Fabernautics
Humans produce things
Serial Justice
Why
For communities who need to manage common goods, to provide settlements and to agree on many other things, getting everybody to vote on everything all the time doesn't scale well.
Similarly to a branch on a tree which grows progressively, some issues might grow in importance and some not. Maybe nobody wishes to spend more time on a question after a few votes, or maybe some members want to be sure the outcome is final to accept it.
Human intelligence is a ressource which should not be over-harvested for decisions to be made with knowledge and embeddedness.
It is also important to make sure that decisions are taken responsibily, because they are one of the common goods of the community.
What
Serial Justice is a consensus mechanism which lives on blockchains. It is designed for Ostrom-like communities and requires a clear definition of membership.
It quantifies justice and distributes it equally among the community members.
It solves the scalability issue by getting people to vote one after the other only as much as needed ...
... by the community members for which the answer matters.
... to get a statistically meaningful answer.
Voting less often enables having a better knowledge of each issue while producing deliberation (transindividuation and new human knowledge) .
Since the deliberation is public, the justification of a vote counts as a contribution for which the members have a responsibility.
How it works
A democratic token called Justice Token is periodically minted and all the community members are given the same amount.
Whenever "justice" (or more generally, "answers") is needed by any member, he can spend one Justice Token on a given question. This will request a randomly selected member to provide his answer to the question as a vote.
This process can repeat until there are enough votes to provide a statistically meaningful answer, at which point the answer can be considered to be effective.
Examples
Serial Justice x AI
We show how Serial Justice can be used together with AI to produce common understanding on air travel carbon footprint.
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