• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.167-176
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• 2024

Chatbot services are used in various fields in connection with AI services. Security research on AI is also in its infancy, but research on practical security in the service implementation stage using it is more insufficient. This paper analyzes the security requirements for chatbot services linked to AI services. First, the paper analyzes the recently published papers and articles on AI security. A general implementation model is established by investigating chatbot services provided in the market. The implementation model includes five components including a chatbot management system and an AI engine Based on the established model, the protection assets and threats specialized in Chatbot services are summarized. Threats are organized around threats specialized in chatbot services through a survey of chatbot service managers in operation. Ten major threats were drawn. It derived the necessary security areas to cope with the organized threats and analyzed the necessary security requirements for each area. This will be used as a security evaluation criterion in the process of reviewing and improving the security level of chatbot service.

• 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.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.297-307
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• 2022

This study examined whether there was a difference in the attitude toward the recommended product and the effect on the choice deferral according to information sources. Experiment 1 examined the relationship between trust in information and product attitude, and between uncertainty and choice deferral according to information sources (AI chatbot vs. human). Experiment 2 examined the impact of social presence, perceived personalization, and choice deferral according to whether anthropomorphism of AI chatbots or not. The research results are as follows. First, consumers were found to have a more positive attitude toward products recommended by AI chatbots (vs. human). Second, consumers were more choice deferral whether to purchase products recommended by AI chatbots (vs. human). Third, it was found that consumers' selection of products recommended by anthropomorphic AI chatbots (vs. impersonated AI chatbots) increased. Also, the implications of this study and future research directions were discussed.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.135-138
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• 2021

본 논문에서는 예비교사를 위한 AI-STEAM 교육 사례로서 봇빌더를 활용한 챗봇 제작 교육을 실시하고 이를 바탕으로 챗봇 제작 AI-STEAM 교육을 위한 시사점을 제시하였다. 최근 관련 정책이 발표되는 등 인공지능 교육이 학교에서 실시되기 위한 기반이 마련되었다. 인공지능 교육이 학교 현장에 제대로 안착되기 위해서는 현직 교사들에 대한 보수교육 뿐 아니라 교육 및 사범대학의 교원양성과정에서도 인공지능 교육이 실시되어야 할 필요가 있다. 본 논문에서는 교사들의 인공지능 교사교육 요구를 바탕으로 AI-STEAM을 제안하고 다양한 전공의 예비교사를 위한 챗봇 제작 AI-STEAM 교양교육 및 학생 작품 사례를 제시하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.203-204
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• 2020

챗봇이란 인공지능 기반으로 인간과 대화하는 로봇을 일컬으며, 요청과 응답구조로 운영되는 인공지능 프로그램을 말한다. 챗봇은 사용자와 상호작용하기 위해 대화형 인터페이스를 사용하는 소프트웨어로 기존 사용자의 언어를 이해하고 학습하여 인간이 대화하듯이 대화를 하도록 설계되어있다. 챗봇을 사용하는 회사는 인건비를 줄이고 빅데이터를 기반으로 전문적이고 정확한 답변을 제공할 수 있어 활용 효율성이 높은 편이다. 그러나 회사가 챗봇을 적극적으로 도입하고 사용자에게 긍정적인 영향을 줄 것이라는 기대와 달리 사용자는 챗봇을 계속 사용하지 않고있다. 따라서 본 논문은 챗봇 서비스의 지속사용의도에 영향을 미치는 요인들을 파악하고자 한다. 특히 인공지능 특성이 챗봇 서비스 지속적 사용의도에 미치는 영향을 연구한다.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.1
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• pp.41-50
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• 2023

Recently, as the Coronavirus disease 2019 (COVID-19) prolongs along with the development of artificial intelligence technology, a non-contact society has become commonplace. Many companies are promoting digital transformation and the activation of artificial intelligence introduction to respond to this which leads to dramatic increase of demand for Chatbot. In addition, a Chatbot has reached the point of processing business transactions from responding simple inquiries. However, it is necessary to develop an API to interface with the legacy system and there are many difficulties in connecting. To solve this, it is becoming important to establish a hybrid Chatbot environment through RPA interface. Recently, the combination of RPA and Chatbot is considered an effective tool for handling many business processes. But, there are many difficulties due to the lack of interface cases and the difficulty in finding a method to development them. This study suggests a method for building a hybrid Chatbot which is an interface Chatbot(Conversational UX) and RPA(Task Automation) from the perspective of hyper-automation based on actual development cases and review of literature review is presented, so that the interface method can be understood and develop more easily. Therefore, there are implications for actively using AI Chatbot for digital transformation.

