• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.19-29
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• 2020

As the AI speaker market is growing rapidly in recent years, the competition for the preoccupation of children who are the main users and the future prospective customers of the related companies is very intense. However, there is a lack of empirical research on how children interact with AI speakers. Therefore, this research examines the interactions between children and AI speakers, primarily through field studies, to extract what functions they use and what features they have. For this purpose, 799 conversations were collected and analyzed using the log data of the AI speaker recorded in real time. As a result, children were more likely to use children's songs, fairy tales, emotional conversations, and personification compared to adults. In addition, content analysis by specific types resulted in success/failure cases of interaction between children and AI speakers and proposed improvements by failure type. This study is meaningful in that it identifies children's AI speaker preferences, content, and major conversation patterns, and provides guidelines for developing services that meet children's eye level.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.109-118
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• 2022

The purpose of this study is to identify trends in the application of artificial intelligence by analyzing upper extremity movement assessment and artificial intelligence convergence research using a systematic literature review method. The research was conducted using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Among the 380 articles searched in three databases, 8 articles were finally selected according to the selection and exclusion criteria. For the evaluation of upper extremity movement, motion performance evaluation, FMA, and ARAT were used. For quantification, data were extracted using various tools, and upper extremity movement classification, recovery prognosis prediction, and evaluation tool score were predicted using artificial intelligence. This study is meaningful in that it systematically reviewed studies that objectively evaluated upper extremity movement using artificial intelligence and identified the direction in which artificial intelligence is being applied. Based on this, the introduction of artificial intelligence technology in the assessment of upper extremity movements is expected to help objectively identify the intervention effect and the patient's recovery.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.447-452
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• 2024

As the remarkable achievements of generative artificial intelligence technology become increasingly visible, the issue of 'controllability' in artificial intelligence is emerging as a prominent global keyword. This comes at a time when existential threats, such as the possibility of machines dominating humans, are being raised. Accordingly, this study aims to establish the groundwork for shaping a social public sphere by closely examining the concept of control, the current status, and the global landscape of artificial intelligence. It seeks to address the innovative changes anticipated in future society, with artificial intelligence technology at its core. The study aims to derive implications for preparing countermeasures against social problems and unpredictable variables that may arise from the evolution of artificial intelligence technology. It also aims to present guidelines and strategic insights for the establishment of government regulations. Furthermore, the study seeks to uncover implications for the formation of social public discourse.

• 한국벤처창업학회:학술대회논문집
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• 2022.04a
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• pp.153-155
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• 2022

고객을 세분화하여 맞춤화된 서비스를 제공하는 것은 고객 관계 관리에 있어 중요하다. 빅데이터 분석 기법과 기계 학습 등을 활용한 분석 기법의 발전은 더욱 세밀한 고객 세분화를 가능케 했다. 하지만 새로운 분석 기법을 기업에서 효과적으로 적용하는 것은 여러 어려움이 존재한다. 본 연구는 특히 국내 보험 산업에서 데이터 분석 기법을 활용해 더욱 향상된 고객 세분화를 수행할 수 있는 방법에 대해 논의한다. 이를 위하여 실제 보험 설계사와의 심층 인터뷰를 통해 국내 보험 회사의 현상을 파악하고, 이를 기반으로 보험 산업에서 활용할 수 있는 가이드라인을 제시하고자 한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.5
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• pp.187-193
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• 2020

The purpose of this study is to study the methodology of deriving a policy that activates artificial intelligence from the governmental perspective in order to induce corporate growth by effectively grafting artificial intelligence technology into society and thereby improve individual and national competitiveness by creating new jobs. In order to derive activation plans, 1) detailed investigation of the domestic environment, 2) discovery of priority support fields and models that can be applied to artificial intelligence, 3) preparation of guidelines for activation and introduction, 4) specific methods for promoting and activating artificial intelligence Should be presented. The proposed artificial intelligence activation method performs a procedure to verify and confirm the effectiveness of artificial intelligence nurturing through a multi-faceted approach. The multi-faceted analysis approach includes business ecosystem aspects, industry-specific aspects including companies, technology fields, policy aspects, public and non-public services aspects, government-led and private-led aspects. Therefore, it can be reviewed as a method of inducing activation in various forms. In the future research field, it is necessary to prove the effectiveness of the proposed activation plan based on empirical data on artificial intelligence-based services. The expected effect of this study is to contribute to support the development of artificial intelligence technology and to establish related policies.

