• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.212-218
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• 2022

In this paper, the necessity of AI video interview arises when conducting an interview for acquisition of excellent talent in a non-face-to-face situation due to similar situations such as Covid-19. As a matter to be supplemented in general AI interviews, it is difficult to evaluate the reliability and qualitative factors. In addition, the AI interview is conducted not in a two-way Q&A, rather in a one-sided Q&A process. This paper intends to fuse the advantages of existing AI interviews and video interviews. When conducting an interview using AI image analysis technology, it supplements subjective information that evaluates interview management and provides quantitative analysis data and HR expert data. In this paper, image-based multi-modal AI image analysis technology, bioanalysis-based HR analysis technology, and web RTC-based P2P image communication technology are applied. The goal of applying this technology is to propose a method in which biological analysis results (gaze, posture, voice, gesture, landmark) and HR information (opinions or features based on user propensity) can be processed on a single screen to select the right person for the hire.

• 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 the Institute of Convergence Signal Processing
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• v.25 no.2
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• pp.100-112
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• 2024

This study investigates the ethical and legal implications of utilizing artificial intelligence (AI) in human resource management, with a particular focus on AI interviews in the recruitment process. AI, defined as the capability of computer programs to perform tasks associated with human intelligence such as reasoning, learning, and adapting, is increasingly being integrated into HR practices. The deployment of AI in recruitment, specifically through AI-driven interviews, promises efficiency and objectivity but also raises significant ethical and legal concerns. These concerns include potential biases in AI algorithms, transparency in AI decision-making processes, data privacy issues, and compliance with existing labor laws and regulations. By analyzing case studies and reviewing relevant literature, this paper aims to provide a comprehensive understanding of these challenges and propose recommendations for ensuring ethical and legal compliance in AI-based HR practices. The findings suggest that while AI can enhance recruitment efficiency, it is imperative to establish robust ethical guidelines and legal frameworks to mitigate risks and ensure fair and transparent hiring practices.

• Journal of Fashion Business
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• v.26 no.2
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• pp.28-47
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• 2022

Rapid development of information and communication technology is leading the digital transformation (hereinafter, DT) of various industries. At this point in rapid online transition, fashion manufacturers operating offline-oriented businesses have become highly interested in DT and artificial intelligence (hereinafter AI), which leads DT. The purpose of this study is to examine the development status and application case of AI-based digital technology developed for the fashion industry, and to examine the DT stage and AI application status of domestic fashion manufacturers. Hence, in-depth interviews were conducted with five domestic IT companies developing AI technology for the fashion industry and six domestic fashion manufacturers applying AI technology. After analyzing interviews, study results were as follows: The seven major AI technologies leading the DT of the fashion industry were fashion image recognition, trend analysis, prediction & visualization, automated fashion design generation, demand forecast & optimizing inventory, optimizing logistics, curation, and ad-tech. It was found that domestic fashion manufacturers were striving for innovative changes through DT although the DT stage varied from company to company. This study is of academic significance as it organized technologies specialized in fashion business by analyzing AI-based digitization element technologies that lead DT in the fashion industry. It is also expected to serve as basic study when DT and AI technology development are applied to the fashion field so that traditional domestic fashion manufacturers showing low growth can rise again.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.591-601
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• 2024

As generative AI-based educational content and services targeting child users rapidly increase, the need for research related to children's perception of generative AI is increasing. Accordingly, this study sought to determine the type of generative AI recognized by children and whether cognitive, behavioral, and emotional properties were assigned to it. To understand this, we collected responses through workshop activities to create storybooks with children, semi-structured interviews, and drawing. As a result, children viewed generative AI as an artifact with a high cognitive level, but it was not a type of existing artifact.

