From Result Imitation to Cultural Translation: An Intelligent Generation Approach for Dong Brocade Patterns Based on Patternology

Abstract

Generative artificial intelligence (AI) has become a significant frontier in pattern design, but generating culturally informed patterns remains challenging. Mainstream training data biases limit AI's understanding of minority cultures, leading to superficial feature replication and cultural appropriation in AIGC. This study uses Dong brocade as a case, shifting from "Lamarckian copy-the-product" to "Weismannian copy-the-instruction.", it adopts a Weismannian concept of cultural inheritance, focusing on transmitting intrinsic generative logic as 'instructional information'. Through fieldwork and Patternological analysis, a systematized Dong brocade knowledge “instructional information set” was constructed and implemented in a customized generation system. Comparative experiments demonstrate that this method significantly outperforms general models in cultural authenticity. This approach reshapes AI from a general imitator into a culturally informed translator, providing a replicable and culturally sustainable pathway for intelligent innovation in minority pattern designs.

Keywords: Dong Brocade, Patternology, Intelligent Generation, Instructional Information

DOI: 10.54941/ahfe1007460