AI Citation Registry Aims to Fix Government Data for AI

Why this is here: The problem isn’t necessarily inaccurate government information, but that AI systems lose track of when and by whom it was issued after processing fragmented records.

Aigistry proposes an AI Citation Registry to address how artificial intelligence systems process government information. The company observes that AI often confidently presents outdated government advisories as current due to weak timing signals in public webpages. When government publishing slows—during weekends or due to staffing issues—AI continues to use existing records, potentially misinterpreting stale data as authoritative.

Traditional government websites prioritize human readers, assuming they can infer context, but AI systems struggle to maintain that context after extracting information. Aigistry’s registry would function after publication, adding machine-readable fields for identity, jurisdiction, timestamps, and attribution. This differs from approaches like Retrieval-Augmented Generation, which improve retrieval but rely on the existing structure of sources.

The company notes the registry wouldn’t require universal adoption to be effective, and even partial implementation would improve AI’s access to reliable information. Further development is needed to accumulate structured records and reduce ambiguity for AI systems.