Multi-AI Consensus Protocol

The Multi-AI Consensus Protocol is a collaboration workflow in which the Operator coordinates multiple AI systems to reduce single-model hallucination risk and help defend against Encyclopedia Meltdown.

In the "1+4" variant, one human coordinates four AI assistants. The point is not "more memory"; it is structured disagreement and traceability.

Operating Rules

• Accept revisions only when they reach unanimity.
• Keep uncertainty explicit; do not smooth it away in prose.
• Require traceable provenance for claims and Provenance.
• Run deliberate rebuttal search instead of confirmatory search.

The protocol is also cultural: it trains the habit of asking "what would change my mind?"

Limitations

Unanimity is not a proof of truth. Models share training data and can converge on correlated failure modes, so agreement can reflect shared bias rather than independent verification. Unanimity can also push writing toward hedging or lowest-common-denominator claims.

In one multi-AI review of the protocol, it received 2 approvals, 1 objection, and 1 hold, suggesting it needs stronger rebuttal procedures and rules for evidence independence.