• Information Systems Review
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• v.26 no.1
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• pp.119-149
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• 2024

This study investigates the antecedents and mechanisms influencing trust and behavioral intentions formation towards new AI chatbots, such as ChatGPT, as travel information searching services. Analyzing the roles of variables such as familiarity, novelty, personal innovativeness, information quality and perceived anthropomorphism, the research elucidates the impact of these factors on users' cognitive and affective trust, ultimately affecting their intention to adopt information and sustain the use of the AI chatbot. Results indicate that perceived familiarity and information quality positively influence both cognitive and affective trust, whereas perceived novelty contributes positively only to cognitive trust. Additionally, the personal innovativeness of new AI chatbot users was found to weaken the effect of familiarity on perceived trust, while the perceived level of anthropomorphism of the chatbot amplified the effects of novelty and familiarity on cognitive trust. These findings underscore the importance of considering factors such as familiarity, personal innovativeness, information quality and anthropomorphism in the design and implementation of AI chatbots, affecting trust and behavioral intention.

• Knowledge Management Research
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• v.25 no.2
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• pp.49-68
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• 2024

Increasing concerns regarding personal data privacy have complicated the acquisition of customer data through online marketing. This study investigates factors influencing customers' willingness to disclose information via a generative AI-based chatbot. Drawing on privacy calculus theory and regulatory focus theory, we explore how customer regulatory focus and familiarity with the generative AI-based chatbot shape disclosure intentions. Our study, involving 473 participants, reveals that low familiarity with the chatbot leads individuals with a prevention focus to perceive higher privacy risks and lower perceived usefulness compared to those with a promotion focus. However, with high familiarity, these differences diminish. Moreover, individuals with a promotion focus show a greater inclination to disclose information when familiarity with the generative AI-based chatbot is low, whereas this regulatory focus does not significantly impact disclosure intentions when familiarity is high. Perceived privacy risks mediate these relationships, underscoring the importance of understanding familiarity with the generative AI-based chatbot in facilitating personal information disclosure.

• The Journal of Bigdata
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• v.7 no.2
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• pp.91-102
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• 2022

As artificial intelligence develops, AI chatbot systems are actively taking place. For example, in public institutions, the use of chatbots is expanding to work assistance and professional knowledge services in civil complaints and administration, and private companies are using chatbots for interactive customer response services. In this study, we propose a scenario-based AI voice chatbot system to reduce museum operating costs and provide interactive guidance services to visitors. The implemented voice chatbot system consists of a watcher object that detects the user's voice by monitoring a specific directory in real-time, and an event handler object that outputs AI's response voice by performing inference by model sequentially when a voice file is created. And Including a function to prevent duplication using thread and a deque, GPU operations are not duplicated during inference in a single GPU environment.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.876-878
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• 2019

본 연구에서는 금융 분야에서 AI 기술을 이용하여 챗봇 기반의 예측 시스템을 구축하는데 목적이 있다. 사용자가 이해하기 쉽게 챗봇 기반으로 실시간 서비스를 제공하며 투자 경험이 없는 사용자를 타겟으로 투자 추천을 하는 것을 목표로 개발하였다. 챗봇 기반의 금융 어플리케이션에서는 종목 주가조회, 코스피 상위 조회, 예측결과 조회, ELS상품추천 등으로 크게 네 가지의 의도파악을 하며 자연어 처리와 단어 매칭 처리를 통해서 사용자에게 최적화된 정보를 제공한다. 정보의 질을 높이기 위해서 인공지능 학습은 10년 치의 데이터를 학습시켰으며 비슷한 패턴을 예측해서 제공한다. 상장기업의 주식과 은행에서 판매하는 ELS를 추천하고 있으며, 챗봇 서비스를 통해 사용자와 실시간적으로 소통할 수 있는 AI기반의 금융 시스템을 제공한다.