• Title/Summary/Keyword: AI 선호도

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Understanding the Impact of Perceived Empathy on Consumer Preferences for Human and AI Agents in Healthcare and Financial Services (의료 및 금융 서비스에서 인간-AI 에이전트 선호도에 소비자가 지각하는 공감 능력의 중요성이 미치는 영향)

  • Ga Young Lim;Aekyoung Kim
    • Knowledge Management Research
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    • v.25 no.2
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    • pp.155-176
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    • 2024
  • This study explores variations in preferences for human and AI agents within the medical and financial services. Study 1 investigates whether there are preferential disparities between human and AI agents across these service domains. It finds that human agents are favored over AI agents in medical services, while AI agents receive greater preference in the financial services. Study 2 delves into the underlying reasons for the preference differentials between human and AI agents by assessing the significance of certain capabilities as perceived by users in each domain. The findings reveal a mediating role of perceived empathy importance in the effect of service domains on human-AI preference. Furthermore, perceived empathy is deemed a more critical capability by users for preferring human over AI agents across both service domains compared to other capabilities such as experience and agency. This research is noteworthy for elucidating the variances in preferences for human and AI agents across medical and financial services and the rationale behind these differences. It enhances our theoretical comprehension of the pivotal factors influencing preferences for human and AI agents, underscoring the significance of human experiential capabilities like empathy.

Building a human rights corpus for interactive generation models (대화형 생성 모델을 위한 인권 코퍼스 구축)

  • Youngsook Song;angjin Sim;Seonghyun Kim
    • Annual Conference on Human and Language Technology
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    • 2023.10a
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    • pp.571-576
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    • 2023
  • 본 연구에서는 인권의 측면에서 AI 모델이 향상된 답변을 제시할 수 있는 방안을 모색하기 위해서 AI가 인권의 문제를 고민하는 전문가와 자신의 문제를 해결하고자 하는 사용자 사이에서 어느 정도로 도움을 줄 수 있는가를 정량적, 정성적으로 검증했다. 구체적으로는 국가인권위원회의 결정례와 상담사례를 분석한 후 이를 바탕으로 좀 더 나은 답변은 무엇인지에 대해 고찰하기 위해서 인권과 관련된 질의 응답 세트를 만든다. 질의 응답 세트는 인권 코퍼스를 학습한 모델과 그렇지 않은 모델의 생성 결과를 바탕으로 한다. 또한 생성된 질의 응답 세트를 바탕으로 설문을 실시하여 전문적인 내용을 담은 문장에 대한 선호도를 분석한다. 본 논문은 대화형 생성 모델이 인권과 관련된 주제에 대해서도 선호되는 답변을 제시할 수 있는가에 대한 하나의 대안이 될 수 있을 것이다.

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An Analysis of Educational Effectiveness of Elementary Level AI Convergence Education Program (초등 AI 융합교육 프로그램의 교육 효과성 분석)

  • Lee, Jaeho;Lee, Seunghoon;Lee, Donghyeong
    • Journal of The Korean Association of Information Education
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    • v.25 no.3
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    • pp.471-481
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    • 2021
  • The purpose of this study is to analyze the effectiveness of AI convergence education program. To this end, the "Elementary Science AI Convergence Education Program for Machine Learning" developed in previous research were taught to elementary school students in the fourth to sixth grades in eight times. The quantitative changes of each factor were analyzed by R program, and the effectiveness of education was analyzed by Pearson correlation and paired samples t-test. As a result, there is a deep correlation between "Attitude to AI technology, Scientific preference and STEAM Literacy" and technical average has improved in many factors. Therefore, AI convergence education program is meaningful in terms of education, and if AI education and AI convergence education are implemented into the primary formal education curriculum, they will have a positive effect.

