• Convergence Security Journal
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• v.23 no.5
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• pp.117-123
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• 2023

Recently, as the demand for Generative Artificial Intelligence (AI) and artificial intelligence has increased, the seriousness of misuse and abuse has emerged. However, intelligent CCTV, which maximizes detection of abnormal behavior, is of great help to prevent crime in the military and police. AI performs learning as taught by humans and then proceeds with self-learning. Since AI makes judgments according to the learned results, it is necessary to clearly understand the characteristics of learning. However, it is often difficult to visually judge strange and abnormal behaviors that are ambiguous even for humans to judge. It is very difficult to learn this with the eyes of artificial intelligence, and the result of learning is very many False Positive, False Negative, and True Negative. In response, this paper presented standards and methods for clarifying the learning of AI's strange and abnormal behaviors, and presented learning measures to maximize the judgment ability of intelligent CCTV's False Positive, False Negative, and True Negative. Through this paper, it is expected that the artificial intelligence engine performance of intelligent CCTV currently in use can be maximized, and the ratio of False Positive and False Negative can be minimized..

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.217-218
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• 2021

The development of artificial intelligence in the field of construction and construction is revitalizing. The performance and development techniques of artificial intelligence are changing rapidly, but if you look at the cases of domestic construction sites, they are using technologies from 5 to 7 years ago. It is right to follow a stable method in consideration of commercialization, but the previous AI development method requires more manpower and time to develop than the current technology. In addition, in order to actively utilize artificial intelligence technology, customized artificial intelligence is required to be applied to ever-changing changes in construction sites. it is the reality As a result, even if good AI technology is secured at the construction site, it is reluctant to introduce it because there is no advantage in terms of time and cost compared to the existing method to apply it only to some processes. Currently, an AI technique with a faster development process and accurate recognition has been developed to cope with a fluid situation, so it will be important to understand and introduce the rapidly changing AI development method.

• Journal of the Korean School Mathematics Society
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• v.23 no.2
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• pp.223-237
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• 2020

Artificial intelligence technology, which represents the era of the 4th Industrial Revolution, is now deeply involved in our lives, and future education places great emphasis on building students' capabilities for the principles and uses of artificial intelligence. Therefore, the purpose of this study is to develop the contents of AI related education in mathematics, which the relationship is closely connected to each other. To this end, I propose establishing two novel AI-related contents in mathematics education. One subject is related to learning the principle of machine learning based on mathematics foundation. In addition, I draw the core math contents dealt in following subject called 'Basic Mathematics for AI and Data Science.'

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.837-846
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• 2019

Purpose: The purpose of this study is to define various concepts, features, and scopes by examining various previous studies on AI services that are completely different from existing services. It also examines the limitations of existing service quality evaluation methods and studies the characteristics by combining them with various cases of new AI services. And this is to derive and propose quality evaluation attributes of AI service. Methods: The concept and characteristics of artificial intelligence were derived through research and analysis of various previous studies related to artificial intelligence. The key characteristics and quality evaluation items were derived through the KJ method and matching based on the keywords and characteristics derived from previous studies and various cases. Results: Based on the review of various previous studies on the quality of artificial intelligence services, this study presents the main characteristics and quality evaluation items of new artificial intelligence services, which are completely different from existing service quality evaluations. Conclusion: The quality measurement model of AI service is very useful when planning and developing AI-based new products or services because it can accurately evaluate the requirements of consumers using the services of the new AI era. In addition, consumers can be recommended a customized service according to the situation or taste, and can be provided with a customized service based on this.

• Korean Journal of Artificial Intelligence
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• v.11 no.2
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• pp.7-17
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• 2023

Artificial Intelligence (AI) technology has already penetrated deeply into our daily lives, and we live with the convenience of it anytime, anywhere, and sometimes even without us noticing it. However, because AI is imitative intelligence based on human Intelligence, it inevitably has both good and evil sides of humans, which is why ethical principles are essential. The starting point of this study is the AI principles for companies or organizations to develop products. Since the late 2010s, studies on ethics and principles of AI have been actively published. This study focused on AI principles declared by global companies currently developing various products through AI technology. So, we surveyed the AI principles of the Global 500 companies by market capitalization at a given specific time and collected the AI principles explicitly declared by 46 of them. AI analysis technology primarily analyzed this text data, especially LDA (Latent Dirichlet Allocation) topic modeling, which belongs to Machine Learning (ML) analysis technology. Then, we conducted a Delphi technique to reach a meaningful consensus by presenting the primary analysis results. We expect to provide meaningful guidelines in AI-related government policy establishment, corporate ethics declarations, and academic research, where debates on AI ethics and principles often occur recently based on the results of our study.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.241-249
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• 2022

