• Journal of Korean Philosophical Society
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• v.147
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• pp.239-260
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• 2018

Is an artificial intelligence robot, a non-human beings newly emerging in the age of technology, a threat to human beings, or a mutual cooperation or ensemble with human beings? The desire to control nature through the use of the power of science and technology is manifested in the fear that humans can annihilate themselves. This study attempts to identify the problems of Cartesian epistemology underlying these questions and fears and to answer these questions based on Merleau - Ponty 's ontological ontology using the Ontology and Latour' s ontology and technological philosophy. The cogito derived from the Cartesian philosophy became the basis of the structure of dichotomous epistemology of 'subjectivity and objectivity' based on human - reason. In the human-centered world, all non-human beings were tools or controls for humans. The problem of the modern people is not only to get help from the natural scientific methods to control the nature including man, but also to think that scientific method is the only way to understand the world. In criticizing this, Merleau-Ponty shows that the body mediates between human beings and non-human beings, and provides a possible ontological basis for the ontology. Merleau - Ponty 's phenomenological methodology and ontology are newly developed by Simondon under the influence of phenomenological philosopher and phenomenology. The relationship between human beings and nonhuman beings by Simondon appears as an ensemble of human and technical objects or a mutual co - operation of human and technical objects. In particular, Latour goes a step further in Simondon and defines all the bodies living in the world as actor-network theory, denying the core concept of modernity. Merleau - Ponty 's phenomenological view can be a new possible basis for the philosophical discussion of the technological age. We will see that the problem itself can be solved by shifting modern fear to a phenomenological attitude.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2002.05a
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• pp.59-64
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• 2002

인지심리학 및 인지언어학 분야에서 시도한 어휘 표상, 특히 움직임과 관련된 동사의 인지도식에 관한 연구들을 비교해보고자 한다. 인간의 언어학적인 지식을 도식적으로 표상 하고자 하는 노력은 언어의 통사적인 외형에만 치중하는 연구에서는 언어의 의미구조를 파악하기 힘들다고 판단하고 의미적인 범주화를 중요시하게 되었다. 본 연구에서는 시각적 이미지 도식을 중점적으로 살펴보기로 한다. 이미지 도식은 공간적 위치 관계, 이동, 형상 등에 관한 지각과 결부되어 있다. 이미지로 나타낸 표상은 근본적으로 세상의 인식과 세상에 대한 행동방법을 사용하게 하는 유추적이고 은유적인 원칙에 기초하고 있다. 이러한 점에 있어서, 언술을 발화한 화자는 어느 정도 주관적인 행동의 능력과 그가 인식한 개념화에서부터 문자화시킨 표상을 구성한다. 인지 원칙에 입각한 의미 표상에 중점을 둔 도식으로는, Langacker, Lakoff, Talmy의 도식이 있다. 프랑스에서 톰 R. Thom과 같은 수학자들은 질적인 현상에 관심을 가져 형역학(morphodynamique)이론을 확립하였는데, 이 이론은 요즘의 인지 연구에 수학적 기초를 제공하였다. R. Thom, J. Petitot-Cocorda의 도식 및 구조 의미론의 창시자라고 불리는 B.Pottier의 도식이 여기에 속한다 J.-P. Descles가 제시한 인지연산문법(Grammaire Applicative et Cognitive)은 다른 인지문법과는 달리 정보 자동처리과정에서 사용할 수 있는 연산자와 피연산자의 관계에 기초한 수학적 연산작용을 발전시켰다. 동사의 의미는 의미-인지 도식으로 설명되는데, 이것은 서로 다른 연산자와 피연산자로 구성된 형식화된 표현이다. 인간의 인지 기능은 언어로 표현되며, 언어는 인간의 의사소통, 사고 행위 및 인지학습의 핵심적 기능을 담당한다. 인간의 언어정보처리 메카니즘은 매우 복잡한 과정이기 때문에 언어정보처리와 관련된 언어심리학, 인지언어학, 형식언어학, 신경해부학 및 인공지능학 등의 관련된 분야의 학제적 연구가 필요하다.

