt to the ways users think and talk about their designs. We demonstrate how fCrit supports this process by tailoring explanations to users' design language and cognitive framing. This work contributes to Human-Centered Explainable AI (HCXAI) in creative practice, advancing domain-specific methods for situated, dialogic, and visually grounded AI support.