• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.70-83
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• 2021

The issue of predicting the relationship between humans and AI robots is a 'strong AI' problem. Many experts predict the tragic ending which is a strong AI with superior thinking ability than humans will conquer humans. Due to the expectations of AI robots are projected onto media, the 'morally good AI' that meets human expectations is an important issue. However, the demand for good AI and the realization of perfect technology is not limited to machines. Rather, it appears as a result of putting all responsibility on humans, driving humans into immoral beings and turning them into human and human problems, which is resulting in more alienation and discrimination. As such, the result of technology interacts with the human being used and its properties are determined and developed according to the reaction. This again affects humans. Therefore, AI technology that considers human emotions in consideration of interaction is also important. Therefore, this study will clarify the process that the demand for 'Good AI' in the relationship of AI to humans with Randall Collins' Interaction Ritual Chain. Emotional energy in Interaction Ritual Chain has explained the formation of human bonds. Also, the methodology is a type of thinking experiment and explained through Janet and surrounding characters in the TV show .

• Trans-
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• v.16
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• pp.107-133
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• 2024

Narratives are fundamental to human cognition and social culture, serving as the primary means by which individuals and societies construct meaning, share experiences, and convey cultural and moral values. The field of artificial intelligence, which seeks to mimic human thought and behavior, has long studied story generation and story understanding, and today's Large Language Models are demonstrating remarkable narrative capabilities based on advances in natural language processing. This situation raises a variety of changes and new issues, but a comprehensive discussion of them is hard to find. This paper aims to provide a holistic view of the current state and future changes by exploring the intersections and interactions of human and AI narrative intelligence. This paper begins with a review of multidisciplinary research on the intrinsic relationship between humans and narrative, represented by the term Homo narrans, and then provide a historical overview of how narrative has been studied in the field of AI. This paper then explore the possibilities and limitations of narrative intelligence as revealed by today's Large Language Models, and present three philosophical challenges for understanding the implications of AI with narrative intelligence.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2016.11a
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• pp.281-282
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• 2016

본 논문에서는 증대하고 있는 재난안전사고에 효율적으로 대응할 수 있도록 훈련할 수 있는 시뮬레이터 플랫폼을 제안한다. 최근 재난은 복합적이며, 타 부처 간의 협력이 필요한 대규모 성격을 띠고 발생하는 빈도가 커지고 있는 반면 훈련도구는 각 부처별로 재난유형별 시스템들이 필요에 따라 독립개발 및 운영되고 있기 때문에 다양한 시나리오에 의한 종합적 분석결과를 기반으로 하는 스마트한 재난대응 방안 모색이 어려운 실정이다. 이러한 이유로 본 연구에서는 재난에 대응하는 사람의 다양한 능력을 반영하여 인공지능 기반 하에 훈련 시나리오가 생성될 수 있는 지능형 재난대응훈련 시뮬레이터 개발을 위한 플랫폼을 제안한다. 또한 몰입감을 가지고 가상의 상황 하에서 훈련할 수 있도록 가상현실 기반의 시뮬레이터 플랫폼이 될 수 있도록 제안한다.

• Trans-
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• v.12
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• pp.1-19
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• 2022

This study predicts and raises the changes that AI will bring to dance art when machine-based choreography began, and finds questions we can ask as human artists. Research suggests that one of the crises of dance in the era of machine creative arts is that artificial intelligence does not stay in the tool of human choreography but becomes the subject of choreography. It is based on the political discourse of choreography that artificial intelligence has the power to control and restrict human dancers. This comes from a sense of crisis that the AI takes over the area of choreography and the human choreographer remains an incompetent coordinator, and as a result, the dancer's dancing body can be reduced to a mechanical body controlled by AI. In order for these concerns not to become a reality, this study proposes three measures. First, choreographer and dancer should develop digital literacy to live in the age of AI art. Secondly, choreographer should acquire the ability to accurately distinguish the roles of human choreographer, dancer, and AI in creative work. Thirdly, various levels of discourse on AI dance should be formed by actively conducting mutual media research of dance and technology. Through these efforts, the human dancer will exist as a subject of art, not a passive agent in the new dance ecosystem brought by the innovation of artificial intelligence technology and will be able to face an era coexistence with artificial intelligence creativily and productively.

