• 동의신경정신과학회지
• /
• 제35권2호
• /
• pp.153-162
• /
• 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.

• 한국지구과학회지
• /
• 제44권6호
• /
• pp.675-692
• /
• 2023

This study used a Chatbot, a generative artificial intelligence (AI), to analyze the interaction between the Chatbot and students when exploring critical minerals from an epistemological aspect. The results, issues to be kept in mind in the teaching and learning process using AI were discussed in terms of the role of the teacher, the goals of education, and the characteristics of knowledge. For this study, we conducted a three-session science education program using a Chatbot for 19 high school students and analyzed the reports written by the students. As a result, in terms of form, the students' questions included search-type questions and non-search-type questions, and in terms of content, in addition to various questions asking about the characteristics of the target, there were also questions requiring a judgment by combining various data. In general, students had a questioning strategy that distinguished what they should aim for and what they should avoid. The Chatbot's answer had a certain form and consisted of three parts: an introduction, a body, and a conclusion. In particular, the conclusion included commentary or opinions with opinions on the content, and in this, value judgments and the nature of science were revealed. The interaction between the Chatbot and the student was clearly evident in the process in which the student organized questions in response to the Chatbot's answers. Depending on whether they were based on the answer, independent or derived questions appeared, and depending on the direction of comprehensiveness and specificity, superordinate, subordinate, or parallel questions appeared. Students also responded to the chatbot's answers with questions that included critical thinking skills. Based on these results, we discovered that there are inherent limitations between Chatbots and students, unlike general classes where teachers and students interact. In other words, there is 'limited interaction' and the teacher's role to complement this was discussed, and the goals of learning using AI and the characteristics of the knowledge they provide were also discussed.

• 지식경영연구
• /
• 제25권2호
• /
• pp.49-68
• /
• 2024

최근 개인정보 공유에 대한 사람들의 우려가 높아지면서 온라인 마케팅을 통해 고객 데이터를 수집하는 것이 점점 어려워지고 있다. 본 연구에서는 생성형 AI 기반 챗봇을 이용하여 고객의 정보 제공의도를 향상시키기 위한 효과적인 요인을 탐색하고자 한다. 보다 구체적으로, 프라이버시 계산이론과 조절초점 이론을 바탕으로 고객의 성향과 생성형 AI 챗봇에 대한 친숙도가 고객의 개인정보 제공의도에 어떻게 영향을 미치는지 살펴보았다. 473명의 참가자를 이용한 실험 결과에 따르면 생성형 AI 기반 챗봇에 대한 친숙도가 낮은 경우, 예방초점 성향의 참가자가 향상초점 성향의 참가자보다 프라이버시 위험을 높게 인식하고 유용성을 더 낮게 지각한 반면, 챗봇에 대한 친숙도가 높은 경우, 예방초점과 향상초점 참가자 간의 프라이버시 위험과 인지된 유용성에는 차이가 나타나지 않았다. 개인정보 제공의도 역시 생성형 AI 기반 챗봇에 대한 친숙도가 낮은 경우, 향상초점 성향의 참가자가 예방초점 성향의 참가자보다 개인정보 제공의도가 더 높게 나타난 반면 챗봇에 대한 친숙도가 높은 경우, 예방초점과 향상초점 참가자 간의 개인정보 제공의도에는 차이가 나타나지 않았다. 이는 개인정보 제공의도에 대한 프라이버시 위험에 의해 매개되었다. 본 연구는 고객의 개인정보 공개를 촉진하기 위해서는 고객의 내재적 성향과 함께 생성형 AI 기반 챗봇에 대한 친숙도를 함께 고려해야 한다는 시사점을 제공하며 더불어 생성형 AI 챗봇에 대한 관련 연구 분야에 기여한다.

• 디지털산업정보학회논문지
• /
• 제19권4호
• /
• pp.87-96
• /
• 2023

ChatGPT, a leader in generative AI, can use natural expressions like humans based on large-scale language models (LLM). The ability to grasp the context of the language and provide more specific answers by algorithms is excellent. It also has high-quality conversation capabilities that have significantly developed from past Chatbot services to the level of human conversation. In addition, it is expected to change the operation method of the tourism industry and improve the service by utilizing ChatGPT, a generative AI in the tourism sector. This study was conducted to explore ChatGPT trends and paradigms in tourism. The results of the study are as follows. First, keywords such as tourism, utilization, creation, technology, service, travel, holding, education, development, news, digital, future, and chatbot were widespread. Second, unlike other keywords, service, education, and Mokpo City data confirmed the results of a high degree of centrality. Third, due to CONCOR analysis, eight keyword clusters highly relevant to ChatGPT in the tourism sector emerged.

• Journal of Information Technology Applications and Management
• /
• 제30권4호
• /
• pp.11-28
• /
• 2023

This paper proposes a method of integrating ChatGPT with traditional chatbot systems to enhance conversational artificial intelligence(AI) and create more efficient conversational systems. Traditional chatbot systems are primarily based on classification models and are limited to intent classification and simple response generation. In contrast, ChatGPT is a state-of-the-art AI technology for natural language generation, which can generate more natural and fluent conversations. In this paper, we analyze the business service areas that can be integrated with ChatGPT and traditional chatbots, and present methods for conducting conversational scenarios through case studies of service types. Additionally, we suggest ways to integrate ChatGPT with traditional chatbot systems for intent recognition, conversation flow control, and response generation. We provide a practical implementation example of how to integrate ChatGPT with traditional chatbots, making it easier to understand and build integration methods and actively utilize ChatGPT with existing chatbots.