Artificial intelligence is applied not only to the daily life of individuals but also to all industries, and it is no wonder that the age of artificial intelligence has arrived. Therefore it is important to understand the factors that influence the acceptance of AI. This study analyzes whether "AI Effect" which recognizes that commercialized or familiar artificial intelligence is no longer artificial intelligence, affects the acceptance of artificial intelligence and proposes an acceptance plan based on the results. Two experiments were conducted. The first experiment was conducted on 105 adults in the result it was found that 32.4% (34 people) had AI Effect, AI Effect existed in 43.6% (24 people) of women and 20% (10 people) of men, that is, the proportion of AI Effect exsitence in women is about twice as high.and AI Effect exists when the level of AI knowledge is low. The second experiment was conducted 240 adults and 85 participants with AI Effect were selected. We found the group that recognized experience of AI accepted AI more actively. Understanding of AI Effect is expected to suggest companies' views in order to enhance AI capabilities and acceptance. In addition, future studies are expected on considering individual differences or related to acceptance attitudes.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.11-23
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• 2022

Although artificial intelligence(AI) is a key technology in the digital transformation among the emerging technologies, there are concerns about the use of AI, so many countries have been trying to set up a proper regulation system. This study analyzes the cases of the regulation policies on AI in USA, EU and Korea with the aim to set up and improve proper AI policies and strategies in Korea. In USA, the establishment of the code of ethics for the use of AI is led by private sector. On the other side, Europe is strengthening competitiveness in the AI industry by consolidating regulations that are dispersed by EU members. Korea has also prepared and promoted policies for AI ethics, copyright and privacy protection at the national level and trying to change to a negative regulation system and improve regulations to close the gap between the leading countries and Korea in AI. Moreover, this study analyzed the course of policy changes of AI regulation policy centered on ACF(Advocacy Coalition Framework) model of Sabatier. Through this study, it proposes hyper-scale AI regulation policy recommendations for improving competitiveness and commercialization in Korea. This study is significant in that it can contribute to increasing the predictability of policy makers who have difficulties due to uncertainty and ambiguity in establishing regulatory policies caused by the emergence of hyper-scale artificial intelligence.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.59-65
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• 2021

In this paper, we propose the AI certification standardization activities for systematic research and planning for the standardization of trustworthy artificial intelligence (AI). The activities will be in two-fold. In the stage 1, we investigate the scope and possibility of standardization through AI reliability technology research targeting international standards organizations. And we establish the AI reliability technology standard and AI reliability verification for the feasibility of the AI reliability technology/certification standards. In the stage 2, based on the standard technical specifications established in the previous stage, we establish AI reliability certification program for verification of products, systems and services. Along with the establishment of the AI reliability certification system, a global InterOp (Interoperability test) event, an AI reliability certification international standard meetings and seminars are to be held for the spread of AI reliability certification. Finally, TAIPP (Trustworthy AI Partnership Project) will be established through the participation of relevant standards organizations and industries to overall maintain and develop standards and certification programs to ensure the governance of AI reliability certification standards.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.232-237
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• 2020

Given the recent pace of development and expansion of Artificial Intelligence (AI) technology, the influence and ripple effects of AI technology on the whole of our lives will be very large and spread rapidly. The National Artificial Intelligence R&D Strategy, published in 2019, emphasizes the importance of artificial intelligence education for K-12 students. It also mentions STEM education, AI convergence curriculum, and budget for supporting the development of teaching materials and tools. However, it is necessary to create a new type of curriculum at a time when artificial intelligence curriculum has never existed before. With many attempts and discussions going very fast in all countries on almost the same starting line. Also, there is no suitable professor for K-12 students, and it is difficult to make K-12 students understand the concept of AI. In particular, it is difficult to teach elementary school students through professional programming in AI education. It is also difficult to learn tools that can teach AI concepts. In this paper, we propose an educational model for elementary school students to improve their understanding of AI through play or experience. This an experiential education model that combineds exploratory learning and discovery learning using multi-intelligence and the PLAY teaching-learning model to undertand the importance of data training or data required for AI education. This educational model is designed to learn how a computer that knows only binary numbers through UA recognizes images. Through code.org, students were trained to learn AI robots and configured to understand data bias like play. In addition, by learning images directly on a computer through TeachableMachine, a tool capable of supervised learning, to understand the concept of dataset, learning process, and accuracy, and proposed the process of AI inference.

• Electronics and Telecommunications Trends
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• v.35 no.7
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• pp.13-22
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• 2020

There is no denying that computing power has been a crucial driving force behind the development of artificial intelligence today. In addition, artificial intelligence (AI) semiconductors and computing systems are perceived to have promising industrial value in the market along with rapid technological advances. Therefore, success in this field is also meaningful to the nation's growth and competitiveness. In this context, ETRI's AI strategy proposes implementation directions and tasks with the aim of strengthening the technological competitiveness of AI semiconductors and computing systems. The paper contains a brief background of ETRI's AI Strategy #2, research and development trends, and key tasks in four major areas: 1) AI processors, 2) AI computing systems, 3) neuromorphic computing, and 4) quantum computing.