• Journal of Digital Convergence
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• v.17 no.10
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• pp.251-258
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• 2019

In the future, various products are created in various fields using artificial intelligence. In this age, it is a very important problem to know the operation principle of artificial intelligence learning method and to use it correctly. This paper introduces artificial intelligence learning methods that have been known so far. Learning of artificial intelligence is based on the fixed point iteration method of mathematics. The GD(Gradient Descent) method, which adjusts the convergence speed based on the fixed point iteration method, the Momentum method to summate the amount of gradient, and finally, the Adam method that mixed these methods. This paper describes the advantages and disadvantages of each method. In particularly, the Adam method having adaptivity controls learning ability of machine learning. And we analyze how these methods affect digital signals. The changes in the learning process of digital signals are the basis of accurate application and accurate judgment in the future work and research using artificial intelligence.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.12-12
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• 2023

지하수자원 관리의 정량적 및 정성적 측면에 있어, 최첨단 인공지능 언어 모델인 ChatGPT의 혁신적인 기능이 활용될 수 있다. 본 발표에서는 지하수 자료에 대한 분석과 도출된 문제의 중요도에 따른 목표를 설정, 그리고 지하수 관리 전략 개발에 있어서의 ChatGPT 활용 방법을 논의할 것이다. 이를 위한 구체적 사례로, 지하수자원 관리에 활용될 수 있는 다양한 도구들의 개발과 고도화에 ChatGPT가 기여하는 방식을 살펴볼 것이다. 이러한 개별 도구들은 지하수자원 관리 결정에 있어 더 나은 예측 및 평가를 제공하여, 지하수 자원 관리의 효율성을 도모할 수 있다. 또한, ChatGPT의 문제 발견 및 해결책 제안 능력에 대해서도 다룰 것이다. 이를 통해 지하수 관리에 있어서의 다양한 문제를 식별하고, 이해당사자들이 보다 효과적으로 대응할 수 있는 방안을 찾아낼 수 있을 것이다. 또한 ChatGPT가 제공하는 다양한 정보 및 문제에 대한 솔루션 접근 방식을 활용한 브레인스토밍 방법을 설명할 것이다. 추가적으로, 일반 인공지능(AGI)의 개발에 근접하면서 지하수 관리의 자동화 및 가속화 그리고 산업 및 환경에 미칠 수 있는 영향에 대해 고찰해 볼 것이다. 이를 위하여, ChatGPT와 같은 인공지능 기술이 더욱 고도화되고 향상되면서, 지하수 관리 및 관련 분야에서의 의사결정, 계획 수립, 그리고 모니터링과 같은 작업들이 어떻게 변화할지에 대하여 토의할 것이다. 본 발표는 지하수 자원 관리 분야에서 ChatGPT와 같은 인공지능 기반 접근법의 가치를 보여주며, 복잡한 지하수 환경 문제를 해결하는 데 있어 첨단 기술의 활용 가능성을 강조할 것이다. 또한, AGI가 등장할 때까지 여전히 요구되는 지하수 분야 도메인 지식과 전문기술의 중요성을 강조할 것이다. 지하수 관리자들의 도메인 지식과 전문적 기술은 인공지능 기반 도구와 결합되어 보다 정확한 분석, 예측 및 해결책 도출을 가속화하며 정교화할 것이다. 결론적으로, 지하수 관리에 대한 종합적인 이해와 전문성을 갖춘 전문가들의 인공지능 기술활용은 지속가능한 지하수의 첨단 관리 효과적 달성에 중요한 계기가 될 것으로 판단한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.172-175
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• 2000

