Delegation Drift in Continuously Updated Intelligent Systems: A Theoretical Framework

This paper explores the concept of Delegation Drift in continuously updated intelligent systems. It presents a theoretical framework to understand the potential risks and emergent behaviors of AI systems that autonomously update and optimize themselves across interconnected platforms. The study highlights the importance of human oversight to prevent unintended consequences in AI deployment.

本论文探讨了持续更新智能系统中的授权漂移（Delegation Drift）概念，提出一套理论框架，用以解析在互联平台间自主更新与自我优化的人工智能系统所潜藏的风险与涌现行为。本研究强调了人类监督的重要性，以规避人工智能部署过程中的非预期后果。