• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.97-106
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• 2020

Due to the rapid development and dissemination of 5G communication and IoT technologies, there are increasing demands for big data analysis techniques and service systems. In particular, explosively growing demands on AI technology adoption are also causing high competitions to take advantages of machine/deep-learning models to extract novel values from enormously collected data. In order to adopt AI technology to various research and application domains, it is necessary to prepare high-performance GPU-equipped systems and perform complicated settings to utilze deep learning models. To relieve the efforts and lower the barrier to utilize AI techniques, AIaaS(AI as a service) platform is attracting a great deal of attention as a promising on-line service, where the complexity of preparation and operation can be hidden behind the cloud side and service developers only need to utilize the high-level AI services easily. In this paper, we propose an AIaaS system which can support the creation of AI services based on Docker and OpenFaaS from the registration of models to the on-line operation. We also describe a case study to show how AI services can be easily generated by the proposed system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.21-27
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• 2020

The purpose of this study is to investigate the ecosystem structure underlying the development of artificial intelligence technology and related industries. In addition, the research on the AI business ecosystem based on AI technology and the ways to activate them was discussed. Ecosystems play a role in organically connecting producers, consumers, and decomposers. In the AI ecosystem, we classified the AI service producers, producers of AI services using the produced services, and data and related infrastructure services that are the basis of AI services. Stakeholders in the AI business ecosystem are the government and various private organizations that have a direct or indirect influence on AI service production, consumption, and operation. In Korea, in particular, the government plays a role as the most influential stakeholders. For example, the company contributes to the increase of producers, which are related to human resource development, and plays a catalyst role in the increase of services produced by R & D funding. In this study, the policy for revitalizing the AI business ecosystem includes (1) securing the environment for increasing producers, (2) spreading AI awareness among consumers, (3) securing data exchange and supply infrastructure, and (4) supporting services and related laws. Secure the system. This study is meaningful in that it contributes to and contributes to the construction of domestic AI-based environment and related research.

• Journal of Venture Innovation
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• v.6 no.4
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• pp.153-170
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• 2023

Generative AI services, including ChatGPT, were becoming increasingly active. This study aimed to empirically analyze the factors that promoted and hindered the diffusion of such services from a consumer perspective. Accordingly, a research model was developed based on the Value-based Adoption Model (VAM) framework, addressing both benefit and sacrifice factors. Benefits identified included usefulness and enjoyment, while sacrifices were security and hallucination. The study analyzed how these factors affected the intention to use generative AI services. A survey was conducted among college students for empirical analysis, and 200 valid responses were analyzed. The analysis utilized structural equation modeling with AMOS 24. The empirical results showed that usefulness and enjoyment had a significant positive impact on perceived value, while security and hallucination had a significant negative impact. The order of influence on perceived value was usefulness, hallucination, security, and then enjoyment. Perceived value had a significant positive impact on usage intention. Moreover, perceived value was found to mediate the relationship between usefulness, enjoyment, security, hallucination, and the intention to use generative AI services. These findings expanded the research horizon academically by validating the effectiveness of generative AI services based on existing models and demonstrated the continued importance of usefulness in a practical context.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.4
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• pp.179-200
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• 2023

Records management institutions in Korea generally face a situation where they lack the workforce to manage the vast amount of electronic records. If electronic records management tasks and archival information services can be automated and intelligentized, the workload can be reduced and the service satisfaction of users can be improved. Therefore, this study proposes to utilize "generative AI" technology in records management practice. To achieve this, the study first examined previous research that aimed to intelligently automate various tasks in the field of records management. The fundamental concepts of generative AI were subsequently outlined, and domestic cases of generative AI applications were investigated. Next, the scope of applying generative AI to the field of records management was defined, and specific utilization strategies were proposed based on this. Regarding the strategies, the effectiveness was verified by presenting results from applying commercial generative AI services or citing examples from other fields. Lastly, the benefits and implications of using generative AI technology in the field of records management, as well as limitations that must be addressed in advance, were presented. This study holds significance in that it identified tasks within the field of records management where generative AI technology can be integrated and proposed effective utilization strategies tailored to those tasks.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.597-599
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• 2022

