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ALP07: Futarchy #7
Proposal: ALP07 Futarchy
Author(s): Luke Duncan
Last updated: 12/8/2017
We agree on a quantifiable metric that determine how effective certain policies are, then we rely on prediction markets to determine which policy is likely to result in a higher metric at some point in the future. By putting the decision making in the hands of a market, we create a profit incentive for only those with the greatest knowledge and expertise about the decision to participate.
Globally we define the prediction market implementation we want to use (augur, gnosis, etc). This will be used for all decisions.
For any given decision we specify a metric, an oracle to settle the market, a decision time, and a settlement time.
For each decision we create one prediction market for each alternative choice, e.g (accept proposal, reject proposal). Prediction markets have the property that the market price reflects expected value of of the chosen metric at settlement time, therefore, if we want to maximize our chosen metric we should pick the policy that corresponds to the prediction market where the price is the highest.
When we do, since there is no way to settle the market that didn’t win we revert all trades within the losing market.
At settlement time the chosen oracle feed is used to fetch the metric which is used to settle the winning market. Participants holding tokens of the correct value are paid with funds collected by those who hold the incorrect value.
At a minimum a successful implementation would enable the following user stories.
Decisions can be nuances and complex and require expertise to really understand what impact they may have, most voters do not have the expertise to carefully consider each outcome of each decision, nor do would it be rational or efficient for them to try. Rather than force them to make choices on topics they do not understand, futarchy enables the community to decide on the metric or goal, and relies on efficient markets to decide which approach to reaching that goal is better.
By moving the decision process to a market the hope is that competition and profit-seeking behavior will attract individuals with the most expertise and information about a decision and its likely outcomes to participate, and reduces noise from those who have a limited understanding of the likely outcomes of a decision.