인공지능 예측시스템이 민간경비에 미치는 영향분석과 입법적 대응방안

Abstract

This study analyzes the impact of prediction systems, a rapidly developing artificial intelligence technology, on the private security sector and suggests legislative responses. First, this study provides an overview of the formation process of AI prediction systems. This includes technical aspects such as machine learning, data processing, and algorithm development, as well as social and ethical contexts. Second, it analyzes the main characteristics of AI predictive systems and their application in the private security sector based on their effectiveness. In the process, the accuracy, speed, and level of automation of the system are discussed. Third, the positive and negative impacts of AI predictive systems on private security are assessed. Positive impacts include crime prevention, increased efficiency, and faster response times, while negative impacts include invasion of privacy, liability for errors, and job losses. Finally, based on these impacts, the study explores legislative responses, including clarifying the responsibility of AI prediction systems, strengthening privacy protection, and standardizing technology. This study highlights various issues that will inevitably arise as AI prediction systems are integrated into society and emphasizes the importance of a legal framework to address them. It also forecasts the long-term changes that the introduction of AI in the private security sector will bring, and proposes a legal framework for sustainable and fair technology utilization.