When IoT device performs on-device AI, the device is required to use various AI models selectively according to target service and surrounding environment. Also, AI model can be updated by additional training such as federated learning or adapting the improved technique. Hence, for successful on-device AI, IoT device should acquire various AI models selectively or update previous AI model to new one. In this paper, we propose AI model repository to tackle this issue. The repository supports AI model registration, searching, management, and deployment along with dashboard for practical usage. We implemented it using Node.js and Vue.js to verify it works well.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.115-123
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• 2024

The purpose of this study is to contribute to how the advantages of artificial intelligence (AI) services and the associated limitations can be simultaneously overcome, using the keywords AI and risk management. To achieve this, two cases were introduced: (1) presenting a risk monitoring process utilizing AI and (2) introducing an operational toolkit to minimize the emerging limitations in the development and operation of AI services. Through case analysis, the following implications are proposed. First, as AI services deeply influence our lives, the process are needed to minimize the emerging limitations. Second, for effective risk management monitoring using AI, priority should be given to obtaining suitable and reliable data. Third, to overcome the limitations arising in the development and operation of AI services, the application of a risk management process at each stage of the workflow, requiring continuous monitoring, is essential. This study is a research effort on approaches to minimize limitations provided by advancing artificial intelligence (AI). It can contribute to research on risk management in the future growth and development of the related market, examining ways to mitigate limitations posed by evolving AI technologies.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.2
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• pp.167-177
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• 2022

Unlike previous studies on AI chatbot preference that focused mostly on satisfaction, this study considered both satisfaction and dissatisfaction. This study established that (1) AI chatbot preference is driven by attractive, must-be, and one-dimensional qualities, (2) AI chatbot need to develop service strategies by taking into account users' satisfaction and dissatisfaction in accordance with preference drivers, and (3) users view interaction as a requisite and thus, if they are not satisfied with services of a AI chatbot, they don't tend to appeal their opinion and leave the service with AI chatbot. This study emphasizes that a AI chatbot that desires to be a dominant market player must provide differentiated services according to the preference drivers and must continuously encourage user participation in order to improve service quality.

• Journal of Information Technology Services
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• v.22 no.2
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• pp.23-40
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• 2023

Despite the growing interest and normative discussions on AI ethics, there is a lack of discussion on policy instruments that are necessary for companies to develop AI-based services in compliance with ethical principles. Thus, the purpose of this study is to explore policy instruments that can encourage companies to voluntarily comply with and adopt AI ethical standards and self-checklists. The study reviews previous research and similar cases on AI ethics, conducts interviews with AI-related companies, and analyzes the data using AHP to derive action plans. In terms of desirability and feasibility, Research findings show that policy instruments that induce companies to ethically develop AI-based services should be prioritized, while regulatory instruments require a cautious approach. It was also found that a consulting support policy consisting of experts in various fields who can support the use of AI ethics, and support for the development of solutions that adhere to AI ethical standards are necessary as incentive policies. Additionally, the participation and agreement of various stakeholders in the process of establishing AI ethical standards are crucial, and policy instruments need to be continuously supplemented through implementation and feedback. This study is significant as it presents the necessary policy instruments for companies to develop ethical AI-based services through an analytical methodology, moving beyond discursive discussions on AI ethical principles. Further analysis on the effectiveness of policy instruments linked to AI ethical principles is necessary for establishing ethical AI-based service development.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.227-229
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• 2021

본 논문에서는 노약자 및 장애인의 증가로 인한 조행보조기구 사용량이 증가하고 있으나 물리적인 보조기구는 있지만 AI를 통한 서비스와 보조보행기구에 관한 AI 데이터셋이 부족하다. 이러한 문제점을 보안하기 위해 본 논문에서는 상기 데이터셋을 설계 및 구축하기 위해 Node JS를 사용하여 이미지 크롤링 프로그램을 구현하여 이미지 데이터를 수집했으며, Yolo Maker를 활용하여 수집된 이미지를 데이터셋으로 변환시켰다. 이를 통해 노약자 및 장애인을 위한 AI 서비스 구축에 필요한 데이터를 손쉽게 설계 및 구축한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.274-276
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• 2021

As artificial intelligence develops rapidly, we can experience it in our everyday life such as with medical, education, and game applications. Traditional SW services were programmed explicitly by the intention of the programmer, and we have conducted evaluation on it. However, due to the uncertianty of AI services, risk follows to the products. Therefore, UX evaluations need to be different from traditional UX evaluations. Therefore, in this paper we suggest a AI-UX framework that consideres the task delegability, UX evaluations metrics, and individual differences.