Application and pathways of AIGC in the digital transference and transformation of traditional Chinese cultural symbols

The swift advancement of Generative Artificial Intelligence (AIGC) technology offers a new paradigm for the inheritance and dissemination of traditional Chinese culture, serving as a crucial engine for driving cultural innovation and shaping new quality productive forces. However, the process of digitally transferring and transforming traditional cultural symbols faces practical bottlenecks, including cultural semantic disjuncture, high transformation costs, and insufficient integration between technological application and humanistic connotations. This research focuses on the application mechanisms and pathway innovation of AIGC technology in this domain. By defining core concepts such as AIGC, traditional cultural symbols, and digital transference/transformation, and reviewing relevant studies on AIGC in cultural creative design, intangible cultural heritage protection, and cross-cultural communication, it aims to explore a technology-supported, culture-oriented path for creative transformation to enhance the vitality and international influence of traditional culture in the digital age. 

Semiotic theory, particularly Peirce's triadic model of the sign, provides a key lens for analyzing the transference process of cultural symbols. Traditional cultural symbols can be viewed as composites of the Representamen (material form), Object (referent), and Interpretant (cultural meaning). The intervention of AIGC profoundly influences the entire process from perception and cognition to emotional resonance. Furthermore, cultural communication theory emphasizes that dissemination is not one-way transmission but a process where meaning is constructed and shared within specific socio-cultural contexts. AIGC-empowered cultural communication is shifting from institution-led Professional Generated Content (PGC) towards a more collaborative and participatory "mass co-creation" model, whose value lies in intelligently facilitating the effective flow of cultural meaning and empathetic resonance. Additionally, human-AI collaborative creation theory redefines the creative paradigm within the AIGC environment. 

Here, AIGC acts as a "creative partner" or "inspiration catalyst," handling tasks like pattern learning from vast cultural data, preliminary creative generation, and rapid iteration of solutions, while humans focus on grasping cultural connotations, making aesthetic judgments, and providing value guidance, creating a complementary advantage. The transference of traditional cultural symbols by AIGC is a systematic process advancing through the interaction of three dimensions: the technological dimension (data-driven, multimodal generation, interactive capabilities) serves as the enabling foundation, expanding the boundaries and efficiency of symbolic expression; the symbolic dimension (extraction, reconstruction, innovative expression of traditional symbols) is the core object of the transference operation, focusing on the modernization of form and meaning; the cultural dimension (cultural authenticity, value connotation, identity construction) is the ultimate value goal and meaning anchor, ensuring technological innovation serves the inheritance of cultural spirit and deepened identity. 

These three dimensions are intertwined and mutually shaping. The application of AIGC in transferring traditional Chinese cultural symbols demonstrates diversification, primarily manifesting in three scenarios: content innovation, experience transformation, and communication empowerment. In content innovation, AIGC drives the modernization of traditional cultural IPs through symbol generation and narrative construction. Regarding experience transformation, AIGC combined with technologies like VR/AR creates immersive experiences in museums and cultural tourism, shifting from "static viewing" to "dynamic participation," making abstract cultural values tangible and perceptible. In communication empowerment, leveraging its algorithmic strengths, AIGC aids traditional culture in cross-cultural adaptation and targeted dissemination, for instance, by learning target culture aesthetics for adaptation or using user profiling for precise content recommendation. 

Elevating the application to a methodological level, a hierarchical and actionable practice guide is constructed, covering a complete pathway from macro-concept evolution to micro-technical implementation. Macroscopically, the concept should shift from one-dimensional "digital archiving" to creative "digital revitalization," involving a closed-loop path: permanent digital archiving of cultural resources, semantic parsing and style learning of structured cultural data using AIGC, and ultimately guiding towards innovative expression and value regeneration, achieving a paradigm upgrade from "preservation" to "innovation." For the diversity of traditional symbols, differentiated transference strategies are necessary: focusing on AIGC's image generation and style transfer capabilities for pattern and craft symbols; emphasizing its narrative construction ability for mythical and literary narrative symbols; and combining AIGC with VR/AR to create immersive experiences for ritual and ceremonial behavioral symbols. 

At the micro-operation level, the specific technical path involves building high-quality cultural datasets, selecting and fine-tuning AIGC models using prompt engineering for precise control, and establishing a human-machine collaborative creation and evaluation cycle where designers critically assess outputs for cultural and artistic value. 

While AIGC presents significant opportunities, its application entails technical, cultural, and ethical challenges requiring careful consideration. Current AIGC may lead to cultural misinterpretation due to training data biases or algorithmic "black boxes." Overemphasis on visual spectacle or market preferences might lead to superficiality and homogenization, diluting profound cultural connotations. Thus, a balance between innovation and preserving cultural authenticity is crucial, ensuring technology serves accurate cultural expression and deep identification. 

Future research will trend towards deeper integration and intellectualization, potentially combining generative AI with embodied intelligence and brain-computer interfaces for fully immersive experiences, and developing controllable AIGC systems with deep cultural understanding. Ultimately, a sustainable "human-machine symbiotic" creative ecosystem should be built, where AIGC acts as a tool to stimulate human cultural creativity, jointly promoting the revitalization of traditional Chinese culture in the digital age and its effective global reach.