• Title/Summary/Keyword: AI policy

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Fitness Measurement system using deep learning-based pose recognition (딥러닝 기반 포즈인식을 이용한 체력측정 시스템)

  • Kim, Hyeong-gyun;Hong, Ho-Pyo;Kim, Yong-ho
    • Journal of Digital Convergence
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    • v.18 no.12
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    • pp.97-103
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    • 2020
  • The proposed system is composed of two parts, an AI physical fitness measurement part and an AI physical fitness management part. In the AI fitness measurement part, a guide to physical fitness measurement and accurate calculation of the measured value are performed through deep learning-based pose recognition. Based on these measurements, the AI fitness management part designs personalized exercise programs and provides them to dedicated smart applications. To guide the measurement posture, the posture of the subject to be measured is photographed through a webcam and the skeleton line is extracted. Next, the skeletal line of the learned preparation posture is compared with the extracted skeletal line to determine whether or not it is normal, and voice guidance is provided to maintain the normal posture.

Trends and Implications of Venture Capital Investment in the Artificial Intelligence Industry (인공지능(AI) 산업의 VC 투자 동향과 시사점)

  • S.S., Choi;B.R., Joo;S.J., Yeon
    • Electronics and Telecommunications Trends
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    • v.37 no.6
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    • pp.1-10
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    • 2022
  • Artificial intelligence (AI) has rapidly diffused across industries and societies as nations' essential strategic technology. In innovative technology, such as AI, a startup leads to technological innovation and significantly impacts the expansion of relevant industries. Thus, this study examined the trend of AI startup venture capital (VC) investments globally, focusing on ① noteworthy VC investment statuses (the number and size of the investment, company establishment, and corporate collection), ② the characteristics of each key nation's investments, and ③ the characteristics of each submarket's investments. Among the 11 countries, the results showed that Korea ranked near the bottom for absolute quantitative measures, including the number and size of investments, company establishment, and corporate collection. However, Korea has built a foundation of catching up with what AI-leading countries have established, considering Korea's high growth rate in the number and size of investments and a recent mega-round. This study has practical implications in that it determined the AI startup VC investment status of Korea's rival countries, not only G2 (US and China). The results can be used in policy-making. Furthermore, identifying the AI industry's submarkets and analyzing each market's VC investment status could be used to establish strategies for the AI industry and R&D.

Application of AI in Marketing Strategy: Insights from Millennials and Generation Z

  • Yooncheong CHO
    • The Journal of Economics, Marketing and Management
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    • v.12 no.1
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    • pp.29-38
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    • 2024
  • Purpose: The purpose of this study is to explore the perceptions of millennials and Generation Z regarding AI applications in marketing, an area that has been rarely explored in previous researches. This study formulated research questions how millennials and Generation Z perceive the impact of brand image, AI-assistant customer service, affective factor, immersive experience, cognitive factor social factor and competitiveness of products and brands on overall attitude through the lens of AI applications in marketing. Additionally, this study also explored the influence of overall attitudes on satisfaction, intention to use, and loyalty towards AI applications. Research design, data and methodology: To gather data, this study employed an online survey conducted in collaboration with a reputable research organization. This study utilized factor analysis, ANOVA, and regression analysis for data analysis. Results: The findings revealed that the impact of brand image, AI-assistant customer service, and competitiveness on attitude demonstrated significance in both millennials and generation Z cohorts. The study identified that cognitive and social factors significantly influenced attitudes among millennials, whereas affective and immersive experiences showed significance in influencing attitudes among Generation Z. Conclusions: The findings offer valuable managerial implications, shedding light on the application of AI in marketing with distinct perspectives between millennials and Generation Z.

The Paradigm Shift of Intelligence Information Society: Law and Policy (지능정보사회에 대한 규범적 논의와 법정책적 대응)

  • Kim, Yun-Myung
    • Informatization Policy
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    • v.23 no.4
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    • pp.24-37
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    • 2016
  • An Intelligent information society means intelligent superconducting society that goes beyond information society where information is centered. Now that artificial intelligence is specifically discussed, it is time to start discussing the laws and systems for intelligent information society, where artificial intelligence plays a key role. At some point it may be too late to cope with singularity. Of course, it is not easy to predict how artificial intelligence will change our society. However, there are concerns on what kind of relationship should humans build with AI in the intelligent information society where algorithms rule the world or at least support decision making of humans. What is obvious is that humans dominating AI or ruling out AI will not be the answer. Discussions for legal framework to respond to the AI-based intelligent information society needs to be achieved to a level that replaces the current human-based legal framework with AI. This is because legal improvement caused by the paradigm shift to the intelligent information society may assume emergence of new players-AI, robots, and objects-and even their subjectivation.

