• Asia pacific journal of information systems
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• v.33 no.4
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• pp.1058-1092
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• 2023

This study investigates the perception and adoption of ChatGPT (a large language model (LLM)-based chatbot created by OpenAI) among Korean users and assesses its potential as the next disruptive innovation. Drawing on previous literature, the study proposes perceived intelligence and perceived anthropomorphism as key differentiating factors of ChatGPT from earlier AI-based chatbots. Four individual motives (i.e., perceived usefulness, ease of use, enjoyment, and trust) and two societal motives (social influence and AI anxiety) were identified as antecedents of ChatGPT acceptance. A survey was conducted within two Korean online communities related to artificial intelligence, the findings of which confirm that ChatGPT is being used for both utilitarian and hedonic purposes, and that perceived usefulness and enjoyment positively impact the behavioral intention to adopt the chatbot. However, unlike prior expectations, perceived ease-of-use was not shown to exert significant influence on behavioral intention. Moreover, trust was not found to be a significant influencer to behavioral intention, and while social influence played a substantial role in adoption intention and perceived usefulness, AI anxiety did not show a significant effect. The study confirmed that perceived intelligence and perceived anthropomorphism are constructs that influence the individual factors that influence behavioral intention to adopt and highlights the need for future research to deconstruct and explore the factors that make ChatGPT "enjoyable" and "easy to use" and to better understand its potential as a disruptive technology. Service developers and LLM providers are advised to design user-centric applications, focus on user-friendliness, acknowledge that building trust takes time, and recognize the role of social influence in adoption.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.505-508
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• 2022

Artificial intelligence itself has the value of advancing technology, and it is used in various industrial fields to enhance the added value of products and services produced in various industries. Therefore, regulations and policies related to artificial intelligence should be considered from a broader perspective. However, researchers have different understandings, and there is no agreement on how to regulate artificial intelligence. Therefore, we will examine the direction of government regulation on artificial intelligence technology in an exploratory manner. First, accountability, transparency, stability, and fairness are derived as the goals of artificial intelligence regulation, and the system itself, development process, and utilization process are set as the scope of regulation, and users and developers are subject to regulation. The academic significance of this study can be seen as analyzing the current level of artificial intelligence technology and laying the foundation for consistent discussions on artificial intelligence regulations in the future. Considering the life cycle from AI development to application, what is important is the balance of promotion policies to promote the artificial intelligence industry and regulatory policies to respond to the resulting risks. The goal of law related to artificial intelligence is to establish a system in which artificial intelligence can be accommodated in a positive direction to all participants, including developers, companies, and users.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.23-37
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• 2024

Digital twin is an M&S (Modeling and Simulation) technology designed to solve or optimize problems in the real world by replicating physical objects in the real world as virtual objects in the digital world and predicting phenomena that may occur in the future through simulation. Digital twins have been elaborately designed and utilized based on data collected to achieve specific purposes in large-scale environments such as cities and industrial facilities. In order to apply this digital twin technology to real life and expand it into user-customized service technology, practical but sensitive issues such as personal information protection and personalization of simulations must be resolved. To solve this problem, this paper proposes a federated learning-based accelerated client training method (FACTS) for personalized digital twins. The basic approach is to use a cluster-driven federated learning training procedure to protect personal information while simultaneously selecting a training model similar to the user and training it adaptively. As a result of experiments under various statistically heterogeneous conditions, FACTS was found to be superior to the existing FL method in terms of training speed and resource efficiency.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.2
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• pp.431-448
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• 2008

The change of management paradigm is that information technology change according to technology evolution at present is applied to corporate management, is that management level must be adapted to uncertainty management environment with activity and be made decision based on analyzed real time information through information system. This produces the effective target achievement and efficiency business productivity guarantee. At the present day, importation of business intelligence like enterprise information system has been the essential factor in business activities. Therefore, It is very important to give lessons the enterprises for building the business intelligence selecting the major success factors of more influence to managing results. In this paper, to authorize the research model and research constructions through theory study of literatures and surveying statics analysis prove the relational influences among the influencing factors related business intelligence system buliding.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1989-2011
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• 2019

Vehicle detection based on aerial images is an interesting and challenging research topic. Most of the traditional vehicle detection methods are based on the sliding window search algorithm, but these methods are not sufficient for the extraction of object features, and accompanied with heavy computational costs. Recent studies have shown that convolutional neural network algorithm has made a significant progress in computer vision, especially Faster R-CNN. However, this algorithm mainly detects objects in natural scenes, it is not suitable for detecting small object in aerial view. In this paper, an accurate and effective vehicle detection algorithm based on Faster R-CNN is proposed. Our method fuse a hyperactive feature map network with Eltwise model and Concat model, which is more conducive to the extraction of small object features. Moreover, setting suitable anchor boxes based on the size of the object is used in our model, which also effectively improves the performance of the detection. We evaluate the detection performance of our method on the Munich dataset and our collected dataset, with improvements in accuracy and effectivity compared with other methods. Our model achieves 82.2% in recall rate and 90.2% accuracy rate on Munich dataset, which has increased by 2.5 and 1.3 percentage points respectively over the state-of-the-art methods.

