• The Journal of the Korea Contents Association
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• v.19 no.9
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• pp.1-10
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• 2019

The purpose of this study is to investigate the influence of exogenous variables on the intention to use AI speaker. An online survey was administrated to 305 AI speaker users in order to examine the effect of the personal characteristics (self-efficacy, innovativeness, suitability, and enjoyment) and social impact (social conformity and social image) on perceived usefulness and easiness. The results indicate that (1) self-efficacy and social conformity have positively effect on perceived easiness; (2) suitability and social image have positively effect on perceived usefulness whereas innovativeness has negatively effect on perceived usefulness; (3) perceived usefulness and perceived easiness have significant effect on the intention to use AI speaker.

• Smart Media Journal
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• v.12 no.8
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• pp.60-68
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• 2023

After COVID-19, hotel industry is rapidly experiencing changes in the business environment, and under the influence of the Fourth Industrial Revolution, hotel industry is striving to secure competitive advantages through differentiation, including the use of big data and the IoT in service provision, as well as the introduction of artificial intelligence(AI) robot services. This study analyzed the perceived value of AI robot services and their impact on usage attitudes and behavioral intentions of customers who have used hotels that have introduced AI robot services. The results of the study showed that the value of robot services perceived by customers who have used robot services in hotels is categorized into three dimensions: social, experiential, and functional, and all of them have a positive effect on usage attitudes, with social, functional, and experiential values having a positive effect on usage attitudes in that order. Attitude toward use was also analyzed to have a positive effect on behavioral intention, which is consistent with the value-attitude-behavior model. Therefore, it is necessary for hotels to improve the satisfaction of hotel guests through diversified services of AI robot service.

• Korean Journal of Cognitive Science
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• v.33 no.4
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• pp.169-203
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• 2022

As artificial intelligence (AI) technology advances, the number of cases in which AI becomes an object or subject of moral judgment is increasing, and this trend is expected to accelerate. Although the area of AI in human society expands, relatively few studies have been conducted on how people perceive and respond to AI. Three studies examined the effect of the anthropomorphism of AI on its responsibility. We predicted that anthropomorphism would increase the responsibility perception, and perceived agency and perceived patiency for AI would mediate this effect. Although the manipulation was not effective, multiple analyses confirmed the indirect effect of perceived patiency. In contrast, the effect of perceived agency of AI was somewhat mixed, which makes the hypothesis partially supported by the overall result. This result shows that for the moral status of artificial agents, perceived patiency is relatively more critical than perceived agency. These results support the organic perspective on the moral status that argues the importance of patiency, and show that patiency is more important than agency in the anthropomorphism related study of AI and robots.

• Journal of Veterinary Clinics
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• v.37 no.5
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• pp.235-241
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• 2020

We aimed to determine the effect of timed artificial insemination (TAI) protocols on the pregnancy rate per insemination and pregnancy loss compared with AI performed at detected estrus in dairy cows and Korean Hanwoo cattle under heat stress. In dairy cattle, 1,250 sets of data that underwent AI during heat stress (temperature-humidity index ≥ 72) were categorized according to their TAI protocols or as controls: 1) PGF_2α-36 h-estradiol benzoate (EB)-36 h-TAI (PG-EB group, n = 113); 2) GnRH-7 days-PGF_2α-56 h-GnRH-16 h-TAI (Ovsynch group, n = 455); or 3) GnRH-6 days-Ovsynch (G6G group, n = 136). The remaining cows underwent AI at detected estrus (AIDE group, n = 546). The probability of pregnancy per AI 45 days after AI was higher (P < 0.01) in the PG-EB (odds ratio [OR]: 1.68), Ovsynch (OR: 1.48), and G6G (OR: 1.79) groups than in the AIDE group. However, the prevalence of pregnancy loss between 30 and 45 days after AI did not differ among the groups. In Hanwoo cattle, 617 sets of data inseminated artificially under heat stress were categorized into AIDE (n = 281), PG-EB (n = 194), and combined Ovsynch or G6G (n = 142) groups. The probability of pregnancy per AI 45 days after AI and the prevalence of pregnancy loss between 30 and 45 days after AI did not differ among the groups. Thus, implementation of a TAI protocol (PG-EB, Ovsynch, or G6G) in dairy cows under heat stress improves the pregnancy rate per AI versus AIDE, whereas there is no beneficial effect of TAI on the pregnancy rate of Hanwoo cattle under heat stress.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.149-158
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• 2019

In this study, the concept of emotional labor and AI(appreciative inquiry) are connected to examine how acceptance of AI, which is related to changes in hospital organizational culture, affects nurses' emotional labor, organizational commitment, and job satisfaction. For this purpose, the data collected from 156 nurses working at a major hospital were analyzed using structural equation modeling. The findings of this study are as follows: First, nurses' acceptance of AI had a significant positive effect on deep acting but not on surface acting. Second, deep acting had a significant positive effect on organizational commitment, but surface acting did not. Third, nurses' organizational commitment had a significant positive effect on job satisfaction. Fourth, deep acting significantly mediated the relationship between nurses' acceptance of AI and organizational commitment, but surface acting did not. Fifth, deep acting and organizational commitment significantly mediated the relationship between nurses' acceptance of AI and job satisfaction, but surface acting and organizational commitment did not. Theoretical and practical implications are provided based on the relationships between the variables found in this study.

