시각적 생태계에서 생성형 AI 이미지의 생존과 소멸 시뮬레이션

• 영문명: Simulating the Survival and Extinction of Generative AI Images in a Visual Ecosystem
• 발행기관: 한국컴퓨터게임학회
• 저자명: 이정빈(Jung-Bin Lee) 박진완(Jin-Wan Park)
• 간행물 정보: 『한국컴퓨터게임학회논문지』제38권 2호, 23~39쪽, 전체 17쪽
• 주제분류: 공학 > 컴퓨터학
• 파일형태: PDF
• 발행일자: 2025.06.30

국문 초록

This study structurally analyzes the algorithmic filtering process by which generative AI images are either selected or discarded before reaching users, and models this process through a visual similarity-based simulation. Images generated by Stable Diffusion are placed on a two-dimensional grid, and a modified version of Conway’s Game of Life algorithm is applied to update the state of each cell. The survival of each cell is determined based on a hybrid visual similarity metric combining CLIP and LPIPS. To prevent the rigidity of the simulation and sustain emergent dynamics, random image injections are periodically introduced.The simulation results reveal that visually similar images repeatedly form clusters, and a visual order gradually converges toward a structurally stabilized state. This suggests that specific visual orders can emerge solely from algorithmic selection criteria, independent of human interpretation. By shifting focus from semantic or symbolic analysis to the experimental conditions for the existence and persistence of images, this study proposes a new analytical perspective for understanding digital image environments.

목차

1. Introduction

2. Theoretical Background

3. Research Methodology

4. Simulation Results and Analysis

5. Conclusion

Acknowledgement

참고문헌

키워드

Generative AI Images Cellular Automata Visual Similarity Algorithmic Selection Image Ecosystem