• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.12
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• pp.2134-2145
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• 1997

We present a framework of an intelligent design system for embodiment design of machine tools which can support efficiently and systematically the machine design by utilizing design knowledge such as objects(part), know-how, public, evaluation, and procedures. The design knowledge of machining center has been accumulated through interview with design experts of machine tool companies. The processes of embodiment design of machining center are established and represented by the IDEF0 model from the field surveys. We also introduce a hybrid knowledge representation so that the system can easily deal with various and complicated design knowledge. The intelligent design system is being developed on the basis of object-oriented programming, and all parts of a design object, machining center, are also classified by the object-oriented modeling.

• Cross-Cultural Studies
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• v.52
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• pp.277-312
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• 2018

First-order cybernetics during the 1940s and 1950s aimed for control of an observed system, while second-order cybernetics during the mid-1970s aspired to address the mechanism of an observing system. The former pursues an objective, subjectless, approach to a system, whereas the latter prefers a subjective, personal approach to a system. Second-order observation must be noted since a human observer is a living system that has its unique cognition. Maturana and Varela place the autopoiesis of this biological system at the core of second-order cybernetics. They contend that an autpoietic system maintains, transforms and produces itself. Technoscientific recreation of biological autopoiesis opens up to a new step in cybernetics: what I describe as third-order cybernetics. The formation of technoscientific autopoiesis overlaps with the Fourth Industrial Revolution or what Erik Brynjolfsson and Andrew McAfee call the Second Machine Age. It leads to a radical shift from human centrism to posthumanity whereby humanity is mechanized, and machinery is biologized. In two versions of the novel Demon Seed, American novelist Dean Koontz explores the significance of technoscientific autopoiesis. The 1973 version dramatizes two kinds of observers: the technophobic human observer and the technology-friendly machine observer Proteus. As the story concludes, the former dominates the latter with the result that an anthropocentric position still works. The 1997 version, however, reveals the victory of the techno-friendly narrator Proteus over the anthropocentric narrator. Losing his narrational position, the technophobic human narrator of the story disappears. In the 1997 version, Proteus becomes the subject of desire in luring divorcee Susan. He longs to flaunt his male egomaniac. His achievement of male identity is a sign of technological autopoiesis characteristic of third-order cybernetics. To display self-producing capabilities integral to the autonomy of machinery, Koontz's novel demonstrates that Proteus manipulates Susan's egg to produce a human-machine mixture. Koontz's demon child, problematically enough, implicates the future of eugenics in an era of technological autopoiesis. Proteus creates a crossbreed of humanity and machinery to engineer a perfect body and mind. He fixes incurable or intractable diseases through genetic modifications. Proteus transfers a vast amount of digital information to his offspring's brain, which enables the demon child to achieve state-of-the-art intelligence. His technological editing of human genes and consciousness leads to digital standardization through unanimous spread of the best qualities of humanity. He gathers distinguished human genes and mental status much like collecting luxury brands. Accordingly, Proteus's child-making project ultimately moves towards technologically-controlled eugenics. Pointedly, it disturbs the classical ideal of liberal humanism celebrating a human being as the master of his or her nature.

• Journal of Digital Convergence
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• v.16 no.10
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• pp.205-212
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• 2018

With the development of high performance CPU / GPU, artificial intelligence algorithms such as deep neural networks, and a large amount of data, machine learning has been extended to various applications. In particular, a large amount of data collected from the Internet of Things, social network services, web pages, and public data is accelerating the use of machine learning. Learning data sets for machine learning exist in various formats according to application fields and data types, and thus it is difficult to effectively process data and apply them to machine learning. Therefore, this paper studied a method for building a learning data set for machine learning in accordance with standardized procedures. This paper first analyzes the requirement of learning data set according to problem types and data types. Based on the analysis, this paper presents the reference model to build learning data set for machine learning applications. This paper presents the target standardization organization and a standard development strategy for building learning data set.

• Communications of Mathematical Education
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• v.32 no.1
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• pp.23-36
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• 2018

Recently, we are working to utilize it in various fields with the expectation of the potential of artificial intelligence. There is also interest in applying to the field of education. In the field of education, machine learning and deep learning, which are used in artificial intelligence technology, are deeply interested in how to learn on their own. We are interested in how artificial intelligence and artificial intelligence technologies can be used in education and we have an interest in how artificial intelligence can be applied to mathematics education. The purpose of this study is to investigate the direction of mathematics education as the change of education paradigm and the development of artificial intelligence according to the development of information and communication technology. Furthermore, we examined how artificial intelligence can be applied to mathematics education.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.741-749
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• 2022

The purpose of this study is to find out what kind of media perception can be experienced by the audience when artificial intelligence technology meets art, where new technologies are invented one after another. Among the artificial intelligence works, I selected works that stand out in relation to perception and investigated what kind of media perception the audience experiences when artificial intelligence technology meets art. By examining the characteristics of machine hallucinations, uncanny, and artificial empathy with the media perception of artificial intelligence art, these perceptions were ultimately identified as aura perception within family resemblance. In the future, artificial intelligence technology will develop further and artists will not stop experimenting with them. It is expected that the works created by artists will expand the audience's perceptual experience while providing new experiences to the audience.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.157-158
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• 2023

