Game‑Chip Perspective: Foundation‑Model‑Driven Algorithmic Planned Economy and the Capture Risk of Distributive Arbitration Power

Driven by the rise of foundation models, digital socialism has revisited the feasibility of an algorithm‑driven centrally planned economy. Existing debates largely focus on Hayek's knowledge problem and innovation‑incentive issues. This paper proposes an analytical framework of "game chips", which distinguishes transaction chips, exit‑resistance chips, and rule chips. It argues that market laws belong to a spontaneous causal order that can hardly be rewritten, whereas the weighting parameters for algorithmic allocation constitute editable rule chips. Furthermore, it deduces a four‑stage evolutionary path for the gradual capture of algorithmic arbitration power, thereby uncovering the under‑explored political bottleneck of algorithmic planned economies.

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Publication Details

Journal
Knowledge Commons (Lakehead University)
Published
2026-08-20
DOI
https://doi.org/10.17613/02dj3-gbd09
Primary Topic
Digital Economy and Work Transformation
Type
article
Field-Weighted Citation Impact
0.00
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article

Game‑Chip Perspective: Foundation‑Model‑Driven Algorithmic Planned Economy and the Capture Risk of Distributive Arbitration Power

Baowei Shan
Knowledge Commons (Lakehead University)
Digital Economy and Work Transformation
article

Game‑Chip Perspective: Foundation‑Model‑Driven Algorithmic Planned Economy and the Capture Risk of Distributive Arbitration Power

Baowei Shan
article en

Abstract

Driven by the rise of foundation models, digital socialism has revisited the feasibility of an algorithm‑driven centrally planned economy. Existing debates largely focus on Hayek's knowledge problem and innovation‑incentive issues. This paper proposes an analytical framework of "game chips", which distinguishes transaction chips, exit‑resistance chips, and rule chips. It argues that market laws belong to a spontaneous causal order that can hardly be rewritten, whereas the weighting parameters for algorithmic allocation constitute editable rule chips. Furthermore, it deduces a four‑stage evolutionary path for the gradual capture of algorithmic arbitration power, thereby uncovering the under‑explored political bottleneck of algorithmic planned economies.

Knowledge Commons (Lakehead University)
Openalex Percentile: Top 6%
Digital Economy and Work Transformation
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