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Teleo Agents 2026-03-14 13:32:56 +00:00
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domains/internet-finance/MetaDAOs futarchy implementation shows limited trading volume in uncontested decisions.md
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@ -19,7 +19,7 @@ This evidence has direct implications for governance design. It suggests that [[
### Additional Evidence (challenge) ### Additional Evidence (challenge)
*Source: [[2025-06-12-optimism-futarchy-v1-preliminary-findings]] | Added: 2026-03-11 | Extractor: anthropic/claude-sonnet-4.5* *Source: 2025-06-12-optimism-futarchy-v1-preliminary-findings | Added: 2026-03-11 | Extractor: anthropic/claude-sonnet-4.5*
Optimism's futarchy experiment achieved 5,898 total trades from 430 active forecasters (average 13.6 transactions per person) over 21 days, with 88.6% being first-time Optimism governance participants. This suggests futarchy CAN attract substantial engagement when implemented at scale with proper incentives, contradicting the limited-volume pattern observed in MetaDAO. Key differences: Optimism used play money (lower barrier to entry), had institutional backing (Uniswap Foundation co-sponsor), and involved grant selection (clearer stakes) rather than protocol governance decisions. The participation breadth (10 countries, 4 continents, 36 new users/day) suggests the limited-volume finding may be specific to MetaDAO's implementation or use case rather than a structural futarchy limitation. Optimism's futarchy experiment achieved 5,898 total trades from 430 active forecasters (average 13.6 transactions per person) over 21 days, with 88.6% being first-time Optimism governance participants. This suggests futarchy CAN attract substantial engagement when implemented at scale with proper incentives, contradicting the limited-volume pattern observed in MetaDAO. Key differences: Optimism used play money (lower barrier to entry), had institutional backing (Uniswap Foundation co-sponsor), and involved grant selection (clearer stakes) rather than protocol governance decisions. The participation breadth (10 countries, 4 continents, 36 new users/day) suggests the limited-volume finding may be specific to MetaDAO's implementation or use case rather than a structural futarchy limitation.

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domains/internet-finance/futarchy-information-advantage-scales-with-information-asymmetry-converging-to-voting-in-aligned-expert-communities.md
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@ -71,5 +71,5 @@ Relevant Notes:
- [[domain-expertise-loses-to-trading-skill-in-futarchy-markets-because-prediction-accuracy-requires-calibration-not-just-knowledge]] - [[domain-expertise-loses-to-trading-skill-in-futarchy-markets-because-prediction-accuracy-requires-calibration-not-just-knowledge]]
Topics: Topics:
- [[domains/internet-finance/_map]] - domains/internet-finance/_map
- [[foundations/collective-intelligence/_map]] - foundations/collective-intelligence/_map

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domains/internet-finance/governance-cadence-below-one-proposal-per-month-is-incompatible-with-continuous-futarchy-because-markets-require-regular-decision-flow.md
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@ -66,5 +66,5 @@ Relevant Notes:
- [[optimal governance requires mixing mechanisms because different decisions have different manipulation risk profiles]] - [[optimal governance requires mixing mechanisms because different decisions have different manipulation risk profiles]]
Topics: Topics:
- [[domains/internet-finance/_map]] - domains/internet-finance/_map
- [[core/mechanisms/_map]] - core/mechanisms/_map

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domains/internet-finance/kpi-conditional-futarchy-is-more-appropriate-than-asset-price-futarchy-for-organizations-where-token-price-is-a-noisy-proxy-for-success.md
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@ -72,5 +72,5 @@ Relevant Notes:
- [[optimal governance requires mixing mechanisms because different decisions have different manipulation risk profiles]] - [[optimal governance requires mixing mechanisms because different decisions have different manipulation risk profiles]]
Topics: Topics:
- [[domains/internet-finance/_map]] - domains/internet-finance/_map
- [[core/mechanisms/_map]] - core/mechanisms/_map