A Study on Factors Affecting University Students' Satisfaction with YouTube AI Recommendation System (대학생들의 유튜브 AI 추천 시스템 만족도에 영향을 미치는 요인 분석 연구)

  • Zhu, LiuCun;Wang, Chao;Hwang, HaSung
    • Journal of Internet Computing and Services
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    • v.23 no.3
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    • pp.77-85
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    • 2022
  • Unlike previous studies that focused on the diversity of YouTube content, this study tried to identify factors affecting users' satisfaction with the YouTube recommendation system. Specifically, by adding content preference suitability and privacy concerns to the technology acceptance model, we empirically analyzed how these variables affect user's satisfaction of the YouTube AI recommendation system. For this purpose, asurvey was conducted on college students in their 20s and 30s, and the main research results are as follows. First, in the respondents of this study, playfulness and usefulness, which are major variables of the technology acceptance model, appeared as significant factors affecting the satisfaction of the YouTube AI recommendation system, whereas the effect of ease to use was not found. Second, content preference suitability was found to affect the satisfaction with AI recommendation system, but privacy concerns did not affect the satisfaction with YouTube AI recommendation system. Based on these research results, the implications of the study and the directions for future studies were suggested.

A Study on the Satisfaction and Dissatisfaction in AI Chatbot (인공지능 챗봇 서비스의 만족과 불만족에 관한 연구)

  • Yang, Chang-Gyu
    • 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.

Analysis of Daily Internet·Gaming·Smartphone Habit and Preference Factors of Moral Machine (인터넷·게임·스마트폰생활 습관과 모랄머신 선호도 요인 분석)

  • Park, SunJu
    • Journal of The Korean Association of Information Education
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    • v.24 no.1
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    • pp.21-28
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    • 2020
  • Technological advancements such as artificial intelligence, robots, and big data are revolutionizing the entire society. In this paper, we analyzed preliminary teachers' daily internet/gaming/smartphone habit and the difference between preference factors in gender and diagnosis group in the situation of ethical dilemma in driverless cars. The result shows most of the male students are in high risk group of daily internet/gaming usage, and male students tend to be more immersed in games compared to female students, which negatively affects their daily lives. Students who have at least one of the daily internet/gaming/smartphone habits are more likely to be classified as high-risk group in all three of daily internet/gaming/smartphone habit. Fortunately, the students perceived themselves addicted and wanted change their habits. An analysis by a moral machine of these students tells that there is no significant difference in preference between male and female students and among diagnosis groups. However, specifically in the ethical dilemma of driverless cars, all the groups of male, female, normal, high-risk showed they have priority in pedestrians over drivers, a large number of people over small, and people who obey traffic rules over who do not. The tendency was pronounced in female group and high-risk students prioritized people who are older and in lower social status.

Development and evaluation of course to educate pre-service and in-service elementary teachers about artificial intelligence (예비 및 현직 초등교사의 인공지능 교육을 위한 수업 콘텐츠의 개발 및 평가)

  • Jo, Junghee
    • Journal of The Korean Association of Information Education
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    • v.25 no.3
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    • pp.491-499
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    • 2021
  • Major countries in the world have established strategies for educating about artificial intelligence(AI) and with large investments are actively implementing these strategies. With this trend, domestic ministries have made efforts to establish national strategies to better educate students about AI. This paper presents the syllabus of AI classrooms which has been developed and presented to pre-service and in-service elementary school teachers for their use. In addition, the AI education tools they particularly preferred and their future plans for utilizing them in the elementary school classroom were investigated. Through this study, it was found that pre-service and in-service elementary school teachers strongly prefer lectures about AI education tools that can be immediately applied in the classroom, rather than learning about the theoretical basis of AI. At issue, however, is that the ability to utilize AI is usually based on a sufficient understanding of the theory. Thus, this paper suggests further study to identify better pedagogical practices to improve students' understanding the theoretical basis of AI.

