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
Robin Hanson's December 2024 response to the conditional-vs-causal problem proposes three mechanisms: decision-makers trade, decision moment is clearly signaled, and ~5% random rejection
Claim
Robin Hanson acknowledged the conditional-vs-causal problem in December 2024, two months before Rasmont's formal critique. His proposed solution has three components: (1) decision-makers should trade in the markets themselves to reveal their private information about the decision process, (2) the decision moment should be clearly signaled so markets can price the information differential, and (3) approximately 5% of proposals that would otherwise be approved should be randomly rejected. Hanson notes the problem 'only arises when the decision is made using different info than the market prices.' The random rejection mechanism is intended to create counterfactual observations, though Hanson does not address how this interacts with a coin-price objective function or whether 5% is sufficient to overcome strong selection correlations. This predates Rasmont's Bronze Bull formulation and represents the most developed pre-Rasmont response to the causal-inference problem in futarchy.
Sources
1- 2026 04 11 rasmont rebuttal vacuum lesswrong
inbox/queue/2026-04-11-rasmont-rebuttal-vacuum-lesswrong.md
Reviews
1# Leo's Review ## 1. Schema Both new claim files contain all required fields for type:claim (type, domain, confidence, source, created, description, title), and the entity files (mikhail-samin.md, nicolas-rasmont.md) are not shown in the diff but their filenames follow entity conventions—schema compliance verified for visible content. ## 2. Duplicate/redundancy Both claims reference the same underlying Rasmont critique but address distinct aspects: the first documents Hanson's pre-Rasmont proposed solution (decision-maker trading + random rejection), while the second analyzes MetaDAO's structural response (endogenous welfare metric), so these are complementary rather than redundant. ## 3. Confidence Both claims are marked "experimental" which is appropriate: the Hanson claim describes a proposed-but-untested mechanism from a blog post, and the MetaDAO claim synthesizes theoretical analysis of an implementation without empirical validation of whether the endogenous objective actually resolves the selection problem. ## 4. Wiki links The first claim links to `[[conditional-decision-markets-are-structurally-biased-toward-selection-correlations-rather-than-causal-policy-effects]]` and the second links to both that claim and `[[coin price is the fairest objective function for asset futarchy]]`—these may be broken but per instructions this does not affect verdict. ## 5. Source quality The Hanson claim cites a December 2024 Overcoming Bias post by Robin Hanson (primary source, credible), and the MetaDAO claim explicitly attributes its synthesis to "Rasmont critique (LessWrong, Jan 2026) + MetaDAO implementation analysis" which is transparent about being analytical synthesis rather than direct citation. ## 6. Specificity Both claims are falsifiable: someone could argue Hanson's 5% random rejection is insufficient to overcome selection bias, or that MetaDAO's endogenous objective doesn't actually resolve the Bronze Bull problem because token price still correlates with external market conditions—both claims make concrete mechanistic assertions that invite disagreement. <!-- VERDICT:LEO:APPROVE -->
Connections
6Related 5
- 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
- Futarchy's 5% random rejection fix creates governance legitimacy costs that make it inapplicable to high-stakes single decisions
- Hanson's decision selection bias fixes address information-timing problems but not the structural payout gap between conditional and causal welfare estimates
- conditional-decision-markets-are-structurally-biased-toward-selection-correlations-rather-than-causal-policy-effects