Abstract
The quantification of social science remains a longstanding challenge, largely due to the philosophical nature of its foundational theories. Although quantum computing has advanced rapidly in recent years, its relevance to social theory remains underexplored. Most existing research focuses on micro-cognitive models or philosophical analogies, leaving a gap in system-level applications of quantum principles to the analysis of social systems. This study addresses that gap by proposing a theoretical and computational framework that combines quantum mechanics with Generative AI to simulate the emergence and evolution of social norms. Drawing on core quantum concepts--such as superposition, entanglement, and probabilistic measurement--this research models society as a dynamic, uncertain system and sets up five ideal-type experiments. These scenarios are simulated using 25 generative agents, each assigned evolving roles as compliers, resistors, or enforcers. Within a simulated environment monitored by a central observer (the Watcher), agents interact, respond to surveillance, and adapt to periodic normative disruptions. These interactions allow the system to self-organize under external stress and reveal emergent patterns. Key findings show that quantum principles, when integrated with generative AI, enable the modeling of uncertainty, emergence, and interdependence in complex social systems. Simulations reveal patterns including convergence toward normative order, the spread of resistance, and the spontaneous emergence of new equilibria in social rules. In conclusion, this study introduces a novel computational lens that lays the groundwork for a quantum-informed social theory. It offers interdisciplinary insights into how society can be understood not just as a structure to observe but as a dynamic system to simulate and redesign through quantum technologies.
Abstract (translated)
社会科学的量化长期以来一直是一个挑战，主要是因为其基础理论具有哲学性。尽管量子计算近年来取得了迅速发展，但其对社会理论的相关性仍未得到充分探索。目前大多数现有研究主要集中在微观认知模型或哲学类比上，而在系统层面应用量子原理来分析社会体系的研究则相对较少。本研究通过提出一个结合了量子力学与生成式人工智能的理论和计算框架来填补这一空白，旨在模拟社会规范的出现和发展过程。 这项研究基于核心量子概念——如叠加态、纠缠以及概率测量等，将社会视为动态且不确定的系统，并设计了五个理想实验场景。在这些场景中，使用25个生成代理（agents）进行仿真，每个代理被分配为执行者、抵抗者或监管者的角色，其身份会随时间变化。在一个由中央观察员（Watcher）监控的模拟环境中，这些代理相互作用，对监视做出反应，并适应周期性的规范性干扰。 在外部压力下系统能够自我组织并显现涌现模式的过程中，这种交互式环境使得研究得以展开。关键发现表明，当量子原理与生成式人工智能结合时，可以建模复杂社会系统的不确定性、涌现性和相互依赖性。仿真揭示了包括向规范秩序趋同、抵抗的传播以及在社会规则中自发产生的新平衡点在内的多种模式。 总的来说，这项研究引入了一种新颖的计算视角，为基于量子理论的社会学奠定了基础。它提供了跨学科见解，展示了如何通过量子技术将社会理解不仅仅是一个需要观察的结构，而是一个可以模拟和重新设计的动力系统。
URL
https://arxiv.org/abs/2506.03503
