• International journal of advanced smart convergence
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• v.13 no.4
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• pp.50-59
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• 2024

Recent advancements in artificial intelligence (AI) technology are creating new opportunities for evolving brand design methodologies. AI possesses the ability to analyze intricate data and propose innovative solutions that may be overlooked by human designers. In this light, this study seeks to investigate the development of brand design concepts in tandem with AI advancements and explore the potential of integrating Generative AI into brand design through practical workshop case studies. The researchers organized a rebranding workshop for 'Goubuli (狗不理),' a renowned Chinese snack brand, involving students in the use of AI technology to generate design concepts. This study examined how AI can be incorporated into brand design processes and the changing role of designers. The key findings revealed that while AI tools excel at rapid concept generation and creative ideation, they require significant human oversight for cultural sensitivity and brand alignment. The findings revealed both the effectiveness and limitations of AI in brand design, highlighting specific methodologies for its application. This research contributes practical guidelines for integrating AI tools into brand design workflows and provides a framework for balancing AI capabilities with human expertise in commercial design projects. It was found that AI-generated images have inherent stylistic and structural limitations, underscoring the ongoing necessity for human designers to refine and enhance AI-generated content.

• Journal of Fashion Business
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• v.28 no.3
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• pp.122-139
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• 2024

Image-generated AI is rapidly emerging as a powerful tool to augment human creativity and transform the art and design process through deep learning capabilities. The purpose of this study was to propose and demonstrate the feasibility of a new design development method that combined traditional design methods and technology by constructing image-generated AI prompts based on artists' formative elements. The study methodology consisted of analyzing Kazmir Malevich's theoretical considerations and applying them to AI prompts for design, print pattern development, and 3D digital design. This study found that the suprematist works of Kazmir Malevich were suitable as design and print pattern prompts due to their clear geometric shapes, colors, and spatial arrangement. The AI-prompted designs and print patterns produced diverse results quickly and enabled an efficient design process compared to traditional methods, although additional refinement was required to perfect the details. The AI-generated designs were successfully produced as 3D garments, thereby demonstrating that AI technology could significantly contribute to fashion design through its integration with artistic principles. This study has academic significance in that it proposes a prompt composition method applicable to fashion design by combining AI and artistic elements. It also has industrial significance in that it contributes to design innovation and the implementation of creative ideas by presenting an AI-based design process that can be practically applied.

• Journal of Information Technology Applications and Management
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• v.31 no.5
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• pp.1-16
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• 2024

Generative AI technology, which represents the artificial intelligence era, is developing faster than any other field in image production and is being applied to practice. The purpose of this study is to explore various ways to use Generative AI by deriving the characteristics and types of Generative AI use cases of book cover design among visual design fields. The research method investigated the concept of Generative AI and the current status of use in the field of visual design through literature. Based on this, the book cover design cases were analyzed using the Generative AI currently published, and design characteristics and types were derived. As a result of the study, Generative AI book cover design could be divided into two characteristics: 'Indirect Expression' and 'Direct Expression' and three types: 'Image Transfer', 'Image Transformation', and 'Image Expansion'. Future uses of generative AI in book cover design will need to understand the format of the book, be able to describe a lot of knowledge and experience for prompting, and generate a lot of images for inspiration. Numerous Generative AI tools exist today. In the future, it should be the basis for designers to effectively handle Generative AI by analyzing commercial outcomes created by Generative AI in various design fields to create creative outcomes that can be used in practice beyond the use of tools.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.81-86
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• 2024

Advancements in generative AI are reshaping graphic and 3D content design landscapes, where AI not only enriches graphic design but extends its reach to 3D content creation. Though 3D texture mapping through AI is advancing, AI-generated 3D modeling technology in this realm remains nascent. This paper presents AI 2D image-driven 3D modeling techniques, assessing their viability in 3D content design by scrutinizing various algorithms. Initially, four OBJ model-exporting AI algorithms are screened, and two are further evaluated. Results indicate that while AI-generated 3D models may not be directly usable, they effectively capture reference object structures, offering substantial time savings and enhanced design efficiency through manual refinements. This endeavor pioneers new avenues for 3D content creators, anticipating a dynamic fusion of AI and 3D design.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.84-89
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• 2023

In recent years, with the breakthrough of Artificial Intelligence (AI) technology in deep learning algorithms such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAE), AI generation technology has rapidly expanded in various sub-sectors in the art field. 2022 as the explosive year of AI-generated art, especially in the creation of AI-generated art creative design, many excellent works have been born, which has improved the work efficiency of art design. This study analyzed the application design characteristics of AI generation technology in two sub fields of artistic creative design of AI painting and AI animation production , and compares the differences between traditional painting and AI painting in the field of painting. Through the research of this paper, the advantages and problems in the process of AI creative design are summarized. Although AI art designs are affected by technical limitations, there are still flaws in artworks and practical problems such as copyright and income, but it provides a strong technical guarantee in the expansion of subdivisions of artistic innovation and technology integration, and has extremely high research value.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.31-36
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• 2021