무인자율항체는 자동차, 선박, 잠수함과 같이 인간에 의해 직접 조종되는 유인항체에 인간의 역할을 대신할 수 있는 지능시스템을 배치하여 전체적 혹은 부분적으로 무인화한 이동체를 말한다. 무인자율항체에서 사용되는 소프트웨어는 인식, 사고, 행위와 같은 인간의 지적능력을 내포한 인공지능시스템이어야 한다. 자율무인잠수정, 자율운항선박과 같은 저속무인자율항체는 무인항공기나 무인차량과 같이 빠른 판단과 제어가 요구되는 지능제어시스템과는 다른 특성을 가진다. 저속무인자율항체에서 가장 주목되는 특성은 주위 환경 변화속도와 운항속도에 따른 긴박감의 차이이다. 고속자율항체에서는 제어시스템의 처리속도에, 저속자율항체에서는 제어시스템의 신뢰성에 비중을 둔다. 본 연구에서는 이와 같은 저속무인자율항체의 특성과 기능별 독립성 보장, 반응형 및 인식형 인공지능 기법의 융화 극대화에 촛점을 맞춘 RVC(Reactive Layer-Virtual World-Congnitive Layer) 지능시스템 모델을 제안한다.

• Journal of Convergence for Information Technology
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• v.10 no.8
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• pp.173-178
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• 2020

In the near future, as artificial intelligence and computing network technology develop, collaboration with artificial intelligence (AI) will become important. In an AI society, the ability to communicate and collaborate among people is an important element of talent. To do this, it is necessary to understand how artificial intelligence based on computer science works. An algorithmic education focused on problem solving and learning is efficient for computer science education. In this study, the results of an assessment of computational thinking at the beginning of the semester, a satisfaction survey at the end of the semester, and academic performance were compared and analyzed for 28 students who received algorithmic education focused on problem-solving learning. As a result of diagnosing students' computational thinking and problem-solving learning, teaching methods, lecture satisfaction, and other environmental factors, a correlation was found, and regression analysis confirmed that problem-solving learning had an effect on improving lecture satisfaction and computational thinking ability. For algorithmic education, if you pursue a problem-solving learning technique and a way to improve students' satisfaction, it will help students improve their problem-solving skills.

• Journal of Science and Technology Studies
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• v.19 no.2
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• pp.169-206
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• 2019

This article seeks to explore new relationships and ethics of human and technology by analyzing a cultural imaginary produced by artificial intelligence. Drawing on theoretical reflections of the Feminist Scientific and Technological Studies which understand science and technology as the matter of care(Puig de la Bellacas, 2011), this paper focuses on the fact that artificial intelligence and robots materialize cultural imaginary such as autonomy. This autonomy, defined as the capacity to adapt to a new environment through self-learning, is accepted as a way to conceptualize an authentic human or an ideal subject. However, this article argues that artificial intelligence is mediated by and dependent on invisible human labor and complex material devices, suggesting that such autonomy is close to fiction. The recent growth of the so-called 'assistant technology' shows that it is differentially visualizing the care work of both machines and humans. Technology and its cultural imaginary hide the care work of human workers and actively visualize the one of the machine. And they make autonomy and agency ideal humanness, leaving disabled bodies and dependency as unworthy. Artificial intelligence and its cultural imaginary negate the value of disabled bodies while idealizing abled-bodies, and result in eliminating the real relationship between man and technology as mutually dependent beings. In conclusion, the author argues that the technology we need is not the one to exclude the non-typical bodies and care work of others, but the one to include them as they are. This technology responsibly empathizes marginalized beings and encourages solidarity between fragile beings. Inspired by an art performance of artist Sue Austin, the author finally comes up with and suggests 'artificial intelligence in wheelchair' as an alternative figuration for the currently dominant 'autonomous artificial intelligence'.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.234-237
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• 2021

최근 인공지능에대한 관심과 COVID-19의 영향으로 인공지능을 적용하려는 연구가 계속되고 있다. 인공지능 학습 방식 중 딥러닝에서는 학습 결과에 따라 가중치를 두며 지속적인 학습을 수행한다. 이때 사용하는 가중치에 따라 학습 능력이 향상되게 되지만, 과다 학습으로 인한 퇴화 현상과 잘못된 결과 도출이 되는 경우가 발생한다. 이를 해결하기 위해 본 논문에서는 문제를 해결하기 위해 비연속적 PoW 합의방식을 사용한 블록체인에 가중치와 학습 결과를 지속적으로 보관하여 형상관리를 할 수 있는 시스템을 설계하였다.