Paper Type
ERF
Abstract
This paper proposes an LLM-assisted framework scaling citizen engagement while preserving democratic legitimacy. Unlike existing platforms focused on clustering, it provides drafting support and summarisation via human-in-the-loop architecture with modular microservices and guardrails. A proof-of-concept on real participatory budgeting data shows LLMs transform informal inputs into compliant proposals and actionable summaries (nvidia-qwen3-80B: FS=0.92, zero hallucinations). Results position LLMs as accountable civic infrastructure enhancing e-inclusion and reducing administrative burden, a key for e-democracy scalability.
Paper Number
1366
Recommended Citation
Domingues, Miguel; Neto, Marco; Guerra, Carla; Pacheco, Emanuel; and Cordeiro, Luis, "Supporting Scalable e-Participation through LLM-Assisted Proposal Writing and Summarisation" (2026). AMCIS 2026 Proceedings. 5.
https://aisel.aisnet.org/amcis2026/egov/sig_egov/5
Supporting Scalable e-Participation through LLM-Assisted Proposal Writing and Summarisation
This paper proposes an LLM-assisted framework scaling citizen engagement while preserving democratic legitimacy. Unlike existing platforms focused on clustering, it provides drafting support and summarisation via human-in-the-loop architecture with modular microservices and guardrails. A proof-of-concept on real participatory budgeting data shows LLMs transform informal inputs into compliant proposals and actionable summaries (nvidia-qwen3-80B: FS=0.92, zero hallucinations). Results position LLMs as accountable civic infrastructure enhancing e-inclusion and reducing administrative burden, a key for e-democracy scalability.
Comments
SIG E-GOV