Artism: AI-Driven Dual-Engine System for Art Generation and Critique
Shuai Liu, Yiqing Tian, Yang Chen, and Mar Canet Sola (2025)
Abstract
This paper proposes a dual-engine AI architectural method designed to address the complex problem of exploring potential trajectories in the evolution of art. We present two interconnected components: AIDA (an artificial artist social network) and the Ismism Machine, a system for critical analysis. The core innovation lies in leveraging deep learning and multi-agent collaboration to enable multidimensional simulations of art historical developments and conceptual innovation patterns. The framework explores a shift from traditional unidirectional critique toward an intelligent, interactive mode of reflexive practice. We are currently applying this method in experimental studies on contemporary art concepts. This study introduces a general methodology based on AI-driven critical loops, offering new possibilities for computational analysis of art. Keywords: Artificial Intelligence Art, Conceptual Collage, Art Production, Multi-Agent Systems, Digital Humanities
Venue: NeurIPS 2025. The Thirty-Ninth Annual Conference on Neural Information Processing Systems, San Diego (US)