Exploring Opportunities to Support Novice Visual Artists' Inspiration and Ideation with Generative AI

2025-09-28

AI Summary

Novice visual artists face core challenges including inspiration scarcity, inefficient reference image acquisition, difficulty in stylistic synthesis, lack of expert feedback, and unclear skill-development pathways. Method: Through interviews with 12 professional artists, we identified key requirements and—leveraging advances in generative AI—designed and implemented six artist-centered interactive prototypes supporting reference image retrieval, multi-style composition visualization, AI-simulated artistic critique, and progressive technique learning. Using a co-design methodology, we validated the prototypes in a workshop with 13 novice artists. Contribution/Results: Our evaluation revealed critical tensions around reference usage, stylistic experimentation, and trust in AI-generated feedback. The study yields a reusable design framework and empirical evidence for generative AI tools targeting creative beginners, advancing human-centered creative augmentation systems.

Technology Category

• Humans and AI: Game Design — Procedural Content Generation & Storytelling
• Computer Vision: Generative Adversarial Networks (GANs) for Vision
• Cognitive Modeling & Cognitive Systems: Computational Creativity

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Search and Retrieval-Augmented AI: Agentic search

Abstract

Recent generative AI advances present new possibilities for supporting visual art creation, but how such promise might assist novice artists during early-stage processes requires investigation. How novices adopt or resist these tools can shift the relationship between the art community and generative systems. We interviewed 13 artists to uncover needs in key dimensions during early stages of creation: (1) quicker and better access to references, (2) visualizations of reference combinations, (3) external artistic feedback, and (4) personalized support to learn new techniques and styles. Mapping such needs to state-of-the-art open-sourced advances, we developed a set of six interactive prototypes to expose emerging capabilities to novice artists. Afterward, we conducted co-design workshops with 13 novice visual artists through which artists articulated requirements and tensions for artist-centered AI development. Our work reveals opportunities to design novice-targeted tools that foreground artists' needs, offering alternative visions for generative AI to serve visual creativity.

Problem

• Investigating how generative AI assists novice artists during early creative stages
• Addressing artists' needs for references, visualizations, and personalized learning support
• Developing artist-centered AI tools that foreground creative needs and tensions

Innovation

• Developed interactive prototypes for novice artists
• Mapped artist needs to open-source AI capabilities
• Designed tools foregrounding artists' requirements