• Korean Journal of Cognitive Science
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• v.30 no.3
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• pp.157-174
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• 2019

Motivation of human individuals to perform on intellectual tasks can be hampered by identity threat from intellectual machines. A laboratory experiment examined whether individuals' performance loss on intellectual tasks appears under human identity threat. Additionally, by affirming alternative attributes of human identity, researchers checked whether group-affirmation alleviate the performance loss on intellectual tasks. This research predicted that under high social identity threat, individuals' performance loss on the intellectual tasks would be moderated by valuing alternative attributes of human identity. Experiment shows that when social identity threat is increased, human individuals affirmed alternative human attributes show higher performance on intellectual tasks than individuals non-affirmed. This effect of human-group level affirmation on performance loss did not appear in the condition of low social identity threat. Theoretical and practical implications were discussed.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.137-147
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• 2018

To prepare for and implement policies for the Fourth Industrial Revolution, which is characterized by convergence, super-connectivity, and AI, this study summarized the effects and characteristics of individual technologies on our society and discussed the issues with humanity and social science perspectives. As a result, in terms of AI technology, the issues of job losses, project-type works, basic income and robot taxes, accountability of AI, and algorithm inequality were dealt with. Security, cyber hacking and privacy infringement issues were highlighted in big-data technology. In the part of block-chain and bioengineering, the society of decentralization, the concentration, digital divide, and ethical issues were discussed. On-demand economic aspects highlighted the problems of civil ethics and human commercialization. Lastly, the development of VR is discussed including side effects such as cyber-syndrom, avoidance of reality, and so on.

• Korean Journal of Cognitive Science
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• v.1 no.2
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• pp.175-192
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• 1989

The main problems of artificial intelligence (AI)which are vividly being discussed today are not only scientific but also involve serious philosophical dimension.The purpose of this paper is to analyze the computer scientist's definitions of AI and by this method uncober and examine the controversial arguments and problems.The result is to clarify the meaning of AI-research program. It can be said that we can clssify the definitions of AI in various types according to the interest and purpose of AI-reasearchers or the strength of their arguments.But this leaves much to be considered.We have also to consider and analyze the following related problems: Understanding how we grasp human intelligence,what relations there are between intelligence and the brain,and what the logical structure of simulating and copying is with the computer. In this respect,the key problem in AI-research is not the matter of it's use and experience such as computer technonolgy,rather it is the philosophical problem of the a priori such as logic,analysis of the concept.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.33-38
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• 2006

인공지능 분야에서는 합의된 개념을 정의하고, 개념과 개념사이의 관계를 표현하여 인간과 시스템이 지식을 공유하는 것으로 온톨로지를 정의하고 있다. 현재까지 영상이해를 위해 온톨로지를 설계하고 이용하는 연구가 진행되어 왔다. 그러나 기존의 영상이해에 관한 연구는 개념적인 연구에 그칠 뿐 구체적인 방법을 제시하지는 못하고 있다. 본 논문에서는 온톨로지로 표현한 지식에 근거하여 영상의 처리, 분석 해석 과정을 통해 영상을 이해하는 영상이해 시스템의 프레임워크를 제안한다. 영상이해 과정은 i)특정 부야의 지식을 온톨로지로 표현하고, ii)영상 처리 및 분석 과정을 통해 영상을 구성하는 객체들의 속성을 추출하며, iii)온톨로지 추론을 통해 객체의 속성으로부터 객체를 정의하여 영상을 해석한다. 그리고 제안한 프로세스에 기반 하여 영상이해 시스템을 구축하고 특정 분야에서의 실험을 통하여 제안된 시스템의 효용성을 확인한다.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.12
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• pp.485-496
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• 2018

