• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.305-310
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• 2024

With the emergence of generative AI, a new era of coexistence with humanity has begun. The vast data-driven learning capabilities of AI are being utilized in various industries to achieve a level of productivity distinct from human learning. However, AI also manifests societal phenomena such as technophobia. This study aims to analyze collaborative AI models based on an understanding of AI and identify areas within the jewelry industry where these models can be applied. The utilization of collaborative AI models can lead to the acceleration of idea development, enhancement of design capabilities, increased productivity, and the internalization of multimodal functions. Ultimately, AI should be used as a collaborative tool from a utilitarian perspective, which requires a proactive, human-centric mindset. This research proposes collaborative AI strategies for the jewelry business, hoping to enhance the industry's competitiveness.

• Annual Conference of KIPS
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• 2023.05a
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• pp.437-439
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• 2023

본 연구는 프로그래밍 협업 환경에서 생성형 AI인 ChatGPT-4를 활용한 코딩 프로세스를 제안한다. 일관성 있는 결과를 얻기 위해 프롬프트 생성, GPT 실행, 의사코드 변환, 코드 비교, 동일 코드 생성 여부 판단, 테스트 실행, 동일 결과 생성 여부 판단, 코드 검사 및 수정의 8단계를 거친다. 팀 프로젝트와 페어 프로그래밍 등의 다양한 협업 환경에 적용 가능한 이 프로세스를 통해 생성형 AI를 효과적으로 활용할 수 있음을 보여주었다는 점에서 그 의미가 있다. 본 연구는 생성형 AI를 활용한 협업 환경에서의 코딩이 본격적으로 이루어질 것으로 예상되는 이 시점에서, 인간-AI 협업 환경에서의 코딩 효율성 및 일관성을 높일 수 있을 것으로 기대한다. 이러한 연구는 인간과 AI가 함께 작업하는 미래를 위한 기초를 마련하는 데 중요한 역할을 할 것이다.

• Electronics and Telecommunications Trends
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• v.37 no.6
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• pp.32-42
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• 2022

Recently, decentralized approaches to artificial intelligence (AI) development, such as federated learning are drawing attention as AI development's cost and time inefficiency increase due to explosive data growth and rapid environmental changes. Collaborative AI technology that dynamically organizes collaborative groups between different agents to share data, knowledge, and experience and uses distributed resources to derive enhanced knowledge and analysis models through collaborative learning to solve given problems is an alternative to centralized AI. This article investigates and analyzes recent technologies and applications applicable to the research of multi-agent collaboration of AI bots, which can provide collaborative AI functionality autonomously.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.87-99
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• 2024

This study aims to identify the competencies required for webtoon artists to survive in the future era of AI commercialization. It explores the current and future use of AI in webtoons, and predicts the role of artists in the future webtoon industry. The study finds that AI will replace human workers in some areas, but human empathy-related fields can be sustained. Artist roles like story projectors, Visual directors, and AI editors were identified as potential models for the changing role of artists. To address terminology ambiguity, a three-step AI categorization mechanical type AI, humanoid type AI, and transcendent type AI was proposed for a more realistic separation of AI capabilities. The researcher suggested these findings as guidelines for developing skills in emerging artists or re-skilling existing ones, emphasizing collaboration with AI for mutual growth rather than a negative acceptance of new technology.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.517-524
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• 2024

Generative AI, exemplified by models like ChatGPT, has revolutionized human-machine interactions in the 21st century. As these advancements permeate various sectors, their intersection with the arts is both promising and challenging. Despite the arts' historical resistance to AI replacement, recent developments have sparked active research in AI's role in artistry. This study delves into the potential of AI in visual arts education, highlighting the necessity of swift adaptation amidst the Fourth Industrial Revolution. This research, conducted at a 4-year global higher education institution located in Gyeongbuk, involved 70 participants who took part in a creative convergence module course project. The study aimed to examine the influence of AI collaboration in visual arts, analyzing distinctions across majors, grades, and genders. The results indicate that creative activities with AI positively influence students' creativity and digital media literacy. Based on these findings, there is a need to further develop effective educational strategies and directions that incorporate AI.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.183-189
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• 2019

