• Informatization Policy
• /
• v.31 no.2
• /
• pp.39-64
• /
• 2024

This study assesses the national AI competitiveness of 38 OECD countries with focus on AI human capital, AI infrastructure, and AI innovation capacity. Utilizing the fuzzy-set ideal type analysis method, these countries were categorized into eight distinct types based on their national AI competitiveness levels, leading to the derivation of pertinent implications. The analysis identified a category termed "AI Leading Country" consisting of North American, Western European, and Nordic countries, along with several Asian nations including South Korea. Remarkably, the United States demonstrated dominant global national AI competitiveness, achieving the highest fuzzy scores across all three evaluative factors. South Korea was classified as an "AI Leading Country" primarily due to its superior AI infrastructure, but its performance in AI human capital and AI innovation capacity was found to be moderate relative to other analyzed nations; thus highlighting the necessity of sustained focus on the accumulation of AI human capital and bolstering of AI innovation capacity.

• Electronics and Telecommunications Trends
• /
• v.36 no.1
• /
• pp.81-88
• /
• 2021

Post COVID-19, the medical legacy system will be transformed for utilizing medical resources efficiently, minimizing medical service imbalance, activating remote medical care, and strengthening private-public medical cooperation. This can be realized by achieving an entire medical paradigm shift and not simply via the application of advanced technologies such as AI. We propose a medical system configuration named "Medical AI Hub" that can realize the shift of the existing paradigm. The development stage of this configuration is categorized into "AI Cooperation Hospital," "AI Base Hospital," and "AI Hub Hospital." In the "AI Hub Hospital" stage, the medical intelligence in charge of individual patients cooperates and communicates autonomously with various medical intelligences, thereby achieving synchronous evolution. Thus, this medical intelligence supports doctors in optimally treating patients. The core technologies required during configuration development and their current R&D trends are described in this paper. The realization of the central configuration of medical AI through the development of these core technologies will induce a paradigm shift in the new medical system by innovating all medical fields with influences at the individual, society, industry, and public levels and by making the existing medical system more efficient and intelligent.

• Convergence Security Journal
• /
• v.24 no.2
• /
• pp.9-17
• /
• 2024

This paper examines the security threats to enterprise Generative Artificial Intelligence systems and proposes countermeasures. As AI systems handle vast amounts of data to gain a competitive edge, security threats targeting AI systems are rapidly increasing. Since AI security threats have distinct characteristics compared to traditional human-oriented cybersecurity threats, establishing an AI-specific response system is urgent. This study analyzes the importance of AI system security, identifies key threat factors, and suggests technical and managerial countermeasures. Firstly, it proposes strengthening the security of IT infrastructure where AI systems operate and enhancing AI model robustness by utilizing defensive techniques such as adversarial learning and model quantization. Additionally, it presents an AI security system design that detects anomalies in AI query-response processes to identify insider threats. Furthermore, it emphasizes the establishment of change control and audit frameworks to prevent AI model leakage by adopting the cyber kill chain concept. As AI technology evolves rapidly, by focusing on AI model and data security, insider threat detection, and professional workforce development, companies can improve their digital competitiveness through secure and reliable AI utilization.

• Journal of Information Technology Services
• /
• v.20 no.5
• /
• pp.43-54
• /
• 2021

Currently, citizens' expectations and concerns on utilizing artificial intelligence (AI) technologies in the public sector are widening with the rapid digital transformation. Furthermore the level of global acceptance on the AI and other intelligent digital technologies is augmenting with the needs of non-face-to-face types of public services more than ever due to the unforeseen and unpredictable pandemic, COVID-19. Thus, this study intended to empirically examine what policy directions for the public should be considered to provide well-designed services as well as to promote the evidence-based public policies in terms of Al speaker technology as a non-contact smart city service. Based on the survey of senior citizens' perceptions on AI (AI Speaker technology), this study conducted structure equation modeling analyses to identify whether technology acceptance models on to the varied dependent variables such as actual use, perception, attitude, and brand royalty. The Results of the empirical analyses showed that AI increased the positive level of citizens' perception, attitude and brand royalty on non-contact public services (smart city services) which are becoming more crucial for developing AI oriented government and providing intelligent public services effectively. In addition, theoretical and practical implications are discussed for understanding the changes of public service in the post-corona.

• Journal of Korea Artificial Intelligence Association
• /
• v.1 no.1
• /
• pp.7-10
• /
• 2023

This study proposes an AI-based shoe recommendation model based on user clothing image data to solve the problem of the global fashion industry, which is worsening due to factors such as the economic downturn. Shoes are an important part of modern fashion, and this research aims to improve user satisfaction and contribute to economic growth through a generative AI-based shoe recommendation service. By utilizing generative AI in the personalized consumer market, we show the feasibility, efficiency, and improvements through an accessible web-based implementation. In conclusion, this study provides insights to help fulfill consumer needs in the ever-changing fashion market by implementing a generative AI-based shoe recommendation model.

