Which Rules Matter Now? Policy-Centroid Routing Before an Intelligent System Acts
2026-08-31 • Artificial Intelligence
Artificial IntelligenceComputers and Society
AI summaryⓘ
The authors explain that before a smart system can decide if an action is okay, it first has to figure out which rules or policies might apply. Because many rules can overlap or interact, the authors propose a method called policy-centroid routing, which simplifies these rules into key points and checks if the action is close enough to any of them to need a closer look. This creates a list of policies to review, rather than making a decision outright. They also describe several tests and comparisons to see how well this method finds relevant rules without missing important details. The paper includes an example but does not provide actual results from real data.
policy-centroid routingsemantic spacepolicy regimesnatural language processingclassificationrule compliancesemantic retrievalstructured workflowsselective predictionpolicy geometry
Authors
Thomson D. Nguy
Abstract
Before an intelligent system can decide whether an action is allowed, it must first know which rules the action has approached. A single proposed action can implicate several policy regimes at once. Their requirements may stack, overlap, or qualify one another, yet many remain written in natural language while the action itself arrives as an incomplete description of intent. The first problem is not judgment. It is attention. Policy-centroid routing creates a layer before adjudication. It compresses expressions within each policy regime into one or more representative centroids, places the proposed action in the same semantic space, applies a declared measure, and routes every regime crossing a declared threshold to authoritative review. Several regimes may trigger at once. The output is a review agenda, not permission, prohibition, legality, breach, compliance, certification, or enforcement. The paper develops six falsifiable propositions and seven follow-on studies comparing the hypothesis with structured workflows, lexical and semantic retrieval, hierarchical and direct classification, and selective prediction under matched review burden. The studies are designed to identify where policy geometry recovers applicable regimes, where compression loses rare or overlapping obligations, and where the mechanism should abstain. The paper includes a synthetic worked example and reports no empirical efficacy result.