• Korean Journal of Weed Science
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• v.8 no.3
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• pp.237-243
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• 1988

Field study was conducted to evaluate safening effect of fenclorim (4,6-dichloro-2-phenyl pyrimidine) against benthiocarb, butachlor, and pretilachlor injury in rice plants under vinyl-covered subirrigated seedbed. Combinated application of benthiocarb 210, and 315 g ai/10a with fenclorim 10 g ai/10a or higher concentration, butachlor 180, and 270 g ai/10a with fenclorim 20 g ai/10a or higher concentration, and pretilachlor 60, and 90 g ai/10a with fenclorim 30 g ai/10a reduced herbicide injury of rice, and thus increased standing, plant height, tillers, and dry weight of rice plants compared to no combined application of fenclorim.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.127-128
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• 2023

The construction industry is increasingly adopting vision AI technologies to improve efficiency and safety management. However, the complex and dynamic nature of construction sites can pose challenges to the accuracy of vision AI models trained on datasets that do not consider the background. This study investigates the effect of background on object recognition for vision AI in construction sites by constructing a learning dataset and a test dataset with varying backgrounds. Frame scaffolding was chosen as the object of recognition due to its wide use, potential safety hazards, and difficulty in recognition. The experimental results showed that considering the background during model training significantly improved the accuracy of object recognition.

• The Journal of Information Systems
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• v.28 no.2
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• pp.25-52
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• 2019

Purpose Despite the recent increase in the use of selection tools using artificial intelligence (AI), far less is known about the effectiveness of them in recruitment and selection research. Design/methodology/approach This paper tests the impact of AI-based initial screening and interview on intentions to apply. We also examine the moderating role of individual difference (i.e., reliability on technology) in the relationship. Findings Using policy-capturing with undergraduate students at a large university in South Korea, this study showed that AI-based interview has a negative effect on intentions to apply, where AI-based initial screening has no effect. These results suggest that applicants may have a negative feeling of AI-based interview, but they may not AI-based initial screening. In other words, AI-based interview can reduce application rates, but AI-based screening not. Results also indicated that the relationship between AI-based initial screening and intentions to apply is moderated by the level of applicant's reliability on technology. Specifically, respondents with high levels of reliability are more likely than those with low levels of reliability to apply for firms using AI-based initial screening. However, the moderating role of reliability was not significant in the relationship between the AI interview and the applying intention. Employing uncertainty reduction theory, this study indicated that the relationship between AI-based selection tools and intentions to apply is dynamic, suggesting that organizations should carefully manage their AI-based selection techniques throughout the recruitment and selection process.

• Journal of Korean Society for Quality Management
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• v.50 no.1
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• pp.43-61
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• 2022

Purpose: The purpose of this study was verifying factors that affect to intention to use AI financial services and finding a way of building an user oriented AI ecology. Methods: This study used the UTAUT (Unified Theory of Acceptance and Use of Technology) model with independent variables such as performance expectancy, effort expectancy, social influence, facilitating conditions, trust, personal innovativeness and AI understanding as moderating variable. The data was collected through online & offline survey with questionnaire from 330 financial customers. Results: As a result, the analysis suggested that the performance expectancy, social influence, facilitating conditions, personal innovativeness are statistically significant to the intention to use AI. It was also found that AI knowledge of users differently influence the intention to use through the moderating effect on the facilitating conditions. Conclusion: Performance expectancy, social influence, facilitating conditions, personal innovativeness have positive causation to the intention to use in AI financial service. On the facilitating conditions, unlike other variables, it was found that the user's intention to use was different by the level of AI understanding. It means that customers could have the strong intention to use AI even though they don't have enough pieces of knowledge on the factors. Customers seem to be of recognition that the technology has certain benefits for themselves. The facilitating factors are significantly affected by AI understanding and differently effect on the intention to use AI.

• Journal of Korean Critical Care Nursing
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• v.12 no.3
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• pp.13-23
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• 2019

Purpose : The purpose of this study was to determine whether appreciative inquiry (AI) is an effective intervention for increasing the positive psychological capital and organizational commitment of new nurses. Method : The study used a nonequivalent control group pretest-posttest design. The participants were 60 new nurses in a tertiary hospital in Seoul. The experimental group received 2 classes of AI education and in-unit AI activities. The control group received the existing education program. Results : There was no statistically significant difference in the positive psychological capital and organizational commitment between the experimental group and the control group over time. Satisfaction with the AI education scored 3.69, which was higher than the average. The reason why the experimental group members were satisfied with the program was that AI education helped them to adapt and the in-unit AI activities made staff more cooperative and the atmosphere of the unit more positive. Conclusion : When applying AI activities to new nurses to promote positive psychological capital and organizational commitment, it is necessary to provide a workshop in which the participants can fully concentrate on education and to extend the period of use to one year in order to maintain the effect of AI activities.