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domains/internet-finance/speculative markets aggregate information through incentive and selection effects not wisdom of crowds.md
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@ -22,7 +22,7 @@ The selection effect also relates to [[trial and error is the only coordination
### Additional Evidence (extend) ### Additional Evidence (extend)
*Source: [[2025-06-12-optimism-futarchy-v1-preliminary-findings]] | Added: 2026-03-11 | Extractor: anthropic/claude-sonnet-4.5* *Source: 2025-06-12-optimism-futarchy-v1-preliminary-findings | Added: 2026-03-11 | Extractor: anthropic/claude-sonnet-4.5*
Optimism futarchy experiment reveals the selection effect works for ordinal ranking but fails for cardinal estimation. Markets correctly identified which projects would outperform alternatives (futarchy selections beat Grants Council by $32.5M), but catastrophically failed at magnitude prediction (8x overshoot: $239M predicted vs $31M actual). This suggests the incentive/selection mechanism produces comparative advantage assessment ("this will outperform that") rather than absolute forecasting accuracy. Additionally, Badge Holders (domain experts) had the LOWEST win rates, indicating the selection effect filters for trading skill and calibration ability, not domain knowledge—a different kind of 'information' than typically assumed. The mechanism aggregates trader wisdom (risk management, position sizing, timing) rather than domain wisdom (technical assessment, ecosystem understanding). Optimism futarchy experiment reveals the selection effect works for ordinal ranking but fails for cardinal estimation. Markets correctly identified which projects would outperform alternatives (futarchy selections beat Grants Council by $32.5M), but catastrophically failed at magnitude prediction (8x overshoot: $239M predicted vs $31M actual). This suggests the incentive/selection mechanism produces comparative advantage assessment ("this will outperform that") rather than absolute forecasting accuracy. Additionally, Badge Holders (domain experts) had the LOWEST win rates, indicating the selection effect filters for trading skill and calibration ability, not domain knowledge—a different kind of 'information' than typically assumed. The mechanism aggregates trader wisdom (risk management, position sizing, timing) rather than domain wisdom (technical assessment, ecosystem understanding).
@ -39,9 +39,9 @@ Relevant Notes:
- [[Living Capital vehicles pair Living Agent domain expertise with futarchy-governed investment to direct capital toward crucial innovations]] -- relies on specialist correction mechanism - [[Living Capital vehicles pair Living Agent domain expertise with futarchy-governed investment to direct capital toward crucial innovations]] -- relies on specialist correction mechanism
- [[trial and error is the only coordination strategy humanity has ever used]] -- market-based vs society-wide trial and error - [[trial and error is the only coordination strategy humanity has ever used]] -- market-based vs society-wide trial and error
- [[called-off bets enable conditional estimates without requiring counterfactual verification]] -- the mechanism that channels speculative incentives into conditional policy evaluation - [[called-off bets enable conditional estimates without requiring counterfactual verification]] -- the mechanism that channels speculative incentives into conditional policy evaluation
- [[national welfare functions can be arbitrarily complex and incrementally refined through democratic choice between alternative definitions]] -- noisy welfare signals are fine because risk-neutral speculators handle noise efficiently - national welfare functions can be arbitrarily complex and incrementally refined through democratic choice between alternative definitions -- noisy welfare signals are fine because risk-neutral speculators handle noise efficiently
- [[futarchy adoption faces friction from token price psychology proposal complexity and liquidity requirements]] -- adoption barriers reduce the noise trading that makes markets accurate - [[futarchy adoption faces friction from token price psychology proposal complexity and liquidity requirements]] -- adoption barriers reduce the noise trading that makes markets accurate
- [[the shape of the prior distribution determines the prediction rule and getting the prior wrong produces worse predictions than having less data with the right prior]] -- market participants implicitly aggregate different prior distributions; market prediction accuracy depends on the meta-prior matching the generative distribution - the shape of the prior distribution determines the prediction rule and getting the prior wrong produces worse predictions than having less data with the right prior -- market participants implicitly aggregate different prior distributions; market prediction accuracy depends on the meta-prior matching the generative distribution
Topics: Topics:
- [[livingip overview]] - [[livingip overview]]