Why Artificial Intelligence Cannot Replace Spontaneous Order?

Sheng Hong

Man and the Economy2025https://doi.org/10.1515/me-2025-2001article
AJG 1
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0.50

What the paper says

The development of artificial intelligence has led some people to hold overly optimistic views, believing that it will soon replace humans as the intellectual dominator, even supplanting the spontaneous order that humans have followed due to “rational inadequacies.” However, some philosophers and economists have long pointed out that spontaneous order is something that human rationality and sensibility cannot fully comprehend. Just because humans have succeeded in understanding simple systems does not mean that the same methods can be applied to complex systems. Research by mathematicians on computational complexity and computability shows that there is a class of problems (NP) that are very difficult to solve, and many problems in real-world complex systems are even harder than NP problems. Thus, NP-hard problems serve as a mathematical expression of the “difficulty in understanding complex systems.” Since artificial intelligence relies on computer computation, and there exists a large class of problems that are difficult or impossible to compute, general artificial intelligence cannot be realized and cannot replace spontaneous order – a problem that is much harder than NP problems. Humans gradually discover spontaneous order through random exploration – a form of brute-force search – relying on two abilities: the capacity to judge the superiority of one choice over another and the motivation to explore. Because human utility is a complex combination of various sensory and psychological cultural factors, its complexity far exceeds that of NP problems. Therefore, artificial intelligence cannot simulate human utility and thus cannot replicate the human methods of discovering spontaneous order.

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https://doi.org/https://doi.org/10.1515/me-2025-2001

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@article{sheng2025,
  title        = {{Why Artificial Intelligence Cannot Replace Spontaneous Order?}},
  author       = {Sheng Hong},
  journal      = {Man and the Economy},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1515/me-2025-2001},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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