Artism: AI-Driven Dual-Engine System for Art Generation and Critique

Shuai Liu, Yiqing Tian, Yang Chen, Mar Canet Sola

Track: Paper

Keywords: Artificial Intelligence Art, Conceptual Collage, Art Production, Multi-Agent Systems, Digital Humanities

TL;DR: Artism introduces a dual AI system: AIDA (virtual artist network) and Ismism Machine (pattern analyzer) that reveals contemporary art's "conceptual collage syndrome" through computational critique and cross-temporal artist simulations.

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.

Submission Number: 189