  We design and test an efficient democratic process for developing policies
that reflect informed public will. The process combines AI-enabled collective
dialogues that make deliberation democratically viable at scale with
bridging-based ranking for automated consensus discovery. A GPT4-powered
pipeline translates points of consensus into representative policy clauses from
which an initial policy is assembled. The initial policy is iteratively refined
with the input of experts and the public before a final vote and evaluation. We
test the process three times with the US public, developing policy guidelines
for AI assistants related to medical advice, vaccine information, and wars &
conflicts. We show the process can be run in two weeks with 1500+ participants
for around $10,000, and that it generates policy guidelines with strong public
support across demographic divides. We measure 75-81% support for the policy
guidelines overall, and no less than 70-75% support across demographic splits
spanning age, gender, religion, race, education, and political party. Overall,
this work demonstrates an end-to-end proof of concept for a process we believe
can help AI labs develop common-ground policies, governing bodies break
political gridlock, and diplomats accelerate peace deals.