In the era of the 4th industrial revolution represented by AI technology, various AI education is being conducted in the education field. However, AI education in the educational field is mostly one-off project education or teacher-centered education. In order to practice student-centered, field-oriented education, an artificial intelligence education program was developed based on design thinking. The AI education program based on design thinking will improve understanding and ability to use AI through the process of solving everyday problems with AI, and will develop the ability to create new values beyond understanding AI. It is expected that various AI education will take place in the educational field through design thinking-based artificial intelligence education programs.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.285-293
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• 2021

With the advent of the 4th Industrial Revolution, AI utilization capabilities are being emphasized in various industries, but AI education design and curriculum research as universal education is currently lacking. This study offers a design for universal AI education to further cultivate its use in universities. For the AI basic education design, a questionnaire was conducted for experts three times, and the reliability of the derived design contents was verified by reflecting the results. As a result, the main competencies for cultivating AI literacy were data literacy, AI understanding and utilization, and the main detailed areas derived were data structure understanding and processing, visualization, word cloud, public data utilization, and machine learning concept understanding and utilization. The educational design content derived through this study is expected to increase the value of competency-centered AI universal education in the future.

• International Journal of Advanced Culture Technology
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• v.12 no.4
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• pp.379-390
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• 2024

Logo design plays a crucial role in brand marketing as an effective communication symbol that represents the identity of various products or services. The creative work of simplifying these symbolic meanings has traditionally been a specialized area reserved for designers, requiring unique artistic skills. However, with the advancement of artificial intelligence technology, it is anticipated that even the field of logo design could partially replace the role of designers, leading to changes in design methods and processes. Notably, AI Logo Maker Web tools provide automated solutions that allow users to easily and quickly create logos. With easier accessibility, convenience, and high efficiency compared to human designers, their use has been expanding, and related research has been progressing. However, specific studies comparing the AI's creativity in the idea generation phase with that of human designers have yet to be thoroughly conducted. This study aims to explore the collaborative potential by analyzing and comparing the types of idea generation (combination, similarity, expansion) in logo design sketches by professional designers versus AI Logo Maker-generated logos through word frequency analysis based on in-depth interviews. The results indicate that the total number of idea-related words used was 343 for designer sketches and 311 for AI Logo Maker outputs, with the AI using fewer words overall compared to the designers. Designers used more words in combination and similarity categories, while the AI excelled in expansion. The AI demonstrated remarkable performance in expansion, suggesting that AI Logo Maker Web services should be used in a complementary manner rather than as a replacement for designers. AI can provide rapid results by suggesting highly expansive ideas, while designers can refine these ideas to align with the concept. To better reflect the intuitive and creative workflows of users, AI needs to develop flexible and customizable interfaces that cater to varying levels of user expertise. Additionally, the AI's customization features should be enhanced through collaborative efforts with professional designers. This research specifically presents a direction for collaboration between designers and AI by comparing their idea generation types. At the same time, it proposes important insights into the value of artificial intelligence technology and human designers within the design industry.

• The Korean Fashion and Textile Research Journal
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• v.26 no.4
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• pp.326-338
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• 2024

This study investigates the intersection of generative AI and fashion design, with emphasis on the recognition of artificial-intelligence (AI)-generated works as creative outputs and the associated ethical and legal challenges. Generative AI technologies, such as GANs and diffusion models, have revolutionized the fashion industry by enabling the rapid creation of innovative designs. Despite these advancements, significant issues persist regarding the attribution of authorship and copyright protection. Current intellectual property frameworks in the U.S., the EU, and South Korea predominantly recognize human creators, which implies that AI-generated works are not copyright protected unless significant human creative input is demonstrated. This study reviews the relevant policies and guidelines from major organizations such as WIPO and the U.S. Copyright Office and examines various case studies to illustrate these points. Additionally, the ethical implications of AI in fashion design, particularly concerning data bias and transparency, are critically analyzed. The findings underscore the necessity for transparent and fair data usage, clear documentation of the creative process, and human-AI collaboration. This collaboration should enhance creativity without overshadowing the unique artistic contributions of human designers. The study concludes by recommending the development of robust legal and ethical guidelines to ensure responsible and innovative use of AI in fashion design. These guidelines aim to protect the rights of human designers while fostering a collaborative environment in which AI serves as an enabler of creativity and innovation.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.130-135
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• 2024

The Stable diffsuion AI tool is popular among designers because of its flexible and powerful image generation capabilities. However, due to the diversity of its AI models, it needs to spend a lot of time testing different AI models in the face of different design plans, so choosing a suitable general AI model has become a big problem at present. In this paper, by comparing the AI images generated by two different Stable diffsuion models, the advantages and disadvantages of each model are analyzed from the aspects of the matching degree of the AI image and the prompt, the color composition and light composition of the image, and the general AI model that the generated AI image has an aesthetic sense is analyzed, and the designer does not need to take cumbersome steps. A satisfactory AI image can be obtained. The results show that Playground V2.5 model can be used as a general AI model, which has both aesthetic and design sense in various style design requirements. As a result, content designers can focus more on creative content development, and expect more groundbreaking technologies to merge generative AI with content design.