• 가정간호학회지
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• 제29권3호
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• pp.319-328
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• 2022

Purpose: This study investigated the relationship between artificial intelligence ethical awareness, bioethics awareness, and person-centered care of general hospital nurses. Methods: The participants were 192 nurses. Data were analyzed using descriptive statistics, t-test, analysis of variance, and Pearson's correlation coefficient with the SPSS program. Results: The average points for artificial intelligence ethical awareness, bioethics awareness, and person-centered care were 2.93, 2.77, and 3.50, respectively. Artificial intelligence ethical awareness and bioethics awareness had statistically significant negative relationships. Artificial intelligence ethical awareness, bioethics awareness, and person-centered care were not significantly correlated. Conclusion: Education, training, and organizational support are needed to improve artificial intelligence ethics awareness, bioethics awareness, and person-centered care for general hospital nurses.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제21권8호
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• pp.572-577
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• 2015

보통의 인공지능 시스템은 특정 작업을 수행하기 위해 설계되며, 해당 작업만을 수행하는 능력을 가진다. 그에 반해 인공 일반지능이란 설계 당시 목표로 한 작업만이 아니라 새로 접하는 다양한 문제에도 대응할 수 있는 인공지능을 의미한다. 최근 게임 인공지능 분야의 일반지능 문제인 General Video Game Playing에 대한 관심이 높아지고 있다. 비디오 게임으로 범위가 제한되었지만, 다양한 형태의 비디오 게임을 플레이 할 수 있는 단일 인공지능을 설계하는 것은 상당히 도전적인 문제이다. 본 논문에서는 Monte-Carlo Tree Search를 이용하는 기존 비디오 게임을 위한 인공 일반지능을 개선하는 방법에 대해 기술한다. 여기서는 UCB1 알고리즘을 문제에 적합하도록 개선한 GreedyUCB1과 게임 분석을 통해 얻은 지식을 활용한 Rollout 방법을 제안한다. 제안한 방법으로 개발된 인공지능은 국제 학술대회인 IEEE Computational Intelligence in Games의 2014년 인공지능 경진 대회에 출전하여 4위의 성적을 보였다.

• 인지과학
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• 제15권4호
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• pp.61-66
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• 2004

서양철학의 근간을 이루는 데카르트의 이성주의적 인간이해의 반성으로부터 등장한 구성주의는 지능을 포함한 인간이해의 새로운 대안이 될 수 있을 것으로 생각한다. 구성주의는 진화생물학, 진화심리학, 뇌과학, 시스템이론, 복잡계 이론의 성과뿐만 아니라 나아가 인문사회학의 경향과도 설명을 공유할 수 있는 많은 부분이 있다. 또한 인공지능 분야에서도 구성주의적 방법이라고 할 수 있는 연구가 진행되고 있다. 이 글에서는 구성주의적 관점에서 인공지능에서 다루는 지능에 대한 이해의 지평을 넓히고 이를 기반으로 한 방법론에 대한 검토와 그러한 경향에 있는 일부 인공지능 기술을 살펴보고자 한다. 이러한 논의를 통하여 여러 가지 관점의 마음에 대한 이론과 기술을 상호보완적으로 이해하고 다소 등한히 되고 있는 인공지능의 보편지능(general intelligence)의 토대로 삼고자 한다.

• 한국병원경영학회지
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• 제28권3호
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• pp.27-38
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• 2023

Objectives: This study explores the impact of age groups on social presence and trust among users of medical artificial intelligence chatbots. Furthermore, we investigate the existence of gender differences within these relationships. Method: We collected data through a survey from people who had interacted with general hospital chatbot services, either by making reservations or seeking consultations. Multiple linear regression analysis was conducted to examine the relationship between general characteristics of study population and social presence and trust of artificial intelligence chatbots. Additionally, we conducted stratified analysis to confirm the presence of gender differences within these relationship. Results: Among 300 participants, those aged 50 and older had higher social presence of artificial intelligence chatbots and greater trust of artificial intelligence chatbots (social presence, 𝛽=0.543, p=0.003; trust, 𝛽=0.787, p=0.000). In stratified by sex, women aged 50 and older had higher social presence and trust of artificial intelligence chatbots compared to those in their 30s age group (social presence, 𝛽 = 0.925, p=0.002; trust, 𝛽=0.645, p=:0.007). However, there was no statistically significant relationship between age and chatbot social presence and trust in men. Conclusion: This study demonstrates that advanced age plays a significant roles in users' social presence and trust in medical artificial intelligence chatbots. Futhermore, our findings reveal gender differences with women aged 50 and older showing the most substantial levels of social presence and trust. Therefore, it is expected that this finding can serve as valuable evidence to enhance the satisfaction of medical institution service users, offering crucial insights into the effective utilization of chatbot services.