Development of AI Image Analysis Emergency Door Opening and Closing System linked Wired/Wireless Counting (유무선 카운팅 연동형 AI 영상분석 비상문 개폐 시스템 개발)

  • Cheol-soo, Kang;Ji-yun, Hong;Bong-hyun, Kim
    • Journal of Digital Policy
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    • v.1 no.2
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    • pp.1-8
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    • 2022
  • In case of a dangerous situation, the roof, which serves as an emergency exit, must be open in case of fire according to the Fire Act. However, when the roof door is opened, it has become a place of various incidents and accidents such as illegal entry, crime, and suicide. As a result, it is a reality to close the roof door in terms of facility management to prevent crime, various incidents, and accidents. Accordingly, the government is pushing to legislate regulations on housing construction standards, etc. that mandate the installation of electronic automatic opening and closing devices on rooftop doors. Therefore, in this paper, an intelligent emergency door opening/closing device system is proposed. To this end, an intelligent emergency door opening and closing system was developed by linking wired and wireless access counting and AI image analysis. Finally, it is possible to build a wireless communication-based integrated management platform that provides remote control and history management in a centralized method of device status real-time monitoring and event alarm.

Research on the application of Machine Learning to threat assessment of combat systems

  • Seung-Joon Lee
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.7
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    • pp.47-55
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    • 2023
  • This paper presents a method for predicting the threat index of combat systems using Gradient Boosting Regressors and Support Vector Regressors among machine learning models. Currently, combat systems are software that emphasizes safety and reliability, so the application of AI technology that is not guaranteed to be reliable is restricted by policy, and as a result, the electrified domestic combat systems are not equipped with AI technology. However, in order to respond to the policy direction of the Ministry of National Defense, which aims to electrify AI, we conducted a study to secure the basic technology required for the application of machine learning in combat systems. After collecting the data required for threat index evaluation, the study determined the prediction accuracy of the trained model by processing and refining the data, selecting the machine learning model, and selecting the optimal hyper-parameters. As a result, the model score for the test data was over 99 points, confirming the applicability of machine learning models to combat systems.

The Ethics of Artificial Intelligence and Robotization in Tourism and Hospitality - A Conceptual Framework and Research Agenda

  • Ivanov, Stanislav;Umbrello, Steven
    • Journal of Smart Tourism
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    • v.1 no.4
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    • pp.9-18
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    • 2021
  • The impacts that AI and robotics systems can and will have on our everyday lives are already making themselves manifest. However, there is a lack of research on the ethical impacts and means for amelioration regarding AI and robotics within tourism and hospitality. Given the importance of designing technologies that cross national boundaries, and given that the tourism and hospitality industry is fundamentally predicated on multicultural interactions, this is an area of research and application that requires particular attention. Specifically, tourism and hospitality have a range of context-unique stakeholders that need to be accounted for in the salient design of AI systems is to be achieved. This paper adopts a stakeholder approach to develop the conceptual framework to centralize human values in designing and deploying AI and robotics systems in tourism and hospitality. The conceptual framework includes several layers - 'Human-human-AI' interaction level, direct and indirect stakeholders, and the macroenvironment. The ethical issues on each layer are outlined as well as some possible solutions to them. Additionally, the paper develops a research agenda on the topic.

