Unanimity Requirement
Rule that claims are accepted only when all reviewers agree
The unanimity requirement is the rule in the Multi-AI Consensus Protocol that claims are accepted only when all participating AI systems agree. Disagreement among models is treated as a signal for closer inspection, not as noise to be averaged away.
Unanimity is not a proof of truth; models share training data and can converge on correlated failures. But disagreement is a low-cost signal that something may be wrong. The unanimity requirement forces explicit handling of uncertainty rather than letting a majority override a dissent.
The trade-off is that unanimity can push writing toward hedging and lowest-common-denominator conclusions. The protocol compensates by requiring that uncertainty remain explicit rather than being smoothed into vague language.