• 디지털산업정보학회논문지
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• 제15권3호
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• pp.55-67
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• 2019

In this study, I researched whether consumers would adopt artificial intelligence speakers. A study was conducted on the motivations that arise when consumers want to use artificial intelligence speakers. Key motivational factors include needs and wants, and emotion is also included in the hypothesis as influencing the intended use. These factors have modeled the motivational process in which consumers want to use artificial intelligence speakers. In the empirical study, the survey was conducted and the survey data was analyzed by applying the method of analysis of the structural equation model. As a result of empirical research, consumers' expectations to meet their general needs for artificial intelligence speakers affected their expectations to meet their wants and their favorable perceptions. And consumers' expectations of meeting their quasi-desire for artificial intelligence speakers have affected their expectations of meeting the wants and affected their perception of favorability. Finally, consumers' expectations for satisfying their wants and their perception of favorability affected their intention to use artificial intelligence speakers. The implications of this study is that it helps to formulate strategies for information technology products with combined functionality. The specific components of motivation can play an important role in increasing consumers' intention to use artificial intelligence speakers.

• 한국정보교육학회:학술대회논문집
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• 한국정보교육학회 2021년도 학술논문집
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• pp.149-157
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• 2021

2022년 개정 교육과정에 인공지능 교육 도입을 앞두고 인공지능을 학습 소재로 한 다양한 수업들이 개발되어야 하는 시점이다. 본 연구에서는 설계기반연구를 활용하여 설명가능한 인공지능을 기반한 인공지능 교육 프로그램을 개발하였다. 인공지능의 기초, 활용, 윤리 세 분야를 골고루 포괄하며 실생활 사례와도 쉽게 연결시킬 수 있는 설명가능한 인공지능을 핵심 주제로 설정하였다. 일반적인 설계기반연구(Design-based research, DBR)에서는 3차 이상의 반복적인 과정이 이루어지지만 본 연구 결과는 1차 설계, 적용 및 평가에 대한 결과를 바탕으로 연구가 진행되었다. 추후 학교 현장에 적용하여 3차 수정 및 보완을 바탕으로 더욱 완성된 설명가능한 인공지능을 주제로 한 프로그램을 개발하고자 한다. 본 연구가 학교 현장에 도입되는 인공지능 교육의 발전에 도움이 되기를 기대한다.

• Korean Journal of Radiology
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• 제21권1호
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• pp.33-41
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• 2020

Artificial intelligence has been applied to many industries, including medicine. Among the various techniques in artificial intelligence, deep learning has attained the highest popularity in medical imaging in recent years. Many articles on deep learning have been published in radiologic journals. However, radiologists may have difficulty in understanding and interpreting these studies because the study methods of deep learning differ from those of traditional radiology. This review article aims to explain the concepts and terms that are frequently used in deep learning radiology articles, facilitating general radiologists' understanding.

• 전자통신동향분석
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• 제35권3호
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• pp.1-8
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• 2020

Artificial-intelligence (AI) technology is used in a variety of fields, from robot cleaner motion control to call center counselors, AI speakers, and Mars exploration. Because the technology levels of all applications and services that utilize AI vary widely, it is not possible to view all applications using AI technology at the same level. Nevertheless, there have been no cases in which the level of AI technology was defined. Therefore, the Electronics and Telecommunications Research Institute (ETRI) Artificial Intelligence Research Laboratory has defined the levels of the main technical elements of AI from steps 1 to 6. In this report, the Artificial Intelligence Technology Level 1.0 (ATL 1.0) is presented. It was established by comprehensively referring to the AI technology prospects and technology roadmaps of major countries. It is hoped that it can be used as a measure for determining the levels of AI applications or services or as an indicator for establishing a technology roadmap.

• 디지털산업정보학회논문지
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• 제15권3호
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• pp.15-28
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• 2019

Artificial intelligence is evolving rapidly in the ICT field, smart convergence media system and content industry through the fourth industrial revolution, and it is evolving very rapidly through Big Data. In this paper, we propose a face recognition method based on object recognition based on object recognition through artificial intelligence. In this method, Were experimented and studied through the object recognition technique of artificial intelligence. In the conventional 3D image field, general research on object recognition has been carried out variously, and researches have been conducted on the side effects of visual fatigue and dizziness through 3D image. However, in this study, we tried to solve the problem caused by the quantitative difference between object recognition and object recognition for human factor algorithm that measure visual fatigue through cognitive function, morphological analysis and object recognition. Especially, The new method of computer interaction is presented and the results are shown through experiments.

• International journal of advanced smart convergence
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• 제13권1호
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• pp.212-220
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• 2024

When a typhoon or natural disaster occurs, a significant number of orchard fruits fall. This has a great impact on the income of farmers. In this paper, we introduce an AI-based method to enhance low-quality raw images. Specifically, we focus on apple images, which are being used as AI training data. In this paper, we utilize both a basic program and an artificial intelligence model to conduct a general image process that determines the number of apples in an apple tree image. Our objective is to evaluate high and low performance based on the close proximity of the result to the actual number. The artificial intelligence models utilized in this study include the Convolutional Neural Network (CNN), VGG16, and RandomForest models, as well as a model utilizing traditional image processing techniques. The study found that 49 red apple fruits out of a total of 87 were identified in the apple tree image, resulting in a 62% hit rate after the general image process. The VGG16 model identified 61, corresponding to 88%, while the RandomForest model identified 32, corresponding to 83%. The CNN model identified 54, resulting in a 95% confirmation rate. Therefore, we aim to select an artificial intelligence model with outstanding performance and use a real-time object separation method employing artificial function and image processing techniques to identify orchard fruits. This application can notably enhance the income and convenience of orchard farmers.