• The Journal of the Convergence on Culture Technology
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• v.10 no.6
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• pp.799-805
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• 2024

Recently, generative artificial intelligence (AI) technology has been rapidly developing and its application fields are expanding beyond text, voice, image, object recognition, time-series forecasting, and natural language processing to the creative design field that AI was thought to be incapable of. We aim for an exploratory approach to study the cognitive model of pattern designers using generative AI. To this end, we used GPT 4o, which is the most well-known generative AI, and applied the protocol analysis method, a cognitive science research method, to the pattern design process. Four design graduate students were selected as subjects and pilot and main experiment were conducted. Voice recording and video capture were performed to collect data. The protocol method applied the concurrent protocol method, which simultaneously expresses what comes to mind while performing the task. The collected verbal data was used to classify the design process by segmenting words and developing a coding scheme to establish a framework for analysis. As a result, analysis, selection, visualization, evaluation, and optimization were discovered. We expect to present design guidelines for pattern design practice.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.471-485
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• 2024

This study explores the effective utilization of generative AI for conducting in-depth interviews within the lean startup environment. With recent technological advancements, the application of generative AI in enhancing operational productivity has been on the rise across various organizations, and this trend extends to the lean startup milieu. The research develops specific guidelines and a guidebook aimed at assisting practitioners in lean startups to conduct in-depth interviews using AI, even amidst the constraints of limited time and capital. The proposed guidebook facilitates practitioners to swiftly design and conduct interviews, thereby promoting an agile and flexible working environment within lean startups. Moreover, this study investigates practical methods for applying text-based generative AI services like ChatGPT 4 and Luyten in the fields of design and interviewing, thereby contributing to the academic discussion and practical implementation in these areas. The significance of this research lies in its potential to broaden the horizon of scholarly debate and practical application of generative AI in lean startups.

• Journal of Practical Engineering Education
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• v.15 no.3
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• pp.581-588
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• 2023

In this paper, we modeled the methods and steps of reflective writing education that effectively utilizes GPT to enable actual classes. In this paper, we sought a teaching model that can be effectively utilized in self-reflective writing education in a reality where it is physically and practically difficult to prevent the use of an artificial intelligence writing machine called GPT. First, in the preparation stage, we made students understand the operating principles of GPT and educated the application team, while suggesting a teaching method using GPT to model and personalize writing ideas. Afterwards, an example of the task was given. Second, in the stage of using GPT, we showed how to model and internalize writing ideas using GPT according to the process of outlining, paragraphing, and reviewing reflective writing. Third, in the organizing stage, the instructor helped learners edit and make final edits to their writing and presented a process of organizing and reflecting.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.403-409
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• 2024

In this paper, the guidelines for the design of an Artificial Intelligence(AI) based Integrated Process Safety Management(PSM) system to enhance workplace safety using data from process safety reports submitted by hazardous and risky facility operators in accordance with the Occupational Safety and Health Act is proposed. The system composed of the proposed guidelines is to be implemented separately by individual facility operators and specialized process safety management agencies for single or multiple workplaces. It is structured with key components and stages, including data collection and preprocessing, expansion and segmentation, labeling, and the construction of training datasets. It enables the collection of process operation data and change approval data from various processes, allowing potential fault prediction and maintenance planning through the analysis of all data generated in workplace operations, thereby supporting decision-making during process operation. Moreover, it offers utility and effectiveness in time and cost savings, detection and prediction of various risk factors, including human errors, and continuous model improvement through the use of accurate and reliable training data and specialized datasets. Through this approach, it becomes possible to enhance workplace safety and prevent accidents.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.1
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• pp.1-5
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• 2020

사물인터넷, 인공지능, 로봇공학, 증강현실, 가상현실과 같은 고급 기술의 융합과 사용자 행동의 변화가 미래 사업의 모습을 다시 만들고 있다. 기업이 어떻게 잠재적 변화, 작업 공간의 설계, 업무의 정의, 업무 절차를 인식하느냐가 기업이 경쟁 우위를 갖게 하는 데 도움이 되는 중요한 요인이다. Frost & Sullivan은 사회적 진화, 미래에도 견고한 사업 모델, 기술 혁신 등 미래 사업의 모습을 만들어갈 3개의 중요한 동인을 찾아냈다. 실제 작업 공간에서 작업자와 기계의 융합, 사람과 공간의 융합과 같은 트랜드가 사이버 작업 공간에 일어날 것으로, 이를 통해 점진적으로 사업과 업무의 미래 모습을 만들 것이다. 하지만 디지털 전환을 받아들이는 와중에 기업은 숙련된 인력의 부족, 기술의 정렬, 직원 반발, 사이버 보안, 조직 구조와 사고 방식 등과 같은 문제를 해결해야만 한다. 이런 문제들을 해결하기 위해 SHARED 방법론이 기술 수용과 업무 절차 개선에 관심이 있는 기업을 위한 가이드라인 역할을 할 수 있다. 시장에서 성공하기 위해 기술 솔루션 제공자(Technology Solution Provider)는 서비스 제공자로서 역할을 계속하는 동시에, 고객에게 인력 관리 솔루션의 필요성을 교육해야 한다. 기술 솔루션 제공자는 디지털 전환 과정에서 기업과 동반할 믿음직한 조언자이자 장기적 파트너에 기초한 사업 관계를 구축해야만 한다.