







































 Humanities and Social Science Research; Vol. 8, No. 3; 2025 

ISSN 2576-3024   E-ISSN 2576-3032 

https://doi.org/10.30560/hssr.v8n3p21 

 21 Published by IDEAS SPREAD 

 

The Application of Generative AI in the Design of Guizhou Batik 

Patterns 

Qian Peng1 & Hourong Yu1 

1 School of Big Data Engineering, Kaili University, China 

Correspondence: Hourong Yu, No. 3 Kaiyuan Avenue, Kaili Economic Development Zone, Guizhou Province, 

China. E-mail: 346920573 qq.com 

 

Received: March 8, 2025; Accepted: March 19, 2025; Published: March 20, 2025 

 

The research is financed by (2023 Kaili University Planning Project "Research on the Design of Ethnic Traditional 

Handicraft Tourism Products in Guizhou Province" (2023XJGHQN04); 2025 Kaili University Integrated 

Research Project: "Research on Methods and Pathways of AIGC Empowering Ethnic Cultural Products" (YTH-

XM2025008); 2025 Kaili University Institutional Research Project: "Research on New Product Development 

Based on Generative Artificial Intelligence" (2025YB030)). 

 

Abstract 

Guizhou batik is a typical representative of textile dyeing intangible cultural heritage. This paper explores the 

feasibility of integrating generative AI with Guizhou batik by examining the current state of both fields. It proposes 

how generative AI can address existing challenges in Guizhou batik, such as the uneven distribution of inheritors 

and the outdated pattern symbols and design language. Furthermore, it discusses how traditional handicrafts can 

coexist with digital intelligence in the modern era. The study also demonstrates that the introduction of generative 

AI not only enables efficient design and enhances artistic expression but also preserves the traditional 

characteristics of batik craftsmanship, providing insights into the digital-intelligent integration of Guizhou batik 

art. 

Keywords: generative AI, Guizhou Batik, pattern design, Cultural Heritage Preservation 

1. Introduction 

Guizhou, as a province rich in ethnic minority cultures, boasts a vast array of intangible cultural heritage, with 

batik being an indispensable part. The value of Guizhou batik lies not only in its deep cultural significance but also 

in its unique aesthetic craftsmanship. However, traditional batik techniques face challenges such as complex 

processes, time-consuming production, limited color variations, and weak dye fastness, making them less 

compatible with the fast-paced modern era. The advancement of artificial intelligence, particularly generative 

technologies, has expanded the possibilities of design applications, bringing new vitality to the field. 

2. Overview of Guizhou Batik Culture and Generative AI Technology 

2.1 Overview of Guizhou Batik Culture 

As a representative textile dyeing technique in Guizhou Province, batik is closely linked to the region’s karst 

landforms and humid climate, which foster the growth of unique natural dye sources such as beeswax and indigo. 

This distinctive and complex geographical advantage directly influences the craftsmanship of batik. 

The traditional batik-making process is intricate and varies across different regions, but it can generally be 

summarized into four key steps: pre-wax treatment, wax application, dyeing, and wax removal [1]. During the wax 

application process, the temperature of the molten beeswax must be controlled between 60°C and 70°C to maintain 

its β-crystal structure [1]. In the indigo reduction bath, microbial fermentation must be carefully regulated within 

a temperature range of 10°C to 35°C to achieve optimal dyeing results. Additionally, during the wax removal stage, 

the temperature must be precisely maintained at 96°C to ensure complete wax dissolution without damaging the 

fabric. These meticulously crafted techniques make the entire batik process time-consuming and labor-intensive, 

leading to inefficiencies and a slow response to market demands. 

Beyond its complex craftsmanship, Guizhou batik boasts a diverse pattern system that reflects indigenous beliefs, 

ethnic history, worldviews, and cosmology, forming a unique cultural totem. Common motifs include dragons, 



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phoenixes, birds, fish, flowers, spirals, thunder patterns, and cloud patterns—symbolizing ancestral heritage, 

mathematical reasoning, and spiritual faith. These motifs serve as abstract expressions of storytelling and cultural 

transmission. However, despite its rich cultural depth, traditional batik techniques face multiple challenges in the 

era of artificial intelligence. The complexity of the craft limits innovation, the shortage of skilled inheritors results 

in a lack of novel pattern designs, and the relatively uniform traditional batik styles hinder penetration into the 

international market. These challenges necessitate urgent attention and solutions. 