본 연구는 건설기계에 의한 협착 및 충돌재해의 예방을 위해 사용하고 있는 스마트 안전관리 시스템 중 건설기계 근접 방지시스템의 재해예방 효과를 분석하여 그 안전성을 실증하고자 하였다. 건설기계 중 재해다발 및 위험성이 높은 굴삭기를 대상으로 스마트 안전관리 시스템의 유무에 따라 근로자(1,000명 기준)의 행동 변화를 라이다 센스 장비를 활용하여 분석하였다. 근로자-건설기계와 최단 이격거리, 위험구역 내 근로자의 체류시간, 위험구역 주변 근로자의 이동 경로 및 체류시간에 따른 근로자의 분포도 등 근로자의 행동 패턴을 분석한 결과스마트 안전관리 시스템을 설치한 건설기계가 미설치한 건설기계보다 근로자와의 이격거리 확보와 위험구역내 체류시간을 단축한 결과를 도출하였다. 이는 스마트 안전관리 시스템이 건설기계와 관련한 협착 및 충돌 등에 의한 재해로부터 근로자의 안전성을 확보한 결과라 분석되었다.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.116-124
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• 2018

This study aimed to interpreting the view of current media by artificial intelligence(AI) with the case of a TV show Person of Interest, which was broadcasted until 2016 in US. In this study, we first attempted to find how AI reflects the three laws of robotics, which often appear in Science Fictions. In addition, we paid attention to how the society looks according to the change of the manipulator of the AI, and as a result we derived the distinguishes of the show from other content dealing with robots or AI in terms of narrative. Through this study, we classified the messages in accordance of AI into three categories- importance of data sovereignty, potential of intelligence explosion, and blind faith in high technology. This study suggested that the show emphasizes the consciousness and attitude that should be possessed as a citizen who meets the era of AI prior to raising issue of 'what artificial intelligence is should be developed for our convenience?'

• Journal of Science and Technology Studies
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• v.17 no.1
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• pp.5-39
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• 2017

In March 2016, the computer Go program, AlphaGo, defeated Sedol Lee, a Korean professional Go player of 9-dan rank. This victory by AlphaGo shows the rise in popularity of artificial intelligence (AI). Not only was this game a testament to machine performance, it was the type of game that extended the Turing test. When the interrogator cannot differentiate between human being and machine, the machine has passed the test. This article examines the interactions between AI and human beings and studies the social nature of intelligence through the AlphaGo case. Collins insists that knowledge or intelligence is social and embodied, and the interrogators in the Turing test can identify the difference between native members and non-members through their knowledge only. Applying this concept, AlphaGo, as subject A of this test, fulfilled its role of stirring up the classical "truth of human." Meanwhile, Lee as subject B, played to speak the truth by revealing his own qualities. Here, it is also important role that interrogators judge what it is. Many spectators, as interrogators, have intervened to confirm the border between human beings and machines by using their embodied and social knowledge.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.35-39
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• 2018

챗봇은 사람과 기계가 자연어로 된 대화를 주고받는 시스템이다. 최근 대화형 인공지능 비서 시스템이 상용화되면서 일반적인 대화와 질의응답을 함께 처리해야할 필요성이 늘어나고 있다. 본 논문에서는 기계독해 기반 질의응답과 Transformer 기반 자연어 생성 모델을 함께 사용하여 하나의 모델에서 일반적인 대화와 질의응답을 함께 하는 기계독해 기반 질의응답 챗봇을 제안한다. 제안 모델은 기계독해 모델에 일반대화를 판단하는 옵션을 추가하여 기계독해를 하면서 자체적으로 문장을 분류하고, 기계독해 결과를 통해 자연어로 된 문장을 생성한다. 실험 결과 일반적인 대화 문장과 질의를 높은 성능으로 구별하면서 기계독해의 성능은 유지하였고 자연어 생성에서도 분류에 맞는 응답을 생성하였다.

• Informatization Policy
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• v.23 no.4
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• pp.3-23
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• 2016

Since Turing (1950) proposed the development of a machine or system that could think and communicate with humans, many engineers and scientists have made endless efforts to create machines and systems that can replace humans. This effort made the field of artificial intelligence. Recently, as many people have been interested in the 4th Industrial Revolution, research on artificial intelligence technology has been actively carried out not only in the university laboratories but also in the companies as the core technology for realizing the 4th Industrial Revolution. As the artificial intelligence technology has been penetrated deeply into our lives, it is true that our lives have become much easier and more comfortable than in the past, but on the other hand, we have begun to have various negative effects. In this study, we review the social changes caused by artificial intelligence in terms of intelligent products and services. By analyzing positive effects and dysfunctions in various cases of daily life and work environment, we try to identify main policy issues.