• Journal of Digital Convergence
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• v.19 no.3
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• pp.217-225
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• 2021

This study analyzed the perception formed by artificial intelligence users by converging technology readiness index and technology acceptance models and expanding them to models considering artificial intelligence ethics in order to find out the impact of technology acceptance and ethics. Independent variables include optimism, transparency, ethical awareness, user-centeredness, perceived usefulness and perceived ease of use as potential variables affected by independent variables, and defined the intention of use as potential variables as dependent variables. The survey results from an online and offline of men and women aged over 17 years old across the country (N=260) from September 5 to October 12, 2020 were used in the analysis. The findings, first, showed that optimism had a significant static effect on perceived usefulness and ease of use. Second, ethical awareness (transparency, ethical awareness, user-centeredness) did not have a significant impact on perceived usefulness and ease of use. Third, perceived usefulness and ease of use are finally found to have a significant static effect on the intention of use. Fourth, perceived usefulness has a relatively high influence over ease of use.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.12
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• pp.329-342
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• 2021

The pharmaceutical industry is experiencing a productivity crisis with a low probability of success despite a long period of time and enormous cost. As a strategy to solve the productivity crisis, the use cases of Artificial Intelligence(AI) and Bigdata are increasing worldwide and tangible results are coming out. However, domestic pharmaceutical companies are taking a wait-and-see attitude to adopt AI platform for drug research. This study proposed a research model that combines the Value-based Adoption Model and the Innovation Resistance Model to empirically study the effect of value perception and resistance factors on adopting AI Platform. As a result of empirical verification, usefulness, knowledge richness, complexity, and algorithmic opacity were found to have a significant effect on perceived values. And, usefulness, knowledge richness, algorithmic opacity, trialability, technology support infrastructure were found to have a significant effect on the innovation resistance.

• Korean Journal of Artificial Intelligence
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• v.7 no.2
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• pp.19-24
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• 2019

Lung cancer is a chronic disease which ranks fourth in cancer incidence with 11 percent of the total cancer incidence in Korea. To deal with such issues, there is an active study on the usefulness and utilization of the Clinical Decision Support System (CDSS) which utilizes machine learning. Thus, this study reviews existing studies on artificial intelligence technology that can be used in determining the lung cancer, and conducted a study on the applicability of machine learning in determination of the lung cancer by comparison and analysis using Azure ML provided by Microsoft. The results of this study show different predictions yielded by three algorithms: Support Vector Machine (SVM), Two-Class Support Decision Jungle and Multiclass Decision Jungle. This study has its limitations in the size of the Big data used in Machine Learning. Although the data provided by Kaggle is the most suitable one for this study, it is assumed that there is a limit in learning the data fully due to the lack of absolute figures. Therefore, it is claimed that if the agency's cooperation in the subsequent research is used to compare and analyze various kinds of algorithms other than those used in this study, a more accurate screening machine for lung cancer could be created.

• Clinical Endoscopy
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• v.57 no.3
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• pp.302-308
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• 2024

With incessant advances in information technology and its implications in all domains of our lives, artificial intelligence (AI) has emerged as a requirement for improved machine performance. This brings forth the query of how this can benefit endoscopists and improve both diagnostic and therapeutic endoscopy in each part of the gastrointestinal tract. Additionally, it also raises the question of the recent benefits and clinical usefulness of this new technology in daily endoscopic practice. There are two main categories of AI systems: computer-assisted detection (CADe) for lesion detection and computer-assisted diagnosis (CADx) for optical biopsy and lesion characterization. Quality assurance is the next step in the complete monitoring of high-quality colonoscopies. In all cases, computer-aided endoscopy is used, as the overall results rely on the physician. Video capsule endoscopy is a unique example in which a computer operates a device, stores multiple images, and performs an accurate diagnosis. While there are many expectations, we need to standardize and assess various software packages. It is important for healthcare providers to support this new development and make its use an obligation in daily clinical practice. In summary, AI represents a breakthrough in digestive endoscopy. Screening for gastric and colonic cancer detection should be improved, particularly outside expert centers. Prospective and multicenter trials are mandatory before introducing new software into clinical practice.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.205-212
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• 2021

The purpose of this study is to analyze elementary school students' interest in virtual reality(VR) technology, usability, and the possibility of learning media. In particular, it is intended to be used for content creation for artificial intelligence(AI) education in the future. The effectiveness of elementary education using virtual reality technology was confirmed through the analysis of overseas research, and the applicability to elementary school students in Korea was analyzed. To proceed with the analysis, various virtual reality contents were provided to 5th grader of elementary school, and then, interest, usability, usefulness, and possibility of use in class and learning were surveyed. As a result of the study, it was confirmed that students' interest in virtual reality contents was very high, and that it could be used sufficiently as a learning medium. It suggests that it can be used in artificial intelligence education and data science education, which have recently been emphasized in importance. In particular, virtual reality can be used to simulate abstract data and artificial intelligence.

