• 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.

• Journal of Digital Convergence
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• v.18 no.8
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• pp.217-224
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• 2020

The purpose of this study is to discuss implications for government policy aimed at increasing public's intention to accept AI. Knowledge regarding AI and feelings regarding AI were found to influence acceptance to intention towards AI. Hierarchical regression analysis was then conducted to explore the moderation effect of confidence in government on knowledge and feelings regarding AI. Results showed that as advanced knowledge regarding AI has a positive influence on acceptance intention towards AI and negative feelings regarding AI has a negative influence on acceptance intention towards AI. Feelings regarding AI had the highest impact on acceptance intention towards AI, followed by confidence in government and knowledge regarding AI. Results also revealed that a high level of confidence in government regulations was associated with greater acceptance intention towards AI and a low level of confidence in government regulations acceptance intention towards AI was more influenced by feelings regarding AI than by knowledge regarding AI. Furthermore, religion had a significant influence on acceptance intention towards AI, which provides one insightful direction for future research.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.241-249
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• 2022

Artificial intelligence is applied not only to the daily life of individuals but also to all industries, and it is no wonder that the age of artificial intelligence has arrived. Therefore it is important to understand the factors that influence the acceptance of AI. This study analyzes whether "AI Effect" which recognizes that commercialized or familiar artificial intelligence is no longer artificial intelligence, affects the acceptance of artificial intelligence and proposes an acceptance plan based on the results. Two experiments were conducted. The first experiment was conducted on 105 adults in the result it was found that 32.4% (34 people) had AI Effect, AI Effect existed in 43.6% (24 people) of women and 20% (10 people) of men, that is, the proportion of AI Effect exsitence in women is about twice as high.and AI Effect exists when the level of AI knowledge is low. The second experiment was conducted 240 adults and 85 participants with AI Effect were selected. We found the group that recognized experience of AI accepted AI more actively. Understanding of AI Effect is expected to suggest companies' views in order to enhance AI capabilities and acceptance. In addition, future studies are expected on considering individual differences or related to acceptance attitudes.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.284-293
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• 2020

The rapid progress of AI technology gives us the expectation to solutions to various problems in our society, and at the same time, it gives us anxiety about the side effects that can occur if AI develops beyond human control. This study was conducted in the early 20s with less objection to advanced devices. We attempted to provide clues to understand thoughts and attitudes of the targets about the future environment that will be brought by AI through the process of finding intent the acceptance of strong AI technology. For this, we applied the Theory of Planned Behavior, and further expanded this research model to identify factors affecting the attitude toward AI. As a result, the attitude toward AI and perceived behavioral control had a significant effect on the intention to use to strong AI. In addition, we found that the expectation of the benefit of improving task performance and the anxiety on the threat of relationship disturbance had a significant effect on the attitude toward AI. This study suggests implications for AI-related companies establishing the direction of technology development and for government setting a policy direction for AI adoption.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.325-338
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• 2022

This study was conducted to explore the acceptance behavior of undergraduate students toward telemedicine, which is temporarily allowed in the COVID-19. We applied social cognitive theory and technology acceptance model in order to reflect the convergence characteristics between medical service and digital technology of telemedicine. Based on these theoretical backgrounds, we investigated perception toward telemedicine and determinants of intention to accept telemedicine. To examine the research model and hypothesis, an online survey was conducted for college students who have not used telemedicine from September 8 to 10, 2021. A total of 184 data were collected, and multiple regression analysis was conducted using the SPSS 28.0 program. The results showed that health technology self-efficacy, usefulness and convenience benefits, social norm, and trust in telemedicine providers had positive effects on intention to accept telemedicine. This study is meaningful in that it selected undergraduate students, who are digital natives, as new targets for telemedicine, and presented the basic direction of strategies to target them.

• Korean Journal of Animal Reproduction
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• v.18 no.2
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• pp.95-99
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• 1994

The purpose of the present study was to determine the in vivo effect of oxytocin antagonist-I(Al) on uterine oxytocin receptor number (Rn) and/or binding affinity (Kd) in the estrous rat. Anesthetized rats were given a bolus infusion of control or 5${\mu}\textrm{g}$ of AI and sacri-ficed 0.5 and 4 hours later. The uterine tissue was removed, trimmed and frozen. Membrane oxytocin receptors were isolated after homogenization of uterine tissue and differential ultracentrifugation. The oxytocin receptor assay was performed by saturation with cold oxytocin competion with a high specific activity oxytocin antagonist. Rn and Kds were determined by nonlinear curve fitting methods. No differences(p>0.05) between the AI and control treated animals in either oxytocin receptor number or binding affinity was detected in this study. These data suggest that the major mode of action of AI is via competitive inhibition at the uterine oxytocin receptor and not by altering receptor number or binding affinity.

• 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.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.350-358
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• 2020

The objective of this empirical study is to examine the mediating and moderating effects of perceived risks on the relationship between knowledge, feelings and acceptance intention towards AI. Subjects in their teens to forties were surveyed and the final sample comprised 1,969 subjects. Data were analyzed using Mediation using Multiple Regression and Moderated Multiple Regression. Results showed that people's knowledge and feelings towards AI affected their acceptance intention of AI. Results also showed that the perceived risks of AI partially mediated and moderated the relationship between feelings and acceptance intention towards AI and moderated but not mediated the relationship between knowledge and acceptance intention towards AI. Overall, these results suggest that people's perceived risks of AI are associated more strongly with their feelings towards AI than their knowledge towards AI. Implications and directions for future research were discussed in relation to increasing general population's acceptance intention towards AI.

• Korean Journal of Cognitive Science
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• v.32 no.4
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• pp.169-191
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• 2021

With the development of artificial intelligence(AI), the jobs of many human experts are threatened, and this also applies to the legal profession. This study attempted to investigate whether AI can actually replace humans in the legal profession, especially the role of judges making final judgments. For this purpose, from the perspective of uniqueness neglect, this study was conducted to confirm the effect of involvement and the severity on acceptance of the judgment made by the AI judge (Experiment 1) and the AI jury (Experiment 2). The involvement was manipulated as if the subject who was sentenced for committing a crime was his or her family (mother, father) or stranger, and the severity was manipulated by the extent of the damage, the perception of the crime, and the number of applied crimes. In Experiment 1, the interactive effect of involvement and severity was found. Specifically, when the involvement was low, the acceptance of AI judges was higher in high severity (vs. low severity). Conversely, when the involvement was high, the acceptance of AI judges was higher in low severity (vs. high severity). The same interactions as in Experiment 1 occurred in Experiment 2. Specifically, when the involvement was low, a larger number of AI jury members were allocated in high severity (vs. low severity). On the other hand, when the involvement was high, the number of AI juries increased in low severity (vs. high severity). This study has implications in that it is the first experimental study in Korea on artificial intelligence legal judgment and that it presents the prospects for the jobs of legal experts.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.388-402
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• 2021

This study utilizes the theoretical framework of Extended Technology Acceptance Model to understand the governmental factors that affect the people's intention to use AI services. With the result of the analysis, as the expected impact of AI on fields related to effectiveness and accountability becomes higher, the intention of using AI service also got higher. In addition, the easier usability of e-government, the more active disclosure of their personal information, and the higher expectations for a hyper-connected society, their intention to use AI services became higher as well.