인공지능과 빅데이터를 통한 이미지의 존재론과 창발성 = Image Ontology and Emergent Properties through AI and Big Data

다국어 초록 (Multilingual Abstract)

This paper presents a study of 'image ontology and emergent properties through artificial intelligence and big data'. In Chapter 2, 'big data and image ontology' and 'image ontology' are examined through the 'image of everyday images and art imitation of artificial intelligence', and from the 'viewpoint of a cloud computing system'. We compare and study the 'ontology of big data'. In Chapter 3, 'image ontology by ‘deep learning operation' and a 'study of diversity / variability through ’deep learning' is studied and 'image ontology by ‘deep learning operations' is studied through 'creativity and emergent properties' research. Recent deep learning on artificial intelligence explores the reasons for 'lane' or 'long-term compensation' rather than 'best' or 'immediate compensation' through inference. To this end, we will examine the concepts of 'diversity/variability' of artificial intelligence and of big data and the concept of the creativity of art. In the last chapter, we examine the history of 'creativity' in an artwork or artistic image that develops into 'originality - creativity - emergent properties', and explains the situation that is understood as 'universal creativity' and 'reorganized creativity' today. In particular, we analyze how images are created by 'deep learning' and how realism is realized in actual images created by Google's 'deep dream'. In addition, we study specifically the ontology and inventiveness of images through a case study of technological engineering works by the contemporary artist Son Yeo-Ul, who uses big data as a material and expresses the emergence between prediction and unpredictability.

국문 초록 (Abstract)

본 연구는 ‘인공지능과 빅데이터를 통한 이미지의 존재론과 창발성‘에 대해서 연구한다. 2장에서는 ‘빅데이터와 이미지 존재론’에서는 ‘일상의 이미지와 인공지능의 미술 모방의 이미지’를 통해서 ‘이미지의 존재론’을 살펴보고, ‘클라우드 컴퓨팅 시스템의 리좀적 네트워킹과 복수성’의 관점에서 ‘빅데이터의 존재론’을 비교, 연구한다. 3장, ‘딥러닝 연산에 의한 이미지 존재론’에서는 ‘딥러닝을 통한 다양성/가변성’ 연구와 더불어 ‘창의성과 창발성’ 연구를 통해서 ‘딥러닝 연산에 의한 이미지 존재론’을 비교, 연구한다. 최근의 인공지능의 딥러닝이 추론을 통해서 ‘최선’ 혹은 ‘즉각적 보상’이 아닌 ‘차선’ 혹은 ‘장기적 의미의 보상’을 도모하는 이유를 알아본다. 이를 위해서 인공지능과 빅데이터의 ‘다양성/가변성’의 개념과 더불어 미술의 창의성의 개념을 연동하여 살펴본다. 마지막 장에서는 독창성-창의성-창발성으로 전개되는 미술 작품 혹은 예술적 이미지에 담긴 ‘창의성’의 변천사를 살펴보고, 오늘날 ‘보편적 창의성’, ‘재편되는 창의성’ 개념으로 이해되고 있는 상황을 설명한다. 특히 딥러닝이 만드는 이미지들과 최근 구글의 딥드림이 만든 실제 이미지들에서 어떻게 창발성이 구현되는지를 분석한다. 덧붙여 빅데이터를 재료로 삼고 예측과 예측 불가능성 사이에서 창발성을 실천하고 있는 현대 미술가 손여울의 기술공학적 작품의 사례 분석을 통해서 이미지의 존재론과 창발성이 무엇인지를 구체적으로 연구한다.

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