2.2 Overview of Generative AI Technology 

Generative Artificial Intelligence (Generative AI) is a significant branch of AI, with its technical workflow 

generally divided into three stages: the learning and training phase, the generation and adjustment phase, and the 

generation optimization phase. Its core capability lies in enabling machines to perform deep learning based on 

given instructions, allowing them to identify patterns, imitate learned rules, and generate creative outputs that align 

with user requirements. These outputs can include text, images, audio, code, and more, making generative AI a 

transformative technology. 

The rise of large-scale models has been a pivotal factor in the rapid advancement of AI. As technological barriers 

lower, the combined forces of data availability, computational power, algorithms, and policy frameworks have led 

to an exponential increase in the development of generative AI platforms across various industries. Today, 

numerous AI platforms have emerged, each excelling in different areas. Examples include DeepSeek, ChatGPT, 

Stable Diffusion, Midjourney, Adobe Firefly, and JiMeng AI, among others. Some specialize in text generation, 

while others focus on creative image production, animation, or video generation [2]. Common applications of 

generative AI include content creation, where platforms such as DeepSeek and ChatGPT assist in generating 

advertising copy, answering queries, and aiding in programming. Others, like Midjourney and Adobe Firefly, 

allow users to generate images or videos simply by entering prompts. These diverse platforms cater to different 

application scenarios, significantly improving efficiency, enhancing creativity, and—most importantly—enabling 

personalized content generation. This versatility gives generative AI a distinct advantage in modern digital 

workflows. 

 
Figure 1. Registered Batik Inheritors Recorded by the National Intangible Cultural Heritage Protection Center 



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3. Analysis of the Current State of Guizhou Batik Pattern Design 

3.1 Distribution of Inheritors 

The inheritors of batik craftsmanship are the lifeblood of this intangible cultural heritage. The sustainability of this 

heritage depends on the collaboration of multiple stakeholders, including the government, the education system, 

and the market. According to data from the National Intangible Cultural Heritage Protection Center, there are only 

three officially registered national-level batik inheritors (as shown in Figure 1), with an average age of 67.3 years, 

all of whom are women. A significant portion of batik inheritors are over 60 years old, while younger inheritors 

under the age of 35 remain scarce. This severe aging trend among inheritors poses a serious challenge to the 

continuity of batik craftsmanship.Moreover, many younger inheritors lack a synchronized understanding of 

systematic craftsmanship and cultural knowledge, leading to gaps in their comprehension of traditional pattern 

genealogy. This disconnect makes it difficult to ensure cultural integrity in the process of innovation, further 

weakening the transmission chain. 

Additionally, the gender imbalance among batik inheritors is another critical issue. Due to traditional customs and 

familial influences, the vast majority of inheritors are women. This disproportionate gender ratio can significantly 

impact the inheritance and evolution of batik. Men and women often approach the world and problem-solving 

differently—women tend to have a softer, more fluid artistic style, while men may exhibit a more structured, bold 

approach. The underrepresentation of male inheritors may result in a lack of diversity in design perspectives, 

ultimately affecting both the preservation and innovation of Guizhou batik. 

3.2 Current State of Pattern Symbol Design 

Batik patterns are deeply rooted in ethnic cultural traditions, with each motif recording the historical evolution of 

the community. Symbols such as the "butterfly," "maple tree," "dragon pattern," "fish pattern," and "bird pattern" 

all carry profound cultural narratives. These symbolic storytelling methods contribute to the unique cultural 

identity of Guizhou batik. 

