October 19, 2026
Getting the same AI answer twice is not verification.
You ask AI to summarize a supplier dispute before a negotiation. It says the supplier missed the delivery deadline. You ask again. Same answer.
That can feel like confirmation. But if the model missed the email that extended the deadline, the repeated answer is still wrong.
Consistency and accuracy are different questions.
Consistency: Does the model give the same response when you repeat the request?
Accuracy: Does that response match the actual records?
Research has shown that AI outputs can vary based on how requests are processed, and that common evaluation methods reward confident guesses over honest uncertainty. Repeatability under controlled conditions does not prove the answer is correct.
For anyone preparing a negotiation or dispute, the practical rule is simple: treat the AI summary as an organizing tool, not evidence. Check the claims that could change your position against the original contracts, emails, and records.
Matching answers are not independent confirmation. An inaccurate summary can lock in a position before anyone examines the assumption underneath it.
Sources
Thinking Machines Lab, “Defeating Nondeterminism in LLM Inference,” September 10, 2025. thinkingmachines.ai
Kalai, Nachum, Vempala, Zhang and colleagues, “Evaluating large language models for accuracy incentivizes hallucinations,” Nature 653(8116):1047–1051, April 22, 2026. nature.com
For a longer treatment of the same two findings, see Neither One Is a Malfunction.
Ariadne Latorre is a Florida Supreme Court certified mediator and a software engineer. She mediates business and commercial, insurance and risk allocation, LegalTech and information governance, HOA and community, and court-ordered matters, in English and Spanish, in Miami and virtually worldwide.