• Journal of The Korean Association of Information Education
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• v.25 no.3
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• pp.483-490
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• 2021

In the era of the fourth industrial revolution, the importance of artificial intelligence(AI) is growing day by day, and there is no disagreement that AI education will bring great innovation in the future. Various attempts are being made to educate the topic of AI, but students who have no experience in AI education recognize AI only as a difficult target. Therefore, in this study, we analyze the changes in students' perception of AI by teaching them using AI. AI convergence education were conducted for 6th grade elementary school students, and pre and post tests were conducted in the form of AI awareness survey questionnaires which included questions such as interest in AI, changes brought by AI, and AI education. As a result, we confirm significant results that suggest the level of awareness of AI has improved through AI education in all factors. AI convergence education requires various AI convergence education programs as a form of education for social needs and future students, and hopefully a design based on this will help realize student centered education.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.4
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• pp.385-393
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• 2024

This study focuses on optimizing the layout of mobile educational content using AI technology, with a particular emphasis on vertical aspect ratio design. Against the backdrop of changing educational content consumption patterns due to the increased mobile device usage and advancements in AI technology, this research analyzes the characteristics and effects of vertical aspect ratio design and explores its potential combination with AI technology. The research methodology combines John Yablonski's UX laws and the concept of human effective field of view with AI technology to analyze the impact of vertical aspect ratio design on the educational content user experience and learning effectiveness. Results show that vertical aspect ratio design effectively focuses users' attention, reduces cognitive load, and contributes to increased learning immersion. Specifically, when combined with AI technology, vertical aspect ratio design proves effective in providing personalized learning experiences, enhancing learning abilities, developing creativity, and optimizing data analysis across various domains. This study is expected to contribute to the qualitative improvement of educational content by emphasizing the importance of vertical aspect ratio design in mobile learning environments and proposing optimization methods using AI technology. Future studies are anticipated to further develop these findings, providing important guidelines for mobile educational content development and the advancement of AI educational technology.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.309-314
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• 2023

This study examines the development and limitations of current artificial intelligence (AI) music composition programs. AI music composition programs have progressed significantly owing to deep learning technology. However, they possess limitations pertaining to the creative aspects of music. In this study, we collect, compare, and analyze information on existing AI-based music composition programs and explore their technical orientation, musical concept, and drawbacks to delineate future directions for AI music composition programs. Furthermore, this study emphasizes the importance of developing AI music composition programs that create "personalized" music, aligning with the era of personalization. Ultimately, for AI-based composition programs, it is critical to extensively research how music, as an output, can touch the listeners and implement appropriate changes. By doing so, AI-based music composition programs are expected to form a new structure in and advance the music industry.

• Journal of Digital Convergence
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• v.22 no.1
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• pp.15-21
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• 2024

The purpose of this study is to analyze the use of generative AI and the perception of differences between user groups. This study explored the perceptions of different user groups regarding generative AI, aiming to derive implications for enhancing AI utilization capabilities for each group. Upon analysis, it was found that there were no significant differences in perceptions across age groups. However, notable differences were observed between professional backgrounds, particularly in the areas of generative AI application and ethical perspectives. Consequently, this study suggests the need for diversified AI solutions tailored to specific fields of expertise. It underscores the importance of customized education and training programs, as well as specialized education focused on ethical considerations. Additionally, this research contributes academically by proposing varied AI usage strategies for different age and professional groups. It also highlights the role of text mining techniques in developing and improving AI utilization skills.

• Convergence Security Journal
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• v.22 no.3
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• pp.101-110
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• 2022

As the cases of using artificial intelligence in various fields increase, attempts to solve various issues through artificial intelligence in the intrusion detection field are also increasing. However, the black box basis, which cannot explain or trace the reasons for the predicted results through machine learning, presents difficulties for security professionals who must use it. To solve this problem, research on explainable AI(XAI), which helps interpret and understand decisions in machine learning, is increasing in various fields. Therefore, in this paper, we propose an explanatory AI to enhance the reliability of machine learning-based intrusion detection prediction results. First, the intrusion detection model is implemented through XGBoost, and the description of the model is implemented using SHAP. And it provides reliability for security experts to make decisions by comparing and analyzing the existing feature importance and the results using SHAP. For this experiment, PKDD2007 dataset was used, and the association between existing feature importance and SHAP Value was analyzed, and it was verified that SHAP-based explainable AI was valid to give security experts the reliability of the prediction results of intrusion detection models.