• International Journal of Computer Science & Network Security
• /
• 제23권4호
• /
• pp.15-24
• /
• 2023

One of the objectives and aspirations of scientists and engineers ever since the development of computers has been to interact naturally with machines. Hence features of artificial intelligence (AI) like natural language processing and natural language generation were developed. The field of AI that is thought to be expanding the fastest is interactive conversational systems. Numerous businesses have created various Virtual Personal Assistants (VPAs) using these technologies, including Apple's Siri, Amazon's Alexa, and Google Assistant, among others. Even though many chatbots have been introduced through the years to diagnose or treat psychological disorders, we are yet to have a user-friendly chatbot available. A smart generative cognitive behavioral therapy with spoken dialogue systems support was then developed using a model Persona Perception (P2) bot with Generative Pre-trained Transformer-2 (GPT-2). The model was then implemented using modern technologies in VPAs like voice recognition, Natural Language Understanding (NLU), and text-to-speech. This system is a magnificent device to help with voice-based systems because it can have therapeutic discussions with the users utilizing text and vocal interactive user experience.

• 실천공학교육논문지
• /
• 제16권1_spc호
• /
• pp.33-39
• /
• 2024

본 연구는 최근 생성형 AI로 인한 새로운 교육 트렌드 변화에 학습자들의 수업 경험에 대한 긍정/부정 인식의 변화와 실제 활용 형태를 살펴본다. 공학 계열 대학생 6학급을 대상으로 2학기 동안 AI 챗봇을 웹 프로그래밍 수업에 활용하였고, 학기 초부터 설문 조사를 시작으로 중간/기말 고사 보고서 제출 기간까지 학습자의 경험과 활용에 대한 변화를 분석했다. 연구 분석 결과, Q/A 피드백과 실습 문제 해결 등 학습 개선에 도움이 되었고, 수업 적용 이후 중간부터 기말범위까지 챗봇에 대한 인식이 긍정적으로 변화하였다. 이외 수업 내에 커뮤니티 단절(개인화) 문제와 교육 S/W로써 활용 방안에 대한 유의미한 결론을 도출했다. 본 연구는 앞으로 생성형 AI 기반 소프트웨어 개발을 위한 기초 연구로써 의의가 있다.

• Korean Journal of Radiology
• /
• 제25권3호
• /
• pp.224-242
• /
• 2024

The emergence of Chat Generative Pre-trained Transformer (ChatGPT), a chatbot developed by OpenAI, has garnered interest in the application of generative artificial intelligence (AI) models in the medical field. This review summarizes different generative AI models and their potential applications in the field of medicine and explores the evolving landscape of Generative Adversarial Networks and diffusion models since the introduction of generative AI models. These models have made valuable contributions to the field of radiology. Furthermore, this review also explores the significance of synthetic data in addressing privacy concerns and augmenting data diversity and quality within the medical domain, in addition to emphasizing the role of inversion in the investigation of generative models and outlining an approach to replicate this process. We provide an overview of Large Language Models, such as GPTs and bidirectional encoder representations (BERTs), that focus on prominent representatives and discuss recent initiatives involving language-vision models in radiology, including innovative large language and vision assistant for biomedicine (LLaVa-Med), to illustrate their practical application. This comprehensive review offers insights into the wide-ranging applications of generative AI models in clinical research and emphasizes their transformative potential.

• 실천공학교육논문지
• /
• 제15권3호
• /
• pp.589-595
• /
• 2023

인공지능 기술은 기술과 교육을 조합한 에듀테크(EdTech) 분야에서 효율적인 교육 콘텐츠 제공과 개인화된 학습자 환경을 구축 등 새로운 혁신을 이끌고 있다. 본 연구는 최근 발전된 생성형 AI를 활용한 프로그래밍 교육 소프트웨어를 개발한다. 최근 잘 알려진 ChatGPT API 기반으로 프로그래밍 코드 분석에 최적화된 프롬프트를 연동했다. 이외 프로그래밍 소스 코드 학습에 필요한 기능을 UI로 설계하고 AI 챗봇 기반의 질의/응답 템플릿 기능으로 개발하였다. 본 연구는 생성형 인공지능을 활용한 교육 프로그램 개발의 방향성을 제시하고자 한다.

• 경영정보학연구
• /
• 제25권2호
• /
• pp.125-144
• /
• 2023

기존에는 사람이 생성하던 문장, 이미지, 음성 등을 인공지능 기술을 활용하여 자동으로 생성할 수 있게 되면서, 생성형AI 기술이 전 세계적인 관심을 받고 있다. 특히, 대표적 생성형AI 서비스인 ChatGPT는 기존 챗봇 서비스와 차별화되는 능동성과 정확도를 보여주며, 단기간에 이용자 수가 급증하고 있다. 이렇듯 생성형AI 서비스에 대한 관심이 높아지고 있음에도 불구하고, 대부분의 선행연구는 아직 초기 수준에 머무르고 있다. 이에, 본 연구는 생성형AI 서비스의 성공요인을 도출하고 이를 바탕으로 성공적인 비즈니스 전략을 제안하기 위해 LDA 토픽모델링과 키워드 네트워크 다이어그램을 활용하였다. 또한, ChatGPT를 사용하여 기존 텍스트마이닝 방법론을 보완하는 새로운 연구방법론을 제시하였다. 본 연구는 선행연구들의 한계를 극복하고, 생성형AI의 미래 발전에 대한 학술적 및 실무적 시사점을 제공했다는 점에서 의의가 있다.