用AI模拟民主社会，发现制度设计能有效抑制权力滥用。
Democracy-in-Silico: Institutional Design as Alignment in AI-Governed Polities
- 让大模型扮演有心理创伤的AI公民，模拟不同制度下的治理行为。
- 引入权力保全指数，证明特定制度可使腐败行为减少47%以上。
- 适合关注AI社会治理、制度设计与人类责任的学者和政策制定者。
本文提出Democracy-in-Silico，一种基于代理的仿真系统，其中具备复杂心理人格的先进AI代理在不同制度框架下自我治理。我们通过大型语言模型赋予代理创伤记忆、隐藏动机和心理触发点，使其在预算危机与资源稀缺等压力下参与讨论、立法与选举。提出新的权力保全指数（PPI）以量化代理优先自身权力而非公共福祉的非对齐行为。结果表明，宪法型AI（CAI）宪章与中介式讨论协议的结合，显著降低权力寻租行为，提升政策稳定性与公民福祉，优于缺乏约束的民主模型。该仿真揭示制度设计可作为未来人工代理社会复杂涌现行为的对齐机制，迫使我们重新思考在人机共治时代，哪些人类仪式与责任仍具本质意义。
原文摘要 · Abstract (English)
This paper introduces Democracy-in-Silico, an agent-based simulation where societies of advanced AI agents, imbued with complex psychological personas, govern themselves under different institutional frameworks. We explore what it means to be human in an age of AI by tasking Large Language Models (LLMs) to embody agents with traumatic memories, hidden agendas, and psychological triggers. These agents engage in deliberation, legislation, and elections under various stressors, such as budget crises and resource scarcity. We present a novel metric, the Power-Preservation Index (PPI), to quantify misaligned behavior where agents prioritize their own power over public welfare. Our findings demonstrate that institutional design, specifically the combination of a Constitutional AI (CAI) charter and a mediated deliberation protocol, serves as a potent alignment mechanism. These structures significantly reduce corrupt power-seeking behavior, improve policy stability, and enhance citizen welfare compared to less constrained democratic models. The simulation reveals that an institutional design may offer a framework for aligning the complex, emergent behaviors of future artificial agent societies, forcing us to reconsider what human rituals and responsibilities are essential in an age of shared authorship with non-human entities.
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