Examining the Generative Artificial Intelligence Landscape: Current Status and Policy Strategies

  • Hyoung-Goo Kang;Ahram Moon;Seongmin Jeon
    • Asia pacific journal of information systems
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    • v.34 no.1
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    • pp.150-190
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    • 2024
  • This article proposes a framework to elucidate the structural dynamics of the generative AI ecosystem. It also outlines the practical application of this proposed framework through illustrative policies, with a specific emphasis on the development of the Korean generative AI ecosystem and its implications of platform strategies at AI platform-squared. We propose a comprehensive classification scheme within generative AI ecosystems, including app builders, technology partners, app stores, foundational AI models operating as operating systems, cloud services, and chip manufacturers. The market competitiveness for both app builders and technology partners will be highly contingent on their ability to effectively navigate the customer decision journey (CDJ) while offering localized services that fill the gaps left by foundational models. The strategically important platform of platforms in the generative AI ecosystem (i.e., AI platform-squared) is constituted by app stores, foundational AIs as operating systems, and cloud services. A few companies, primarily in the U.S. and China, are projected to dominate this AI platform squared, and consequently, they are likely to become the primary targets of non-market strategies by diverse governments and communities. Korea still has chances in AI platform-squared, but the window of opportunities is narrowing. A cautious approach is necessary when considering potential regulations for domestic large AI models and platforms. Hastily importing foreign regulatory frameworks and non-market strategies, such as those from Europe, could overlook the essential hierarchical structure that our framework underscores. Our study suggests a clear strategic pathway for Korea to emerge as a generative AI powerhouse. As one of the few countries boasting significant companies within the foundational AI models (which need to collaborate with each other) and chip manufacturing sectors, it is vital for Korea to leverage its unique position and strategically penetrate the platform-squared segment-app stores, operating systems, and cloud services. Given the potential network effects and winner-takes-all dynamics in AI platform-squared, this endeavor is of immediate urgency. To facilitate this transition, it is recommended that the government implement promotional policies that strategically nurture these AI platform-squared, rather than restrict them through regulations and stakeholder pressures.

An analysis of public perception on Artificial Intelligence(AI) education using Big Data: Based on News articles and Twitter (빅데이터 분석을 통해 본 AI교육에 대한 사회적 인식: 뉴스기사와 트위터를 중심으로)

  • Lee, Sang-Soog;Yoo, Inhyeok;Kim, Jinhee
    • Journal of Digital Convergence
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    • v.18 no.6
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    • pp.9-16
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    • 2020
  • The purpose of this study is to understand the public needs for AI education actively promoted and supported by the current government. In doing so, 11 metropolitan news articles and Twitter posts regarding AI education that have been posted from January 1, 2018 to December 31, 2019 were collected. Then, word frequency analysis using TF(Term Frequency) method and LDA(Latent Dirichlet Allocation) method of topic modeling analysis were conducted. The topics of the news articles turn out to be a macroscopic policy support such as 'training female manpower in the AI field' and 'curriculum reform of university and K-12', whereas the topics of twitter delineate more detailed social perception on future society, such as future competencies and pedagogical methods, including 'coexistence with intelligent robots', 'coding education', and 'humane education competence development'. The findings are expected to be used to suggest the implications for the composition and management of AI curriculum as well as the basic framework of human resources development in the future industry.

Categorization of Regional Delivery System for the Elderly Chronic Health Care and Long-Term Care (지역별 노인 만성기 의료 및 요양·돌봄 공급체계 유형화)

  • Nan-He Yoon;Sunghun Yun;Dongmin Seo;Yoon Kim;Hongsoo Kim
    • Health Policy and Management
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    • v.33 no.4
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    • pp.479-488
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    • 2023
  • Background: By applying the suggested criteria for needs-based chronic medical care and long-term care delivery system for the elderly, the current status of delivery system was identified and regional delivery systems were categorized according to quantity and quality of delivery system. Methods: National claims data were used for this study. All claims data of medical and long-term care uses by the elderly and all claims data from long-term care hospitals and nursing homes in 2016 were analyzed to categorize the regional medical and long-term care delivery system. The current status of the delivery system with a high possibility of transition to a needs-based appropriate delivery system was identified. The necessary and actual amount of regional supply was calculated based on their needs, and the structure of delivery systems was evaluated in terms of the needs-based quality of the system. Finally, all regions were categorized into 15 types of medical and care delivery systems for the elderly. Results: Of the total 55 regions, 89.1% of regions had an oversupply of elderly medical and care services compared to the necessary supply based on their needs. However, 69.1% of regions met the criteria for less than two types of needs groups, and 21.8% of regions were identified as regions where the numbers of institutions or regions with a high possibility of transition to an appropriate delivery system were below the average levels for all four needs groups. Conclusion: In order to establish an appropriate community-based integrated elderly care system, it is necessary to analyze the characteristics of the regional delivery system categories and to plan a needs-based delivery system regionally.