Jake Lawrence · Science and Technology Studies · AI Systems theme
Every planning layer is a classification system. The question is whether we build it deliberately or let it emerge accidentally.
Connects two technical systems (SAGEN, LLM-QP) to Bowker and Star's theory of classification as infrastructure. Argues that the planning layers emerging in LLM architectures reproduce the same dynamics found in institutional classification: invisible category work that distributes consequences unevenly.
SAGEN's blackboard is itself a classification system: it categorizes agent state into six module types. The position paper argues this is not incidental.
LLM-QP classifies queries by execution cost. Every routing decision is a classification decision with consequences the user never sees.
Both examine invisible classification. The position paper finds it inside AI architecture. Stance Design finds it at the product layer, where the system classifies users by what relational posture they receive.
Both apply Bowker and Star. The position paper identifies the pattern in AI; The Invisible Architecture traces it in psychiatric diagnosis.
Both examine how classification distributes consequences while remaining invisible. One in AI architecture, the other in AI deployment.
The same infrastructure dynamics in LLM planning layers and special education placement. Neither was designed for the people being sorted.
Classification as Infrastructure names the residual category in the abstract. Unratified makes you author one: every required field in the enrollment console manufactures the population it cannot represent, and then hands you that population to live inside.
Classification as Infrastructure names the pattern: each category is locally honest and globally blind. Ninety-Seven Percent Off makes it a supply chain, where the card merchant sees only cards, the pool only accounts, the relay only a clean product, and the fraud is legible to no single layer, which is exactly how it survives.
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