Signal Paper argues AI is shifting standardization from explicit product rules to implicit infrastructure

Summary

A theoretical paper argues that artificial intelligence represents a historical transition in society's information-processing capacity, enabling social systems to accommodate forms of complexity that previously had to be compressed through standardization. It reframes industrial standardization not merely as a product of capital preference or power relations, but as an institutional arrangement that maintained the manageability of large-scale systems under limited information-processing capacity by reducing the variety of the controlled system. The paper argues the fundamental change in the AI era lies in an expansion of information-processing capacity across three dimensions, perception, computation, and execution, which shifts personalized production from physical adaptation toward information-based adaptation and enables a transition from discrete to continuous objectification of difference. It introduces "cognitive fixed cost" as an analytical concept describing how the upfront concentration of cognitive labor transforms the cost structure of personalized production. The author concludes that standardization has not disappeared but has moved from explicit constraints at the product level to implicit generation rules embedded in infrastructure, shifting the central contradiction from "whether to have commonality" to "who controls commonality."