(1) Systematic and Narrative Aspects of Symbol Design 

The core of batik pattern design lies in symbolic representation. Designers classify and express symbols within 

different semantic categories, such as nature worship, ancestral worship, totemic symbolism, and geometric 

decoration (see Table 1) [3]. The structure of these symbols follows a hierarchical system: Core symbols are 

positioned at the center of the pattern, occupying the most prominent space with strict compositional 

rules.Auxiliary symbols are more flexible and serve to fill and decorate the design. Peripheral symbols, as the 

name suggests, are placed along the edges, playing a transitional and connective role.The most critical aspect of 

cultural symbol design is its cultural semantics—batik patterns should not only be aesthetically pleasing but also 

serve as carriers of ethnic history and cultural identity. For example, the "butterfly" pattern symbolizes the origin 

of life. According to Miao mythology, the Butterfly Mother was born from a maple tree and is revered as the 

mother of all beings. She fell in love with a water bubble and gave birth to twelve eggs, from which emerged 

legendary figures such as Jiang Yang (the ancestor of humanity), the Thunder God, the dragon, the ox, the tiger, 

the snake, and the centipede. After fulfilling her mission of creation, the Butterfly Mother became the guardian 

deity of the Miao people [4]. Thus, batik symbols are not merely decorative elements but visual carriers of ethnic 

history and cultural heritage. 

 

Table 1. Classification of Batik Pattern Symbols 

Pattern Category Typical Patterns Symbolic Meaning Pattern Examples 

Nature Worship 

Sun pattern, water 

wave pattern, cloud 

thunder pattern 

Reverence for natural 

forces 

 



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Ancestral Worship 

Butterfly pattern, 

bronze drum 

pattern, spiral 

pattern 

Related to the community's 

creation mythology or 

beliefs 

 

Totem Symbolism 

Dragon pattern, 

fish and bird 

patterns 

Ethnic identity 

recognition, spiritual 

beliefs of the community 

 

Geometric 

Decoration 

Spiral pattern, 

floral and plant 

patterns 

Decorative accents 

 

 

(2) Continuity and Innovation in Design Language 

The expression of batik patterns can be explored from three aspects: composition rules, shaping characteristics, 

and color systems. Traditional composition methods often follow principles such as "central symmetry," 

"continuous repetition," and "layered filling" [5]. Contemporary batik designers, while innovating, have 

incorporated some international design styles, such as the minimalist aesthetics of Nordic design. They simplify 

traditional symbols to cater to certain aesthetic preferences, but this may lead to a loss of cultural semantics. 

Traditional shaping characteristics often feature abstract and geometric forms, focusing on the rhythm and fluidity 

of the composition. In terms of color systems, the primary palette involves indigo and white, which are used in the 

batik process to express layers and depth. With the introduction of digital design tools, the efficiency of pattern 

creation has significantly increased. However, this innovation sometimes results in reduced cultural distinctiveness 

and recognition, and in some cases, an overemphasis on innovation has caused a misalignment of symbolic 

meaning within the patterns. 

 

 



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(3) Traditional Craftsmanship vs. Digital and Intelligent Techniques 

The traditional batik-making process centers around handmade craftsmanship, using indigo dye and natural 

beeswax as pigments, with copper knives as painting tools and cloth as the canvas. The wax-resist dyeing technique 

is employed to create the designs. These methods strictly adhere to the design rules passed down through 

generations, embodying the belief that "everything has a spirit, and everything can be painted."In contrast, digital 

intelligence (also known as "digital smart" technology) integrates digital media techniques into traditional 

processes, enabling faster and more efficient expression. The use of AIGC (Artificial Intelligence Generated 

Content) for decoding and encoding batik patterns allows for learning and simulating the traditional process 

through input instructions, ultimately generating results that resemble hand-crafted works. By adjusting and 

refining the design iteratively, digital methods can replicate the effects of plant dyes and copper knife artwork, 

changing the traditional characteristics of low production efficiency and high uniqueness.This deep integration of 

traditional craftsmanship and digital intelligence not only provides technological anchors for accurate cultural 

transmission but also fosters the emergence of a new paradigm for the "algorithm-driven traditional aesthetics" of 

intangible cultural heritage protection. Despite this, the practical application of AIGC in this field remains 

relatively rare and requires more guidance for positive development. 