Development of a data analysis system for preventing school violence based on AI unsupervised learning (AI 비지도 학습 기반의 학교폭력 예방 데이터 분석 시스템 개발)

  • Jung, Soyeong;Ma, Youngji;Koo, Dukhoi
    • Journal of The Korean Association of Information Education
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    • v.25 no.5
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    • pp.741-750
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    • 2021
  • School violence has long been recognized as a social problem, and various efforts have been made to prevent it. In this study, we propose a system that can prevent school violence by analyzing data on the frequency of conversations between students, friendship and preference to be in the same group. This data was quantified using a Likert scale questionnaire, and also grouped into the appropriate number of clusters using the K-means algorithm. Additionally, the homeroom teacher observed the frequency and nature of conversations between students, and targeted specific individuals or groups for counseling and intervention, with the aim of reducing school violence. Data analysis revealed that the teachers' qualitative observations were consistent with the quantified data based on student questionnaires, and therefore applicable as quantitative data towards the identification and understanding of student relationships within the classroom. The study has potential limitations. The data used is subjective and based on peer evaluations which can be inconsistent as the students may use different criteria to evaluate one another. It is expected that this study will help homeroom teachers in their efforts to prevent school violence by understanding the relationships between students within the classroom.

A Study on Chatbot Profile Images Depending on the Purpose of Use (사용 목적에 따른 챗봇의 프로필 이미지 연구)

  • Kang, Minjeong
    • The Journal of the Korea Contents Association
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    • v.18 no.12
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    • pp.118-129
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    • 2018
  • In AI chatbot service via a messenger, a profile image of the chatbot is the first thing that users see to communicate with the chatbot. This profile image not only manages an impression about the profile owner in SNS on followers, but also makes an important impression about chatbot services on users. Thus motivated, this study investigates proper profile images tailored for the types of chatbot services and users. Specifically, I reviewed the preferred images and expressions of chatbots for each purpose of chatbot service. Then, in a case study, I collected and analyzed the representative chatbot profile images for the purpose of fun and counseling. The profile images are categorized as robot, human, animal, and abstract images. Based on these categories, I surveyed the preferred profile image of the chatbot service in either the text type or image type alternatives. For the purpose of fun, in the text version, I found that both men and women preferred a human image to others. However, in the image version, men preferred woman and robot images while women preferred cute animation character and robot images. For counseling services, both men and women preferred woman and animal images most, which is similar to the results of the text version of questionnaires as well. While both genders consistently preferred real photo images, women tend to like abstract images more than men do. I expect that the results of this study would be useful to develop the proper profile images of AI chatbot for each service purpose.

A Study of Chatbot Personality based on the Purposes of Chatbot (사용목적에 따라 선호하는 챗봇의 성격에 관한 연구)

  • Kang, Minjeong
    • The Journal of the Korea Contents Association
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    • v.18 no.5
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    • pp.319-329
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    • 2018
  • With rapid development of technology for strong AI chatbot, the role of chatbot has been extended from conducting simple tasks to being a friend or counsellor. For this newly emerging purpose of chatbot, endowment of personality is important to make the chatbot regarded as a human being. Nevertheless I found that there are few guides about it. Thus, this study identifies the proper personality of chatbot depending on the purpose of services and user types. The purposes of chatbot services are divided into three types such as leisure-time, counselling, and task. The DISC theory is used for categorizing personality, which consists of 4 types such as dominance(D), inducement(I), submission(S), and compliance(C). An interview and survey were conducted to investigate the preferred personality of chatbot and contents for leisure-time. As results, people tend to prefer people-oriented types such as I, S for their leisure time, task-oriented types such as D,C for their task, and slow types such as C,S for counselling. Women prone to prefer neutral gender except for counselling and men tend to prefer female in all chatbot services. Preferred chatbot age is either same or younger age for leisure-time, same or older for counselling, and 30's for tasks. Preferred contents for leisure-time are mostly recent information but many 20's want fun contents and 50-70's want emphatic conversation. 30-50's want honorific but 20's and 60-70's don't care. The research results useful guide on proper personality of AI chatbot for each purpose of its service.