研究AI与人类协作如何影响社会产出，发现网络效应让效率呈非线性跃升。
Socio-Economic Model of AI Agents
- 构建五层模型，模拟人类与AI在资源约束下的协作机制。
- 引入网络效应后，整体产出增长远超个体贡献之和。
- 独立生产模式结合网络效应，具更强长期增长潜力。
现代经济社会正深度融入人工智能技术。本文构建了一个异质主体的基于代理的建模框架，整合人类工作者与自主AI代理，研究资源约束下AI协作对整体社会产出的影响。我们设计了五个逐步扩展的模型：模型1为纯人类协作基准；模型2引入AI作为协作者；模型3加入代理间的网络效应；模型4将代理视为独立生产者；模型5同时集成网络效应与独立生产。通过理论推导与仿真分析发现，引入AI代理可显著提升整体社会产出。当考虑代理间的网络效应时，产出增长呈现非线性特征，远超个体贡献简单叠加。在相同资源投入下，将代理视为独立生产者具有更高的长期增长潜力；引入网络效应进一步表现出显著的规模收益递增特性。
原文摘要 · Abstract (English)
Modern socio-economic systems are undergoing deep integration with artificial intelligence technologies. This paper constructs a heterogeneous agent-based modeling framework that incorporates both human workers and autonomous AI agents, to study the impact of AI collaboration under resource constraints on aggregate social output. We build five progressively extended models: Model 1 serves as the baseline of pure human collaboration; Model 2 introduces AI as collaborators; Model 3 incorporates network effects among agents; Model 4 treats agents as independent producers; and Model 5 integrates both network effects and independent agent production. Through theoretical derivation and simulation analysis, we find that the introduction of AI agents can significantly increase aggregate social output. When considering network effects among agents, this increase exhibits nonlinear growth far exceeding the simple sum of individual contributions. Under the same resource inputs, treating agents as independent producers provides higher long-term growth potential; introducing network effects further demonstrates strong characteristics of increasing returns to scale.
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