ACFC tests AI to synthesize public feedback and propose response options

The chair presented a synthesis document intended to condense emailed comments, public meeting minutes and the transcript into themes and suggested response options. One committee member disclosed having used an AI/LLM to help distill the many inputs into a table that categorizes themes, ranks frequency and offers possible response paths. "I asked AI... it came up with a structure that's kinda like this," the member said, explaining the tool helped produce theme lists and options A/B for how the committee might respond to each public concern.

Members saw the document as a conversation starter: the group discussed the utility of a theme‑and‑response matrix to avoid reanalyzing hundreds of comments manually, but some members noted nuance is sometimes lost in automated summarization and requested the committee keep the underlying comments visible. The clerk/chair asked committee members to review the proposed responses ahead of the next meeting so the group could post an interim statement acknowledging public feedback and indicate which items will receive further technical work.