4. Application of Generative AI in Guizhou Batik Pattern Design 

4.1 Symbolic Semantics Decoding and Batik Pattern Generation 

Guizhou batik dates back to the Qin and Han dynasties and is primarily found in regions such as Danzhai County, 

Zhijin County, and Anshun City. Researchers such as He Ruyi [6], Wu Lili [7], Wang Tong [8], and Zhang Yu [9] 

have contributed to the study of batik traditions among the Miao people in Zhijin, Anshun, Huishui, and Liuzhi, 

shedding light on the different regional characteristics, folk customs, core patterns, color features, and pattern 

structures. These differences have led to the formation of various batik schools (see Table 2).Generative AI, 

through deep learning techniques, collects and learns related data, and builds corresponding databases by 

simulating, classifying, and summarizing information. This allows for the rapid and systematic decoding of the 

cultural symbolism and semantic logic of Guizhou batik patterns. By doing so, generative AI helps batik inheritors 

shorten the learning time, enabling them to grasp the core essence of batik pattern design more quickly. 

 

Table 2. Analysis of Batik Schools 

school Core Patterns 
Color 

Features 
Pattern Structure 

Danzhai Miao Butterfly Mother, Water Patterns 

Blue and 

white 

contrast 

Symmetry with "vertical and horizontal" 

balance and scattered distribution 

Zhijin Miao 

Butterfly Mother, Yin Yang Fish, 

Miao Dragon, Golden Pheasant, 

Jiyu Bird, Bronze Drum, Swirl 

Patterns 

Dark blue 

tones 

Divergent, repetitive, positive and 

negative shapes, individual, continuous, 

appropriate, and combined forms 

Anshun Miao 
Horseshoe, Cockscomb Flower, 

Butterfly, Fish and Bird Patterns 

Solid dark 

blue 

"Full," "complete," "borrowed," and 

"combinational" layouts, with a multi-

layered composition radiating from the 

center 

Huishui 

Fengxiang 

Dyeing 

Starry Sky, Butterfly, Square 

Grid, Spider Flower, Thorn Pear 

Flower 

Cyan, blue, 

white tones 

Symmetrical central motifs with suitable 

patterns on both sides 

Liuzhi Long 

Horn Miao 

Migration Symbols (straight lines, 

square patterns), Butterfly, Sand 

Tree Tip Symbols 

Black and 

blue mixed 

dye 

Geometric "point, line, surface" 

composition 

 

Taking the batik patterns of the Danzhai Miao as an example, generative AI is used for pattern design. The author 

employs a combination of two platforms, DeepSeek (hereafter referred to as DS) and MidJourney (hereafter 

referred to as MJ), to generate new patterns. First, relevant historical and cultural data are input into DS, including 

information about the historical development of the ethnic group, core patterns, color features, and pattern 

structures, as well as the desired pattern outcomes. DS then learns from this information and generates prompt 



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words for MJ (as shown in Figure 1).Next, in MJ, the existing Danzhai Miao batik patterns are combined with the 

newly generated pattern prompts, producing new patterns that align with the semantic decoding and adapt to the 

development of the times (as shown in Figure 2). If the result is unsatisfactory, DS can be used to generate 

modification instructions, and adjustments can be made in MJ by refining the pattern iteratively until the most 

suitable version is achieved (as shown in Figure 3). 

  
Figure 1. DS-generated Prompt for MJ Figure 2. MJ-generated Patterns Based on the Prompt 

 

Figure 3. Final Generated Suitable Pattern 

  
Figure 4 Jimeng AI Generation Interface Figure 5 Jimeng AI Pattern Generated Based on Prompts 



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4.2 Design Language Innovation and Batik Pattern Generation 

Although Guizhou batik can be divided into several major schools, the blending of ethnic groups has led to a fusion 

of their characteristics. Upon examining the design language, certain common features can be identified, such as 

"central symmetry," "continuous repetition," and "layered filling," which are frequently used techniques. In 

addition to MJ, there are many excellent AI platforms in China that can generate images, such as Jimeng AI. The 

author uses the Jimeng AI platform to innovate the design language and generate new batik patterns. Taking the 

