探讨完全自动化经济中效率与去中心化的本质关系
Alignment of a Total Automation Economy
- 用库兰特维奇对偶理论分析自动化经济的最优生产机制
- 发现自动化追求市场定价目标可能产生对齐风险
- 为多智能体AI系统设计提供理论参考
我们从完全自动化经济的视角出发，即生产过程无人参与制造或管理。自然会提出：这种经济本质上是中央计划经济，还是因效率需求必须去中心化为竞争性代理的自主生产？苏联经济学家列昂尼德·库兰特维奇发展了线性规划方法，供企业或政府优化生产。讽刺的是，他同样被普遍认为证明了最高效的生产依赖于去中心化——即存在竞争代理的自由市场经济。本文详细回顾了库兰特维奇的对偶理论。我们将经济目标设定为以（人类）市场价格加权最大化生产。一个根本问题是：随着经济演进，自动化追求此目标是否可能产生对齐漏洞？另一个问题是：对偶理论能否为一般性的智能体人工智能系统（多智能体系统）提供洞见。
原文摘要 · Abstract (English)
We consider economic theory from the perspective of a total automation economy, one with no human involvement in production either in manufacturing or in management. One can naturally ask whether a total automation economy is fundamentally a centrally planned economy or, alternatively, whether efficiency demands decentralization into local decisions by competing agents -- agentic production. A soviet economist, Leonid Kantorovich, developed linear programming as a method companies or governments can use to optimize production. Ironically, he is also generally credited with showing that the most efficient production is achieved through decentralization -- a free market economy with competing agents. Here we review Kantorovich's dualization in detail. We take the objective of the economy to be maximizing production weighted by (human) market price. A fundamental issue is whether an automated pursuit of this objective might have alignment vulnerabilities as the economy evolves. Another question is whether dualization provides insight into the utility of agentic AI systems (multi-agent AI systems) generally.
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