After the fourth industrial revolution, a business that utilizes Artificial Intelligence (AI) is expanding centered around IT industries and it is expected that the quality of AI services will improve. This study aims to examine changes in marketing through the advance and development of AI and to establish and apply marketing strategies to respond to future market changes. Based on existing data, the development of AI technology was examined and looked into changes in marketing and counter strategies through cases overseas and South Korea. Artificial Intelligence technology has a close impact on our lives, changing our lives, and thus changing consumer patterns, perceptions, and consumer culture. In the future, innovative changes in AI technologies will require government policies, the vision of the corporation, and it is necessary to establish longer-term success strategies. Collaboration between companies and industries is also important.

• The Journal of the Korea Contents Association
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• v.20 no.5
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• pp.79-89
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• 2020

The current study explored if users' self-relevance of the comparison domain with creative AI robot in music composition affected their envy toward the robot, cognitive assessment toward the music and intention toward working with robot in future. This study conducted a 2 (degree of self-relevance: high(college students majoring in music) vs. low(those not majoring in music) × 2 (working type: robot-only vs. robot-human collaboration) between-subjects factorial design experiment. The findings revealed that those majoring in music did not feel envious of the robot as much as those not majoring in music. However, compared to those not majoring in music, those majoring in music evaluated the robot's creativity lower, had more negative attitude toward the music, showed less intention to use the music and work with the robots in future. No interaction between the degree of self-relevance and the working type was found.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.1
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• pp.25-40
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• 2023

Recommendation systems are frequently used by users to generate intelligent automatic decisions. In the study of movie recommendation system, the existing approach uses largely collaboration and content-based filtering techniques. Collaborative filtering considers user similarity, while content-based filtering focuses on the activity of a single user. Also, mixed filtering approaches that combine collaborative filtering and content-based filtering are being used to compensate for each other's limitations. Recently, several AI-based similarity techniques have been used to find similarities between users to provide better recommendation services. This paper aims to provide the prospective expansion by deriving possible solutions through the analysis of various existing movie recommendation systems and their challenges.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.127-130
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• 2024

본 연구는 기존 포털형 정보 서비스의 한계를 극복하고자, 이전 연구에서 제안된 연구자의 R&D 프로세스 과정에서의 협업을 지원하는 개방형 협업 지원 서비스 플랫폼을 기반으로 하여, 본 연구에서는 R&D 프로세스 중 '사전 단계'에 대한 설계와 구현을 소개한다. 우리는 R&D 프로세스를 문헌 리뷰와 연구 가설 설정 등을 수행하는 '사전 단계,' 실험과 데이터 분석 등을 수행하는 '실행 단계', 논문 작성 및 출판 등을 수행하는 '성과화 단계'로 구분하고, 이 중 '사전 단계'에 대해 프로젝트 뷰, 그룹 뷰, 문헌 뷰, 관계 뷰를 설계하고 구현하였다. 연구자는 이 플랫폼을 통해 문헌 내용 및 문헌 간 복잡한 연관성을 신속하게 파악할 수 있으며, 플랫폼은 연구자에 의해 자연스럽게 생성되는 사용자 정의 관계를 통해 향후 심층적인 문헌 네트워크 구축 및 분석이 가능해질 것으로 기대한다.

• Industry Promotion Research
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• v.9 no.4
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• pp.237-246
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• 2024

The purpose of this study is to explore ways to improve the efficiency of design work using Adobe Firefly, a generative AI program. To this end, we conducted an online survey and in-depth interviews with Firefly experts using a mixed research methodology that combines quantitative data analysis and qualitative research. Studies have shown that Firefly's image editing, text-to-image conversion, vector graphics conversion, and icon creation capabilities significantly improve user productivity and satisfaction. Additionally, the intuitive user interface and integration with the Adobe Creative workflow were found to contribute to increased efficiency. Based on this, this study proposes strategies such as active use of Firefly functions, integration with work flow, utilization of collaboration tools, and user education and experience enhancement. This is expected to increase the overall efficiency and productivity of the design team.