AI enables shift from compressing complexity to accommodating it
New arXiv paper argues AI ends the era of forced standardization.
A new arXiv paper by Li Li and Yu Cao (July 2026) argues that AI is fundamentally transforming how societies balance standardization and individualization. The authors contend that industrial-era standardization wasn't just a capitalist preference but a necessary institutional arrangement to keep large-scale systems manageable under limited information-processing capacity. By reducing variety (compressing complexity), societies could coordinate effectively. AI changes this equation by massively expanding capacity across perception, computation, and execution, allowing systems to accommodate the complexity of individual preferences without sacrificing coordination.
The paper introduces the concept of 'cognitive fixed cost' — the upfront concentration of cognitive labor that now makes personalized production economically viable. Instead of physical adaptation, AI enables information-based adaptation, transitioning from discrete to continuous differentiation. Crucially, standardization hasn't disappeared; it has moved from explicit product-level constraints to implicit generative rules embedded in AI infrastructures. The central question shifts from 'should we have commonality?' to 'who controls the commonality?' The paper concludes that civilization's production logic evolves from compressing complexity to accommodating complexity — a paradigm shift with profound implications for everything from manufacturing to software.
- AI expands perception, computation, and execution capacity, enabling complexity accommodation instead of compression
- Introduces 'cognitive fixed cost' as the upfront cognitive effort that makes personalized production scalable
- Standardization shifts from product-level constraints to infrastructure-level generative rules, raising control questions
Why It Matters
AI is rewriting the rules of mass customization and control over the infrastructure we all rely on.