Anshun Miao batik style as an example, the author inputs the following command in the image generation page of 

Jimeng AI: Anshun Miao batik pattern design, combining cockscomb flowers and fish-bird patterns, with a deep 

blue monochromatic color feature. The pattern structure is a full-layout design with a central-to-periphery, multi-

layered composition. The model chosen is Image 2.0Pro, and the image size is W: 1291, H: 1360 (as shown in 

Figure 4). This allows Jimeng AI to generate the corresponding image (as shown in Figure 5). The author then 

selects the most appropriate design and iterates adjustments until the best result is achieved (as shown in Figure 

6). 

 
Figure 6. Final Optimized Pattern Generation 

 

4.3 Intelligent Craftsmanship and the Revival of Batik Patterns 

Traditional batik craftsmanship in Guizhou faces challenges related to the uneven distribution of inheritors. As a 

crucial link in the chain of cultural transmission, the craft is threatened by an aging practitioner demographic, a 

gender imbalance favoring women, low representation of urban inheritors, and a concentrated geographic spread. 

Additionally, the uniqueness of handmade production presents further challenges to the preservation of batik 

heritage. 

(1) Building Human-Machine Collaboration to Overcome the Challenges of Traditional Craftsmanship 

The inheritance of batik techniques is at risk due to the declining number of skilled artisans, compounded by the 

semantic loss in the transition from handcrafted to mechanized production. The advent of generative AI, alongside 

bionic control systems, intelligent fault-tolerance algorithms, and cross-media compilers, provides machines with 

intelligent "hands" capable of replicating traditional craftsmanship. Moreover, the synergy between high-precision 

nanotechnology and artisans' cultural intuition allows machines to precisely mimic the intricate characteristics of 

copper knife wax application, while artisans can compensate for the semantic gaps introduced by machine-based 

reproduction. 

(2) Innovating Interaction Paradigms and Reducing Training Cycles 

The essence of batik lies in the meticulous handwork of artisans, where every stroke—light or heavy—embodies 

years of experience. Advances in augmented reality (AR) now enable batik creation through AR gesture control 

systems, allowing for precise finger adjustments of density and wrist control of curvature. Additionally, sandbox 

modeling of craft parameters facilitates complex system simulations and the creation of novel patterns. This 

approach supports the nonlinear coupling of hundreds of process parameters, fostering new batik styles. 

Furthermore, the development of a digital DNA map for batik patterns can catalog unique features, procedural 

data, and heritage relationships, akin to biological DNA sequencing. Such a framework not only preserves the 

uniqueness of each craft but also reflects its evolution and lineage, significantly reducing the time required to train 

new artisans. 



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5. Conclusion 

This study explores the current state of Guizhou batik and generative AI, analyzing their integration to decode the 

semantic logic of batik symbols and innovate design language. By leveraging multiple AI platforms, the research 

provides inspiration for creating novel batik patterns. Additionally, to address the uneven distribution of batik 

inheritors, this study proposes the construction of a human-machine collaborative framework to overcome 

challenges in traditional craftsmanship. With the aid of generative AI, intelligent machines can closely replicate 

handcrafted techniques, while artisans’ cultural intuition helps mitigate semantic loss in machine-generated 

outputs. Moreover, the use of digital tools to create a DNA mapping system for batik patterns significantly shortens 

the training cycle for new artisans.However, there are still limitations in this research. For example, the challenge 

of reproducing the intricate "cracked ice" effect of traditional wax-resist dyeing through generative AI remains 

unresolved, which is a potential area for further investigation. It is hoped that these findings will provide valuable 

insights for future researchers working on the integration of generative AI and batik pattern design, contributing 

to the global promotion of China's intangible cultural heritage. 

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Copyright for this article is retained by the author(s), with first publication rights granted to the journal. 

This is an open-access article distributed under the terms and conditions of the Creative Commons Attribution 

license (http://creativecommons.org/licenses/by/4.0/). 


