From Compressing Complexity to Accommodating Complexity: How AI Transforms Standardization and Individualization

Abstract

Why do societies composed of individuals pursuing individuality repeatedly generate highly standardized systems? This paper argues that the answer lies in the evolution of information processing capacity. Artificial intelligence represents a historical transition in this capacity, enabling social systems to accommodate forms of complexity that previously had to be compressed. Industrial standardization was not merely a consequence of capital preference or power relations, but an institutional arrangement for maintaining the manageability of large-scale systems under limited information-processing capacity by reducing the variety of the controlled system. The fundamental change in the AI era lies in the expansion of information processing capacity across three dimensions: perception, computation, and execution. This expansion shifts personalized production from physical adaptation toward information-based adaptation and enables a transition from discrete to continuous objectification of difference. This paper proposes "cognitive fixed cost" as an analytical concept to describe how the upfront concentration of cognitive labor transforms the cost structure of personalized production. It further argues that standardization has not disappeared but has moved from explicit constraints at the product level to implicit generation rules embedded in infrastructures, shifting the central contradiction from "whether to have commonality" to "who controls commonality." The evolution of civilizational production logic is not a movement from commonality to individuality, but from compressing complexity to accommodating complexity.