So far, the deep learning, a field of artificial intelligence, has achieved remarkable results in solving problems from unstructured data. However, it is difficult to comprehensively judge situations like humans, and did not reach the level of intelligence that deduced their relations and predicted the next situation. Recently, deep neural networks show that artificial intelligence can possess powerful relational reasoning that is core intellectual ability of human being. In this paper, to analyze and observe the performance of Relation Networks (RN) among the neural networks for relational reasoning, two types of RN-based deep neural network models were constructed and compared with the baseline model. One is a visual question answering RN model using Sort-of-CLEVR and the other is a text-based question answering RN model using bAbI task. In order to maximize the performance of the RN-based model, various performance improvement experiments such as hyper parameters tuning have been proposed and performed. The effectiveness of the proposed performance improvement methods has been verified by applying to the visual QA RN model and the text-based QA RN model, and the new domain model using the dialogue-based LL dataset. As a result of the various experiments, it is found that the initial learning rate is a key factor in determining the performance of the model in both types of RN models. We have observed that the optimal initial learning rate setting found by the proposed random search method can improve the performance of the model up to 99.8%.

• The Journal of Korean Association of Computer Education
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• v.22 no.4
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• pp.35-45
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• 2019

How future generations perceive coexistence with intelligent robots is an important element of how SW and artificial intelligence education should be designed and conducted. This study conducted a survey of 214 first graders in middle school and looked at differences in understanding and perception of coexistence through empathy and expected problem situations depending on the type of intelligent robot. As a result of the analysis, Firstly, if the form was not explicit, it was recognized as a top-down relationship, and Second, in the case of human form, it was ready to recognize intelligent robots and communicate with them. Third, Many people were feeling Emotion in the Robot shape AI. Fourth, there was a vague sense of uneasiness about simple mechanical robots. The study is meaningful as a case study to confirm awareness of intelligent robots and needs to consider and establish awareness of whether they can coexist and live together with robots by age group as well as middle school students.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.87-99
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• 2021

As face-to-face social exchanges are limited by the pandemic, the influence of the metaverse, a virtual space crosses virtual and reality, is gradually expanding. Various metaverse platforms are currently taking advanced AI technology to provide users with a more diverse experience. However, as a result, if AI-human communion in the metaverse space is as active as the relationship between humans, this may lead to side effects that threaten humanity. This study emphasized the value of empathy as a way to minimize the side effects, and suggested that the concept and role of empathy need to be expanded. Accordingly, we conducted an empirical study to examine the difference between social relationship in the metaverse and in real life at the current level, and based on the results, we predicted the future social relationship in the environment where AI was applied to the metaverse. Combining the study, we proposed "Digital Human Empathy" for human dignity in the digital age.

• Annual Conference on Human and Language Technology
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• 2020.10a
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• pp.237-240
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• 2020

사전학습 언어모델은 다양한 자연어처리 작업에서 높은 성능을 보였다. 하지만, 사전학습 언어모델은 문장 내 문맥 정보만을 학습하기 때문에 단어간 의미관계 정보를 추론하는데는 한계가 있다. 최근에는, 사전학습 언어모델이 어느수준으로 단어간 의미관계를 이해하고 있는지 다양한 Probing Test를 진행하고 있다. 이러한 Test는 언어모델의 강점과 약점을 분석하는데 효율적이며, 한층 더 인간의 언어를 정확하게 이해하기 위한 모델을 구축하는데 새로운 방향을 제시한다. 본 논문에서는 대표적인 사전 학습기반 언어모델인 BERT(Bidirectional Encoder Representations from Transformers)의 단어간 의미관계 이해도를 평가하는 3가지 작업을 진행한다. 첫 번째로 단어 간의 상위어, 하위어 관계를 나타내는 IsA 관계를 분석한다. 두번째는 '자동차'와 '변속'과 같은 관계를 나타내는 PartOf 관계를 분석한다. 마지막으로 '새'와 '날개'와 같은 관계를 나타내는 HasA 관계를 분석한다. 결과적으로, BERT_base 모델에 대해서는 추론 결과 대부분에서 낮은 성능을 보이지만, BERT_large 모델에서는 BERT_base보다 높은 성능을 보였다.