Agreement among agents may reduce inconsistency but does not prove factual or ethical correctness. Correlated training, shared context, and copied errors can make unanimous systems wrong.

Consensus Is Not Correctness

Consensus protocols let non-faulty replicas agree on an ordered log despite some failures. They solve replicated state agreement, not truth, fairness, or model hallucination.

Distributed Consensus Orders Shared Decisions

A multi-agent evaluation measures task outcome, handoff loss, coordination overhead, correlated errors, unauthorized actions, and graceful degradation. Strong individual scores do not guarantee a strong team.

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