• Journal of Digital Convergence
• /
• v.18 no.6
• /
• pp.479-493
• /
• 2020

Outbreak of COVID-19 originated from China resulted significantly high casualties and social and economic damages. Currently the major countries see importance of accurate prediction of originating trend to prevent the spread of infectious disease and AI is actively utilized when establishing the system. Therefore this study has comprehended the status of utilizing the AI in overseas and made comparison and analysis with domestic status. It derived the necessity to establish national control tower based on One Health to respond to infectious disease to effectively utilize AI and suggested to establish higher organization, Medical Big Data Governance, to respond to the infectious disease. It is necessary to conduct further study to utilize the results and suggestions derived from this study into the policy and if the suggestions are reflected to improve institutional imperfection, it will be positively used for prevention of the spreading infectious disease and utilizing medical Big Data.

• The Journal of Industrial Distribution & Business
• /
• v.12 no.8
• /
• pp.21-32
• /
• 2021

Purpose: With the advent of the era of the 4th industrial revolution, called a new technological revolution, the necessity of fostering future talents equipped with AI utilization capabilities is emerging. However, there is a lack of research on AI education design and competency-based education curriculum as education for business major. The purpose of this study is to design AI education to cultivate competency-oriented AI literacy for business major in universities. Research design, data and methodology: For the design of AI basic education in business major, three expert Delphi surveys were conducted, and a demand analysis and specialization strategy were established, and the reliability of the derived design contents was verified by reflecting the results. Results: As a result, the main competencies for cultivating AI literacy were data literacy, AI understanding and utilization, and the main detailed areas derived from this were data structure understanding and processing, visualization, web scraping, web crawling, public data utilization, and concept of machine learning and application. Conclusions: The educational design content derived through this study is expected to help establish the direction of competency-centered AI education in the future and increase the necessity and value of AI education by utilizing it based on the major field.

• Journal of Information Technology Applications and Management
• /
• v.31 no.4
• /
• pp.99-119
• /
• 2024

Focusing on the rapid progress of image generation AI, this study examines the changes in talent required according to changes in the production process of the content industry, and proposes an educational management plan for the subject and comparative department of the university's animation major. First, through environmental analysis, the trend of the animation content industry is analyzed in three stages, and the necessity of producing AI-adapted content talent is derived by re-establishing the talent image of the university's animation major and introducing it into rapid education. Next, we present a case designed by applying teaching methods to improve technology convergence capabilities and project-oriented capabilities by presenting subject and non-curricular cases operated in the animation department of the researcher's university. Through this, we propose the necessity of education to cultivate animation content talent who can play technical and administrative roles by utilizing various AI systems in the future. The goal of this study is to establish a cornerstone study by presenting application cases and having the status of a university as a talent supplier that can lead the content industry beyond the era of AI content production that breaks the boundaries of genres between contents. In conclusion, it is intended to propose the application of education to create value through technology convergence capabilities and project-oriented capabilities to cultivate AI-adapted content talents.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.3
• /
• pp.713-722
• /
• 2024

This study highlights the impact of Artificial Intelligence (AI) technology on journalism, discussing its utility and addressing major ethical concerns. Broadcasting companies and media institutions, such as the Bloomberg, Guardian, WSJ, WP, NYT, globally are utilizing AI for innovation in news production, data analysis, and content generation. Accordingly, the ecosystem of AI journalism will be analyzed in terms of scale, economic feasibility, diversity, and value enhancement of major media AI service types. Through the previous literature review, this study identifies key ethical and social issues in AI journalism as well. It aims to bridge societal and technological concerns by exploring mutual development directions for AI technology and the media industry. Additionally, it advocates for the necessity of integrated guidelines and advanced AI literacy through social consensus in addressing these issues.

• International Journal of Advanced Culture Technology
• /
• v.11 no.4
• /
• pp.333-339
• /
• 2023

In three-dimensional(3D) modeling, texturing plays a crucial role as a visual element, imparting detail and realism to models. In contrast to traditional texturing methods, the current trend involves utilizing AI tools such as Leonardo.Ai and Meshy to create textures for 3D models in a more efficient and precise manner. This paper focuses on 3D texturing, conducting a comprehensive comparative study of AI tools, specifically Leonardo.Ai and Meshy. By delving into the performance, functional differences, and respective application scopes of these two tools in the generation of 3D textures, we highlight potential applications and development trends within the realm of 3D texturing. The efficient use of AI tools in texture creation also has the potential to drive innovation and enhancement in the field of 3D modeling. In conclusion, this research aims to provide a comprehensive perspective for researchers, practitioners, and enthusiasts in related fields, fostering further innovation and development in this domain.