• Journal of Digital Convergence
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• v.17 no.7
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• pp.73-87
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• 2019

The purpose of this study is to clarify the continuous usage intention of artificial intelligence products and services. In this study, we try to define the artificial intelligence quality and preference on the online job information platform and investigate the effect of artificial intelligence on continues usage intention. A survey of artificial intelligence users was conducted and recalled 184. The empirical analysis shows that the artificial intelligence quality and preference have a positive effect on satisfaction, and that the satisfaction has significant effect on the intention of continuing use. but the artificial intelligence quality does not significantly affect the intention of continuing use. These results are expected to provide useful guidelines for artificial intelligence technology products or services in the future.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.4
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• pp.283-292
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• 2020

Artificial intelligence, which is one of the representative images of the 4th industrial revolution, has been highly recognized since 2016. This paper analyzed domestic paper trends for 'Artificial Intelligence', 'Machine Learning', and 'Deep Learning' among the domestic papers provided by the Korea Academic Education and Information Service. There are approximately 10,000 searched papers, and word count analysis, topic modeling and semantic network is used to analyze paper's trends. As a result of analyzing the extracted papers, compared to 2015, in 2016, it increased 600% in the field of artificial intelligence, 176% in machine learning, and 316% in the field of deep learning. In machine learning, a support vector machine model has been studied, and in deep learning, convolutional neural networks using TensorFlow are widely used in deep learning. This paper can provide help in setting future research directions in the fields of 'artificial intelligence', 'machine learning', and 'deep learning'.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.245-251
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• 2021

This work aims to focus on the current features and characteristics of Human Element and Artificial intelligence (AI), ask some questions about future information security, and whether we can avoid human errors by improving machine learning and AI or invest in human knowledge more and work them both together in the best way possible? This work represents several related research results on human behavior towards information security, specified with elements and factors like knowledge and attitude, and how much are they invested for ISA (information security awareness), then presenting some of the latest studies on AI and their contributions to further improvements, making the field more securely advanced, we aim to open a new type of thinking in the cybersecurity field and we wish our suggestions of utilizing each point of strengths in both human attributions in software security and the existence of a well-built AI are going to make better future software security.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.952-973
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• 2021

In recent years, mobile devices have become an essential part of daily life. More and more applications are being supported by mobile devices thanks to edge computing, which represents an emergent architecture that provides computing, storage, and networking capabilities for mobile devices. In edge computing, heavy tasks are offloaded to edge nodes to alleviate the computations on the mobile side. However, offloading computational tasks may incur extra energy consumption and delays due to network congestion and server queues. Therefore, it is necessary to optimize offloading decisions to minimize time, energy, and payment costs. In this article, different offloading models are examined to identify the offloading parameters that need to be optimized. The paper investigates and compares several optimization techniques used to optimize offloading decisions, specifically Swarm Intelligence (SI) models, since they are best suited to the distributed aspect of edge computing. Furthermore, based on the literature review, this study concludes that a Cuckoo Search Algorithm (CSA) in an edge-based architecture is a good solution for balancing energy consumption, time, and cost.

• Asia pacific journal of information systems
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• v.33 no.3
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• pp.624-651
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• 2023

The study makes several contributions to not only the adoption literature by examining the influence of Emotional Intelligence (EI) and Big-Five traits on adoption of Augmented Reality (AR) but also given its utility in both industry and research, it contributes to the interesting inter-disciplinary domain of psychology, information systems, and human behaviour. A quantitative based approach using a sample of 275 respondents was undertaken. It is found that emotional intelligence influence both perceived ease-of-use and perceived usefulness. They in turn influence intention to use. Another important observation is that personality traits (openness and agreeableness) have a significant moderating effect on the relation between attitude and intention to use AR. This research will help academicians and executives working on the adoption of AR in various sectors ranging from retail industry to the education sector. The originality of this study is that it explores the impact of EI on the acceptance of AR and helps in extending the literature in interdisciplinary research.