Paper: Characterizing Agentic Flooding of Government Services
RexDouglass · x · 2026-08-26
The paper "Characterizing Agentic Flooding of Government Services" analyzes surges in demand caused by AI agents interacting with government systems.
Key Findings:
- Based on 84 potential cases, "agentic flooding" is likely widespread due to the low cost of LLM-generated text.
- Risk Matrix: Services that are financially attractive but complex (e.g., benefit applications) are most exposed.
- Responses: While governments may deploy friction-inducing measures (e.g., fees), these often trade off equitable access. The paper recommends alternative mitigation strategies.
Context: Accepted by AAAI AIES 2026.
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