• Journal of the Korea Society of Computer and Information
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• v.25 no.1
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• pp.199-206
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• 2020

In this study, the factors affecting consumers' intention to use AI speakers were focused on the perceived value of the product and the perceived necessity of the product. Factors affectationist consumers' perceived value of the product were divided into benefits and costs. Reflecting the characteristics of information technology products, I included perceptions of usefulness of products. Empirical results show that consumers' perceptions of perceived benefits and usefulness of AI speaker products have a positive effect on perceived value and perceived necessity. Perception of necessity had a positive (+) significant effect on perception of value. Perception of necessity and perception of value had a positive(+) and positive effect on each intention of use. However, the cost perceived by consumers did not have a significant effect on perception of value.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.205-219
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• 2021

The present study identified determinants to user acceptance of artificial intelligence(AI)-based news anchor. Our conceptual model included three constructs of ability, benevolence, and integrity to determine whether these three constructs are predictive of trust perceived from AI news anchor. This work further examined the influences of social presence, anthropomorphism, perceived usefulness, understanding as well as trust as immediate determinants to user acceptance. The conceptual model was validated on survey data collected from 513 respondents. A series of scale refinement process was conducted by the examination of data normality, common method bias, structure of latent variables as well as internal consistency. In addition, a confirmatory factor analysis was performed to assess the extent to which the sample data collected from survey study measures the constructs adequately. The results from the analysis of structural equation model indicated that, (1) two constructs of ability and integrity were found to be significantly predictive of perceived trust, and (2) anthropomorphism, perceived usefulness, and trust emerged as significant and positive predictors of user acceptance of AI-based news anchor.

• Journal of Information Technology Services
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• v.20 no.6
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• pp.1-16
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• 2021

The health functional food market continues to grow, and according to that trend, the subdivision sales of personalized health functional foods, which have been legally prohibited, will be operated as a special regulatory pilot project. Personalized health functional food recommendations have a variety of personalized indicators to consider, and it is believed that algorithmic methods will be needed to proceed in a customized manner considering all of them. This study aims to contribute to the development of the AI-based health functional food recommendation service by studying factors that affect the use of the AI-based health functional food recommendation service. This paper analyzed the intention of use for AI-based health functional food recommendation service based on the information system success model and Technology Acceptance Model. This study considered information quality factors, service quality factor, and system quality factor as independent variables influencing perceived usefulness, perceived ease of use and trust. For empirical analysis, 406 questionnaires were used and the collected data were performed using AMOS 22.0 and SPSS 22.0. Research has shown that the accuracy, timeliness, empathy and availability have a positive effect on usefulness. Understandability and availability has been shown to have a positive effect on ease of use. The accuracy, understandability, empathy and availibility has been shown to have a positive impact on Trust. Usefulness, ease of use and trust all have been shown to have a positive influence on intention of use.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.3
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• pp.464-480
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• 2022

With the steady development of Artificial Intelligence (AI), online stores are adopting chatbot services as virtual shopping assistants. This study proposes the concept of para-social presence to explore the undiscovered role of fashion chatbots' emotional and relational characteristics on service acceptance. Based on the Technology Acceptance Model (TAM), this study investigates the effect of a chatbot's para-social presence on service acceptance intention through consumers' beliefs. The web-based experiment was conducted on adult consumers who experienced chatbot services in an online shopping situation. A total of 247 responses were analyzed using confirmatory factor analysis, structural equation modeling, and multi-group SEM by AMOS 21.0 and SPSS 23.0. The findings illustrate that the chatbot's intimacy positively influenced consumers' perceived enjoyment, while the chatbot's understanding had a significant effect on perceived usefulness and ease of use. The chatbot's involvement had a positive effect on all consumer beliefs. Moreover, perceived ease of use had a positive influence on usefulness. A greater level of perceived usefulness and enjoyment positively heightened consumers' service acceptance intention. This study also verifies the moderating role of a need for human interaction. Consumers with a high need for human interaction have a relatively low tendency to perceive chatbot services as useful.

• Journal of Oriental Neuropsychiatry
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• v.35 no.2
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• pp.153-162
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• 2024

Objectives: Among OECD countries, South Korea has been having the highest suicide rate since 2018, with 24.1 deaths per 100,000 people reported in 2020. The objectie of this study was to examine the use of generative artificial intellicence (AI) chatbots to train third-year Korean medicine (KM) students in conducting suicide risk assessments for patients with depressive disorders to train students for their clinical practice skills. Methods: The Claude 3 Sonnet model was utilized for chatbot simulations. Students performed mock consultations using standardized suicide risk assessment tools including Ask Suicide-Screening Questions (ASQ) tool and ASQ Brief Suicide Safety Assessment. Experiences and attitudes were collected through an anonymous online survey. Responses were rated on a 1~5 Likert scale. Results: Thirty-six students aged 22~30 years participated in this study. Their scores for interest and appropriateness (4.66±0.57), usefulness (4.60±0.61), and overall experience (4.63±0.60) were high. Their evaluation of the usability of artificial intelligence chatbot was also high at 4.58±0.70 points. However, their trust in chatbot responses (Q12) was lower (3.86±0.99). Common issues related to dissatisfaction included conversation disruptions due to token limits and inadequate chatbot responses. Conclusions: This is the first study investigating generative AI chatbots for suicide risk assessment training in KM education. Students reported high satisfaction, although their trust in chatbot accuracy was moderate. Technical limitations affected their experience. These preliminary findings suggest that generative AI chatbots hold promise for clinical training, particularly for education in psychiatry. However, improvements in response accuracy and conversation continuity are needed.