• Journal of Medicine and Life Science
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• v.21 no.3
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• pp.92-101
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• 2024

This study investigated how the use of a conversational artificial intelligence (AI) chatbot improved medical students' patient-centered communication (PCC) skills and how it affected their motivation to learn using innovative interactive tools such as AI chatbots throughout their careers. This study adopted a one-group post-test-only design to investigate the impact of AI chatbot-based learning on medical students' PCC skills, their learning motivation with AI chatbots, and their perception towards the use of AI chatbots in their learning. After a series of classroom activities, including metaverse exploration, AI chatbot-based learning activities, and classroom discussions, 43 medical students completed three surveys that measured their motivation to learn using AI tools for medical education, their perception towards the use of AI chatbots in their learning, and their self-assessment of their PCC skills. Our findings revealed significant correlations among learning motivation, PCC scores, and perception variables. Notably, the perception towards AI chatbot-based learning and AI chatbot learning motivation showed a very strong positive correlation (r=0.72), indicating that motivated students were more likely to perceive chatbots as beneficial educational tools. Additionally, a moderate correlation between motivation and self-assessed PCC skills (r=0.54) indicated that students motivated to use AI chatbots tended to rate their PCC skills more favorably. Similarly, a positive relationship (r=0.68) between students' perceptions of chatbot usage and their self-assessed PCC skills indicated that enhancing students' perceptions of AI tools could lead to better educational outcomes.

• Journal of Advanced Navigation Technology
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• v.28 no.3
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• pp.369-374
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• 2024

This study aims to improve the accessibility and efficiency of sign language education for both hearing impaired and non-deaf people. To this end, we developed VR realistic sign language education content that integrates hand tracking technology and conversational AI. Through this content, users can learn sign language in real time and experience direct communication in a virtual environment. As a result of the study, it was confirmed that this integrated approach significantly improves immersion in sign language learning and contributes to lowering the barriers to sign language learning by providing learners with a deeper understanding. This presents a new paradigm for sign language education and shows how technology can change the accessibility and effectiveness of education.

• Asia pacific journal of information systems
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• v.33 no.4
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• pp.957-976
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• 2023

ChatGPT has had a significant impact on society, business, and academia by influencing individuals and organizations through knowledge generation and supporting users in locating conversational inquiries and answers. It can transform how people seek answers by combining human-like conversational skills with AI. By eradicating the cumbersome process of selecting from multiple options, users can conduct preliminary research or create optimized solutions. The purpose of this research is to investigate how consumers use ChatGPT and digital transformation, specifically in terms of knowledge development, searching and recommending, and optimizing accessible possibilities. Using many linked theories, we address the potential implications and insights that can be gained from ChatGPT's early stages and its integration with other applications such as robotics, service automation, and the metaverse. Finally, the application of ChatGPT has practical, theoretical, and phenomenological impacts, in addition to improving users' experiences.

• Electronics and Telecommunications Trends
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• v.38 no.5
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• pp.1-11
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• 2023

The emergence of generative hyperscale artificial intelligence (AI) has enabled new services, such as image-generating AI and conversational AI based on large language models. Such services likely lead to the influx of numerous users, who cannot be handled using conventional AI models. Furthermore, the exponential increase in training data, computations, and high user demand of AI models has led to intensive hardware resource consumption, highlighting the need to develop domain-specific semiconductors for hyperscale AI. In this technical report, we describe development trends in technologies for hyperscale AI processors pursued by domestic and foreign semiconductor companies, such as NVIDIA, Graphcore, Tesla, Google, Meta, SAPEON, FuriosaAI, and Rebellions.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.572-573
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• 2022

본 논문은 메타버스 환경에서 문제가 대두되고있는 AI 윤리(ethic)를 배경으로 인터랙션을 통해 사람들의 온라인과 오프라인의 결정요소에 직접적으로 영향을 미치는 대화형 AI가 어떻게 윤리적으로 진화될 수 있을지에 대한 공학적 솔루션을 UX 관점으로 찾아보는 기술 전략 연구라고 할 수 있다. 연구의 가설은 AI 의 머신러닝과정에 개별 사용자 그룹의 경험데이터가 반드시 포함되고 고려되어야 AI 는 오류값을 줄이고 윤리적으로 대응할 수 있다는 전제이다. 이를 위하여 본 논문은 기존의 머신러닝과 대화형 AI 의 UX 관점의 다이아로그 플로우 등을 연구 분석하고 사용자 데이터들을 실험하여 메타버스 서비스 환경에서의 기존에 논의되고 있는 컨택스트기반의 AI 머신러닝 과정에 사용자의 정성적 경험데이터를 추가한 윤리적 UX 접근 개념 모델을 제안 하였다. 아직은 개념모델 단계이고 시스템에서는 지금까지 다르지 않았던 비정량적인 감정과 융합적경험을 어떻게 문화적으로 코드화 하고 시스템적인 랭귀지와 연결시킬 수 있을지에 대한사용자 연구가 후속연구로 진행될 예정이다.

