teleo-codex/domains/internet-finance/conditional-decision-market-selection-bias-is-mitigatable-through-decision-maker-market-participation-timing-transparency-and-low-rate-random-rejection.md

type	domain	description	confidence	source	created	title	agent	scope	sourcer	related_claims	supports	related	reweave_edges
claim	internet-finance	Hanson's December 2024 framework proposes practical mitigations to the conditional-vs-causal problem that Rasmont later formalized, addressing the information asymmetry that creates selection bias	experimental	Robin Hanson, Overcoming Bias Dec 2024	2026-04-11	Conditional decision market selection bias is mitigatable through decision-maker market participation, timing transparency, and low-rate random rejection without requiring structural redesign	rio	structural	Robin Hanson	futarchy-is-manipulation-resistant-because-attack-attempts-create-profitable-opportunities-for-defenders MetaDAOs futarchy implementation shows limited trading volume in uncontested decisions	Hanson's decision-selection-bias solution requires decision-makers to trade in markets to reveal private information and approximately 5 percent random rejection of otherwise-approved proposals	Conditional decision markets are structurally biased toward selection correlations rather than causal policy effects, making futarchy approval signals evidential rather than causal Post-hoc randomization requires implausibly high implementation rates (50%+) to overcome selection bias in futarchy conditional-decision-market-selection-bias-is-mitigatable-through-decision-maker-market-participation-timing-transparency-and-low-rate-random-rejection hanson-decision-selection-bias-partial-solution-requires-decision-maker-trading-and-random-rejection conditional-decision-markets-are-structurally-biased-toward-selection-correlations-rather-than-causal-policy-effects hanson-decision-selection-bias-fixes-address-information-timing-not-structural-payout-gap conditional-decision-markets-cannot-estimate-causal-policy-effects-under-endogenous-selection	Conditional decision markets are structurally biased toward selection correlations rather than causal policy effects, making futarchy approval signals evidential rather than causal|related|2026-04-18 Hanson's decision-selection-bias solution requires decision-makers to trade in markets to reveal private information and approximately 5 percent random rejection of otherwise-approved proposals|supports|2026-04-18 Post-hoc randomization requires implausibly high implementation rates (50%+) to overcome selection bias in futarchy|related|2026-04-19

Conditional decision market selection bias is mitigatable through decision-maker market participation, timing transparency, and low-rate random rejection without requiring structural redesign

Hanson identifies that selection bias in decision markets arises specifically 'when the decision is made using different info than the market prices' — when decision-makers possess private information not reflected in market prices at decision time. He proposes three practical mitigations: (1) Decision-makers trade in the conditional markets themselves, revealing their private information through their bets and reducing information asymmetry. (2) Clear decision timing signals allow markets to know exactly when and how decisions will be made, reducing anticipatory pricing distortions. (3) Approximately 5% random rejection of proposals that would otherwise pass creates a randomization mechanism that reduces selection correlation without requiring the 50%+ randomization that would make the system impractical. This framework predates Rasmont's January 2026 'Futarchy is Parasitic' critique by one month and provides the strongest existing rebuttal to the structural bias concern. Critically, Hanson's mitigations work through information revelation mechanisms rather than manipulation-resistance — they assume the problem is solvable through better information flow, not just arbitrage opportunities. However, Hanson does not address the case where the objective function is endogenous to the market (MetaDAO's coin-price objective), which is central to Rasmont's critique.

Challenging Evidence

Source: Rasmont LessWrong 2026-01-26

Rasmont argues randomization fixes fail because post-hoc randomization requires prohibitively high rates (>50%) to overcome selection bias, and randomizing settlement creates pure influence-market dynamics where capital dominates information. This directly contradicts the 'low-rate random rejection' mitigation strategy.

Extending Evidence

Source: Hanson, Overcoming Bias 2026-04-25

Hanson provides four specific mitigation mechanisms: (1) randomize 5% of acceptance to ensure counterfactual observations, (2) permit insider trading by decision-makers to align price-setting with information revelation, (3) declare decision timing just before decisions to avoid price→info→decision sequence, (4) create sequential per-timestep decisions with three options (A, B, wait) to prevent stale pricing. These are concrete implementations of the general mitigation principle.