Evolution & Foundation: AI Shares Creative Control
2026-06-15 • Neural and Evolutionary Computing
Neural and Evolutionary ComputingGraphicsHuman-Computer Interaction
AI summaryⓘ
The authors explore how combining genetic algorithms with AI that understands images and concepts can help create complex 3D shapes that look nice. Instead of artists picking every detail, AI helps guide the process by judging what looks good based on the artist's goals. This approach lets artists quickly try many different designs and see how the AI thinks about each one. The system also provides tools and explanations so users can understand the AI's creative decisions.
genetic algorithmsevolutionary systemsmultimodal AI3D organic formsaesthetic evaluationvisual reasoninggenerative designinteractive visualizationevolutionary parameter spaceAI foundation models
Authors
Dylan Banarse, Stephen Todd, William Latham, Frederic Fol Leymarie
Abstract
This paper investigates the creative process of automated design and artistic evaluation using an evolutionary system. We consider how a multimodal artificial intelligence (AI) model can communicate and guide a combined generative and evolutionary computational system. This creates a framework for the evolution of aesthetically pleasing complex 3D organic forms by integrating genetic algorithms with the visual reasoning capabilities of large-scale AI foundation models. The framework shifts the artist role from that of intensive direct selection to one of system design; transferring detailed step-by-step curation to an AI agent capable of multimodal aesthetic judgement. This framework enables the human artist/designer to rapidly traverse large areas of multi-dimensional evolutionary parameter space to find creative outcomes based on their semantic targets. Detailed audit trails of the AI's aesthetic reasoning are generated for each experiment. Interactive visualisation tools, together with AI-generated summaries and evolutionary narratives, enable deep exploration into each evolutionary experiment and providing a transparent insight into the AI-guided process.