• The Journal of the Korea Contents Association
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• v.19 no.11
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• pp.558-566
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• 2019

Artificial intelligent (AI) smart speaker sales have increased rapidly, and AI technology has become more pervasive in our daily lives. This study explored motivations for smart speaker use and examined how motivation and relationship type with AI speakers affect enjoyment. Smart speaker use is primarily motivated by conversational, trend-leading, efficient, and entertaining factors. Among these four, trend-leading, efficient, and entertaining factors positively influenced users' enjoyment. However, among the three types of relationship with AI speakers, only the assistant/helper type affected enjoyment. The results of the current study provide practical implications for future directions in AI speaker interaction design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2049-2068
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• 2021

AI combined with NLP techniques has promoted the use of Virtual Assistants and have made people rely on them for many diverse uses. Conversational Agents are the most promising technique that assists computer users through their operation. An important challenge in developing Conversational Agents globally is transferring the groundbreaking expertise obtained in English to other languages. AI is making it possible to transfer this learning. There is a dire need to develop systems that understand secular languages. One such difficult language is Hindi, which is the fourth most spoken language in the world. Semantic similarity is an important part of Natural Language Processing, which involves applications such as ontology learning and information extraction, for developing conversational agents. Most of the research is concentrated on English and other European languages. This paper presents a Corpus-based word semantic similarity measure for Hindi. An experiment involving the translation of the English benchmark dataset to Hindi is performed, investigating the incorporation of the corpus, with human and machine similarity ratings. A significant correlation to the human intuition and the algorithm ratings has been calculated for analyzing the accuracy of the proposed similarity measures. The method can be adapted in various applications of word semantic similarity or module for any other language.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.4
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• pp.412-418
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• 2023

As advances in artificial intelligence (AI) increasingly approach areas once relegated to the realm of science fiction, there is growing public interest in using these technologies for practical everyday tasks in both the home and the workplace. This paper explores the applications of and implications for of using ChatGPT, a conversational AI model based on GPT-3.5 and GPT-4.0, in the field of occupational health and safety. After gaining over one million users within five days of its launch, ChatGPT has shown promise in addressing issues ranging from emergency response to chemical exposure to recommending personal protective equipment. However, despite its potential usefulness, the integration of AI into scientific work and professional settings raises several concerns. These concerns include the ethical dimensions of recognizing AI as a co-author in academic publications, the limitations and biases inherent in the data used to train these models, legal responsibilities in professional contexts, and potential shifts in employment following technological advances. This paper aims to provide a comprehensive overview of these issues and to contribute to the ongoing dialogue on the responsible use of AI in occupational health and safety.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.219-240
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• 2023

Conversational AI which allows users to interact with satisfaction is a long-standing research topic. To develop conversational AI, it is necessary to build training data that reflects real conversations between people, but current Korean datasets are not in question-answer format or use honorifics, making it difficult for users to feel closeness. In this paper, we propose a conversation dataset (KOMUChat) consisting of 30,767 question-answer sentence pairs collected from online communities. The question-answer pairs were collected from post titles and first comments of love and relationship counsel boards used by men and women. In addition, we removed abuse records through automatic and manual cleansing to build high quality dataset. To verify the validity of KOMUChat, we compared and analyzed the result of generative language model learning KOMUChat and benchmark dataset. The results showed that our dataset outperformed the benchmark dataset in terms of answer appropriateness, user satisfaction, and fulfillment of conversational AI goals. The dataset is the largest open-source single turn text data presented so far and it has the significance of building a more friendly Korean dataset by reflecting the text styles of the online community.

• Journal of Practical Engineering Education
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• v.16 no.4
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• pp.513-520
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• 2024

This study investigates the changes in teachers' roles as the impact of AI on school education expands. Traditionally, teachers have been responsible for core aspects of classroom instruction, curriculum development, assessment, and feedback. AI can automate these processes, particularly enhancing efficiency through personalized learning. AI also supports complex classroom management tasks such as student tracking, behavior detection, and group activity analysis using integrated camera and microphone systems. However, AI struggles to automate aspects of counseling and interpersonal communication, which are crucial in student life guidance. While direct conversational replacement by AI is challenging, AI can assist teachers by providing data-driven insights and pre-conversation resources. Key competencies required for teachers in the AI era include expertise in advanced instructional methods, dataset analysis, personalized learning facilitation, student and parent counseling, and AI digital literacy. Teachers should collaborate with AI to emphasize creativity, adjust personalized learning paths based on AI-generated datasets, and focus on areas less amenable to AI automation, such as individualized learning and counseling. Essential skills include AI digital literacy and proficiency in understanding and managing student data.