• Journal of Smart Tourism
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• v.1 no.4
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• pp.9-18
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• 2021

The impacts that AI and robotics systems can and will have on our everyday lives are already making themselves manifest. However, there is a lack of research on the ethical impacts and means for amelioration regarding AI and robotics within tourism and hospitality. Given the importance of designing technologies that cross national boundaries, and given that the tourism and hospitality industry is fundamentally predicated on multicultural interactions, this is an area of research and application that requires particular attention. Specifically, tourism and hospitality have a range of context-unique stakeholders that need to be accounted for in the salient design of AI systems is to be achieved. This paper adopts a stakeholder approach to develop the conceptual framework to centralize human values in designing and deploying AI and robotics systems in tourism and hospitality. The conceptual framework includes several layers - 'Human-human-AI' interaction level, direct and indirect stakeholders, and the macroenvironment. The ethical issues on each layer are outlined as well as some possible solutions to them. Additionally, the paper develops a research agenda on the topic.

• Smart Media Journal
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• v.11 no.2
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• pp.39-52
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• 2022

In the context of the evolution of automation and intelligence, deep learning and machine learning algorithms have been widely applied in aquaculture in recent years, providing new opportunities for the digital realization of aquaculture. Especially, water quality management deserves attention thanks to its importance to food organisms. In this study, we proposed an end-to-end deep learning-based TabNet model for water quality prediction. From major indexes of water quality assessment, we applied novel deep learning techniques and machine learning algorithms in innovative fish aquaculture to predict the number of water cells counting. Furthermore, the application of deep learning in aquaculture is outlined, and the obtained results are analyzed. The experiment on in-house data showed an optimistic impact on the application of artificial intelligence in aquaculture, helping to reduce costs and time and increase efficiency in the farming process.

• Educational Technology International
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• v.24 no.2
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• pp.143-168
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• 2023

This study aims to analyze the perceptions and educational needs of pre-service teachers for the use of Artificial Intelligence (AI) in education. To this end, we collected survey data from 25 undergraduate students who were enrolled in a teacher education college in Seoul. The purpose of the survey was to measure the importance and current performance for instructional AI use based on the technological, pedagogical, and content knowledge (TPACK) framework, and to explore the priority of educational needs using Borich's needs analysis and the Locus for Focus model. The results of the study confirmed that Ethics and TPK competencies are prioritized. Additionally, the results indicated a high demand for practical knowledge that can be implemented in the practice of education. Based on the results, it is necessary to develop a teacher education program that focuses on ethical aspects and teaching strategy competencies in AI-based education.

• Electronics and Telecommunications Trends
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• v.39 no.2
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• pp.54-65
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• 2024

This paper examines the trends of AI Foundation Model development and the competition to lead the related ecosystem, which have been rapidly unfolding since the emergence of ChatGPT, focusing on big tech companies in the United States. Based on this understanding of background knowledge, I analyzed and presented the main contents of the initial report reviewed by the UK competition authority, CMA, on potential competition issues that may arise in the process of innovations resulting from FM development. In addition, the trend and background of the CMA's investigation into the OpenAI-Microsoft partnership, whose importance has recently been highlighted, were also explained. It is expected that a reasonable domestic policy plan will be established by referring to these UK policy trends and monitoring & analyzing domestic industries.

• Journal of Information Technology Services
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• v.19 no.2
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• pp.93-107
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• 2020

Recently, artificial intelligence (AI) technologies has been widely used in various fields such as finance, and distribution. Accordingly, Korea has also announced its AI R&D strategy for the realization of i-Korea 4.0 in May 2018. However, Korea's AI technology is inferior to major competitors such as the US, Canada, and Japan Therefore, in order to cope with the 4th industrial revolution, it is necessary to allocate AI R&D budgets efficiently through selection and concentration so as to gain competitive advantage under a limited budget. In this study, the importance of each AI technology was evaluated in multi-dimensional way through the questionnaire of expert group using the evaluation index derived from the literature review From the results of this study, we draw the following implication. In order to successfully establish the AI technology development strategies, it is necessary to prioritize the cognitive computing technology that has great market growth potential, ripple effect of technology development, and the urgency of technology development according to the principle of selection and concentration. To this end, it is necessary to find creative ideas, manage assessments, converge multidisciplinary systems and strengthen core competencies. In addition, since AI technology has a large impact on socioeconomic development, it is necessary to comprehensively grasp and manage scientific and technological regulations in order to systematically promote AI technology development.