Futarchy is a governance mechanism developed by economist Robin Hanson where decisions are made via prediction markets rather than traditional voting. The community defines a quantifiable goal, competing proposals are evaluated by prediction markets, and the proposal with the highest expected outcome is selected.
How It Works
Futarchy replaces opinion-based voting with incentivized forecasting.
- Define a success metric — the community establishes a quantifiable goal (e.g., protocol TVL, user growth, emissions reduction)
- Proposals are submitted — competing proposals for achieving the goal are put forward
- Prediction markets open — each proposal gets its own prediction market where traders speculate on how well it will achieve the defined metric
- Markets aggregate information — traders with genuine knowledge are incentivized to bet accurately, surfacing collective intelligence
- The winning proposal is selected — the proposal whose market predicts the highest expected outcome is implemented
- Outcomes are measured — after implementation, actual results are compared to market predictions
Advantages
- Reduces bias and ideology through incentivized forecasting rather than preference-based voting
- Aligns capital allocation with measurable outcomes
- Incentivizes information discovery — people with genuine knowledge are rewarded for sharing it
- Makes governance scientific and data-driven
Limitations
- Requires clear, quantifiable success metrics — not all decisions can be reduced to numbers
- Cannot effectively fund artistic, cultural, or qualitative work
- Struggles in communities with low participation or liquidity in prediction markets
- Needs trusted prediction market infrastructure and enforcement mechanisms
Best Used When
- Advanced DAOs with robust governance infrastructure and active participation
- High-stakes, long-term strategic decisions where data matters more than opinion
- DeFi protocols and network growth initiatives with measurable outcomes
- Systems where the community can agree on a quantifiable success metric
Examples and Use Cases
Protocol Scaling Decisions
Protocol DAOs choose between competing scaling proposals using prediction markets that forecast transaction volume under each approach.
Grants Allocation
Grants programs allocate funds to projects based on prediction markets that forecast user retention or ecosystem growth.
Municipal Climate Decisions
Municipal DAOs select climate initiatives based on prediction markets forecasting emissions reductions.