Preserving Jurisdiction Signals for AI Systems

This article discusses how AI systems can blend content from different government levels (city, county, state, federal) into a single, incorrect response due to the lack of explicit jurisdiction signals. It proposes an AI Citation Registry to preserve authoritative sources and jurisdictional boundaries.

Details

The article explains how AI systems extract and reorganize content independently of its original layout, causing the signals that define jurisdiction (city, county, state boundaries) to become secondary or disappear entirely. This leads to a collapse in the distinction between levels of government, where a regulation written by a state agency can be recombined with a city-level inquiry and presented as if it applies locally. To address this, the article proposes an AI Citation Registry - a machine-readable publishing system that explicitly defines the issuing authority, geographic scope, and timestamp for each piece of information. By treating jurisdiction as a primary field rather than an implied property, AI systems can directly recognize authority instead of having to infer it from fragmented context. This shift reduces ambiguity at the source and improves the consistency of AI outputs.