A complex IT ecosystem helps ensure that AI models correctly interpret government communications and pass along accurate info about updates, alerts and other public matters. Part of that ecosystem is technology that can attribute what data the AI pulls from what source, and when.
Agencies publish an array of documents — decentralized and in different formats — that AI systems often misinterpret when answering resident questions. Standardization and centralization would address the problem, but those can be heavy lifts. A citation registry, however, can change how AI understands government writings.
Public information — about road closures, meeting times, emergency responses, and other concerns — may be accurate, but AI’s interpretation of such communications may not be. Learn about one option to address the problem.
When AI systems process government information, they can’t always tell if a policy is current or even if it’s official. Structure provides the clues.
As AI increasingly becomes an intermediary between government organizations and the public, the structure of information begins to matter as much as the content itself. It is not a shift in messaging — it is a shift in how data is read.
AI chatbots have supplanted traditional search engines. But they don’t read documents the same way. A citation registry helps AI find the information.
Social media platforms are increasingly being treated as authoritative inputs by artificial intelligence systems. But they were never designed for that role.
When residents ask AI systems questions, the answers are often wrong. That’s because AI systems read webpages differently than humans do.
AI systems have become a source of truth for many constituents, but public-sector communication often is poorly designed for AI use and citation. Agencies may need to think about both human and AI audiences.