• Knowledge Management Research
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• v.19 no.2
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• pp.187-203
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• 2018

The purpose of this study was to investigate the perception about AI assistants and the differences between two groups, workers(secretaries) and supervisors(bosses), using the Q-methodology which has an advantage in understanding the types of subjective perceptions. Through literature reviews and interviews, 34 Q-samples were extracted, and then Q-sorting was conducted by P-samples(20 workers and 15 supervisors). As a result of Q-sorting, the types and characteristics of AI assistants perceived by each P-sample were explained. The perception of the workers divided into five distinct types, and the perception of the supervisors was divided into three distinct types. The most crucial factors in distinguishing between workers and supervisors' perceptions depend on whether they are capable of performing certain tasks and whether they can replace existing secretarial jobs. This study, as the primary research on AI assistants, can help to redefine the work that can be replaced by AI and the work that only people can do, and thus to establish education, recruitment, and training plans.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.44-52
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• 2022

With recent scientific advances and growing interest in AI technologies, AI-based chatbots have been viewed as a practical learning aid for English language development. The purpose of this study is to examine preservice teachers' perceptions on the potential benefits of employing AI chatbots in English instruction and its pedagogical aspects. 28 preservice teachers majoring in English education were asked to use Kuki chatbots for a week with a guidance of a researcher and then report on their perceptions of AI chatbots in terms of perceived usefulness after use, applicability, and educational benefits and drawbacks. Emerging codes and themes were identified and evaluated using Thematic Analysis(TA) based on qualitative data from surveys and interviews. The findings show that six emerging themes were identified, encompassing perspectives on teacher, learner, communication, linguistic, affective, and assessment. The overall findings of this study revealed that AI-based chatbots can play a significant role as learning tools for stimulating interactive communication in a target language. Most preservice primary teachers acknowledge that AI chatbots can be useful as teaching and learning aids for both teachers and students. Furthermore, when applying various learner data to chatbot technology, such as learner assessment and diagnosis, a guided approach is necessary to perform a conversation appropriate for the learner's level and characteristics. Finally, as chatbots have a variety of benefits in terms of affective aspects, they may improve EFL learners' confidence in speaking English and learning motivation.

• Journal of Information Technology Services
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• v.22 no.2
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• pp.23-40
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• 2023

Despite the growing interest and normative discussions on AI ethics, there is a lack of discussion on policy instruments that are necessary for companies to develop AI-based services in compliance with ethical principles. Thus, the purpose of this study is to explore policy instruments that can encourage companies to voluntarily comply with and adopt AI ethical standards and self-checklists. The study reviews previous research and similar cases on AI ethics, conducts interviews with AI-related companies, and analyzes the data using AHP to derive action plans. In terms of desirability and feasibility, Research findings show that policy instruments that induce companies to ethically develop AI-based services should be prioritized, while regulatory instruments require a cautious approach. It was also found that a consulting support policy consisting of experts in various fields who can support the use of AI ethics, and support for the development of solutions that adhere to AI ethical standards are necessary as incentive policies. Additionally, the participation and agreement of various stakeholders in the process of establishing AI ethical standards are crucial, and policy instruments need to be continuously supplemented through implementation and feedback. This study is significant as it presents the necessary policy instruments for companies to develop ethical AI-based services through an analytical methodology, moving beyond discursive discussions on AI ethical principles. Further analysis on the effectiveness of policy instruments linked to AI ethical principles is necessary for establishing ethical AI-based service development.

• Asia pacific journal of information systems
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• v.32 no.3
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• pp.496-513
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• 2022

Artificial intelligence or big data technologies can benefit finance companies such as those in the insurance sector. With artificial intelligence, companies can develop better customer segmentation methods and eventually improve the quality of customer relationship management. However, the application of AI-based customer segmentation in the insurance industry seems to have been unsuccessful. Findings from our interviews with sales agents and customer service managers indicate that current customer segmentation in the Korean insurance company relies upon individual agents' heuristic decisions rather than a generalizable data-based method. We propose guidelines for AI-based customer segmentation for the insurance industry, based on the CRISP-DM standard data mining project framework. Our proposed guideline provides new insights for studies on AI-based technology implementation and has practical implications for companies that deploy algorithm-based customer relationship management systems.

• Information Systems Review
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• v.25 no.3
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• pp.43-57
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• 2023

In this study, we developed an AI-based system to generate sentences that assist in creating Korean poetry. Instead of replacing the creative aspect of composition, which is considered a unique domain of humans, the focus was on generating foundational sentences to enhance human imagination efficiently. By conducting interviews with poets, the researchers extracted sentences from eight distinct datasets, enabling the generation of poetry across eight different genres. This study stands out for its innovation in developing a method for crafting literary works in Korean. Its significance lies in its potential to facilitate the creation of diverse literary forms such as essays, prose, or novels.