• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.7-13
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• 2023

This study investigated the criteria for evaluating the impact of artificial intelligence services. The study classified AI evaluation targets into two areas: AI service and AI technology, and identified influence, sustainability, efficiency, effectiveness, and appropriateness as potential evaluation criteria. The time aspect of AI service evaluation was divided into pre-evaluation and post-evaluation, with pre-evaluation focused on reviewing items during development and design. The AI service area was classified into public, private, and mixed forms, and the impact assessment was classified as vertical or horizontal. The application of AI services was divided into normative and regulatory aspects, and the purpose of the evaluation could be impact or process evaluation. The subject and field of the AI service could also be used for classification purposes. The results of this study can be used to support the creation of AI service impact policies and countermeasures. However, further research is needed to develop specific indicators based on the criteria identified in this study to evaluate the impact of AI services.

• 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.

• 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.

• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.147-157
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• 2022

The purpose of this study is to establish policy recommendations for the promotion of AI service impact assessment based on the definition of impact assessment and analysis of domestic and foreign AI service impact assessment cases. The direction of implementation was analyzed based on the case of impact evaluation promoted in various fields at home and abroad and the case of impact evaluation at home and abroad of artificial intelligence services. As a step-by-step implementation plan, in the first stage, quantitative indicators such as AI level survey-based economic effects are developed, and in the second stage, information culture such as safety and reliability and artificial intelligence ethics described in the Framework Act on Intelligence Information, social, economic, information protection, and people's daily lives are prepared. In the third stage, discussion on detailed metrics and methods will be expanded and impact assessment results will be evaluated. This study requires analysis through various participants such as policy designers, artificial intelligence service developers, and civic groups in the future.

• 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.

• Science of Emotion and Sensibility
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• v.22 no.2
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• pp.49-58
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• 2019

In the era of the 4th Industrial Revolution, artificial intelligence (AI) has become one of the core technologies in terms of the business strategy among information technology companies. Both international and domestic major portal companies are launching AI search services. These AI search services utilize voice, images, and other unstructured data to provide different experiences from existing text-based search services. An unfamiliar experience is a factor that can hinder the usability of the service. Therefore, the usability testing of the AI search services is necessary. This study examines the usability of the AI search service on the Naver App 8.9.3 beta version by comparing it with the search services of the current Naver App and targets 30 people in their 20s and 30s, who have experience using Naver apps. The usability of Smart Lens, Smart Voice, Smart Around, and AiRS, which are the Naver App beta versions of their artificial intelligence search service, is evaluated and statistically significant usability changes are revealed. Smart Lens, Smart Voice, and Smart Around exhibited positive changes, whereas AiRS exhibited negative changes in terms of usability. This study evaluates the change in usability according to the application of the artificial intelligence search services and investigates the correlation between the evaluation factors. The obtained data are expected to be useful for the usability evaluation of services that use AI.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.15-21
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• 2024

The purpose of this study is to propose a framework for the introduction and evaluation of artificial intelligence (AI) services not only in general applications but also in public policies. To achieve this, the study explores AI service management and governance toolkits, providing insights into how to introduce AI services in public policies. Firstly, it offers guidelines on the direction of AI service development and what aspects to avoid. Secondly, in the development phase, it recommends using the AI governance toolkit to review content through checklists at each stage of design, development, and deployment. Thirdly, when operating AI services, it emphasizes the importance of adhering to principles related to 1) planning and design, 2) the lifecycle, 3) model construction and validation, 4) deployment and monitoring, and 5) accountability. The governance perspective of AI services is crucial for mitigating risks associated with service provision, and research in risk management aspects should be conducted. While embracing the advantages of AI, proactive measures should be taken to address limitations and risks. Efforts should be made to efficiently formulate policies using AI technology to create high value and provide meaningful societal impacts.

• Journal of Korean Library and Information Science Society
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• v.52 no.1
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• pp.155-178
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• 2021

In the era of the 4th industrial revolution, public libraries need a strategy for promoting intelligent library services in order to actively respond to changes in the external environment such as artificial intelligence. Therefore, in this study, based on the concept of artificial intelligence and analysis of domestic and foreign artificial intelligence related trends, policies, and cases, we proposed the future direction of introduction and development of artificial intelligence services in the library. Currently, the library operates a reference information service that automatically provides answers through the introduction of artificial intelligence technologies such as deep learning and natural language processing, and develops a big data-based AI book recommendation and automatic book inspection system to increase business utilization and provide customized services for users. Has been provided. In the field of companies and industries, regardless of domestic and overseas, we are developing and servicing technologies based on autonomous driving using artificial intelligence, personal customization, etc., and providing optimal results by self-learning information using deep learning. It is developed in the form of an equation. Accordingly, in the future, libraries will utilize artificial intelligence to recommend personalized books based on the user's usage records, recommend reading and culture programs, and introduce real-time delivery services through transport methods such as autonomous drones and cars in the case of book delivery service. Service development should be promoted.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.20-33
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• 2021

This study is to suggest improvements of personal information protection in South Korea, according to requiring the safety of process and protection of personal information. Accordingly, based on data collection and analysis through literature research, this study derived the issues and suitable standards of personal information for major artificial intelligence services. In addition, this cases studies were reviewed, focusing on the legal compliance and porcessing compliance for personal information proection in major countries. And it suggested the improvement plan applied in South Korea. As the results, in legal compliance, it is required reorganization of related laws, responsibility and compliance to develop and provide AI, and operation of risk management for personal information protection laws in AI services. In terms of processing compliance, first, in pre-processing and refining, it is necessary to standardize data set reference models, control data set quality, and voluntarily label AI applications. Second, in development and utilization of algorithm, it is need to establish and apply a clear regulation of the algorithm. As such, South Korea should apply suitable improvement tasks for personal information protection of safe AI service.