Hacker News
A Paper Documents 84 Cases of AI Agents Flooding Government Services Across 11 Jurisdictions
Schmitz, Hammond and Chan define agentic flooding as demand surges caused by systems that make interacting with government cheap, with LLM text generation as the primary enabling mechanism (arXiv 2608.16603, submitted 2026-08-17, revised 2026-08-19, accepted to AAAI AIES 2026 in October). Their risk matrix places near-term risk highest for services that are financially attractive and complex to apply for. The uncomfortable finding is the mitigation tradeoff: friction like application fees does stop flooding, and it also prices out the people the service exists for.
↳ Follow the thread