AI系统互操作引发意外风险，需通过注册与监管降低系统性危机
The Problem of Algorithmic Collisions: Mitigating Unforeseen Risks in a Connected World
- 提出算法系统交互风险的治理框架，强调透明化与责任追溯
- 指出多系统无意识协同可致市场崩盘、能源中断等连锁后果
- 适合关注数字治理、人工智能政策与系统安全的研究者
人工智能等自主算法系统的广泛部署带来了新的系统性风险。尽管关注点常集中于单个算法的功能，但更关键且被低估的危险来自算法之间的相互作用，尤其当各系统彼此缺乏认知，或部署方未意识到其运行于复杂的算法生态中时。这些交互可能引发不可预见且迅速恶化的负面后果——从市场崩溃、能源供应中断，到潜在的物理事故和公众信任流失，往往超出人类监控能力及法律干预范围。现有治理体系因缺乏对复杂交互生态的可见性而失效。本文阐述了该挑战的本质，并提出初步政策建议：通过分阶段系统注册、部署许可机制以及强化监测能力，提升透明度与问责性。
原文摘要 · Abstract (English)
The increasing deployment of Artificial Intelligence (AI) and other autonomous algorithmic systems presents the world with new systemic risks. While focus often lies on the function of individual algorithms, a critical and underestimated danger arises from their interactions, particularly when algorithmic systems operate without awareness of each other, or when those deploying them are unaware of the full algorithmic ecosystem deployment is occurring in. These interactions can lead to unforeseen, rapidly escalating negative outcomes - from market crashes and energy supply disruptions to potential physical accidents and erosion of public trust - often exceeding the human capacity for effective monitoring and the legal capacities for proper intervention. Current governance frameworks are inadequate as they lack visibility into this complex ecosystem of interactions. This paper outlines the nature of this challenge and proposes some initial policy suggestions centered on increasing transparency and accountability through phased system registration, a licensing framework for deployment, and enhanced monitoring capabilities.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。