Editing Openai/692f308e-2d40-8006-9e6e-c3d36639678c (section)

===== Given known data (2025 benchmarks), we assume an average current hallucination rate h=0.15h = 0.15h=0.15, error rate p=0.30p = 0.30p=0.30, and recurrence r=0.12r = 0.12r=0.12. =====
The collective correction (multi-model cross-response) reduces total systemic error according to:

Pc=(p×r)/n=(0.30×0.12)/10=0.0036P_c = (p \times r) / n = (0.30 \times 0.12) / 10 = 0.0036Pc=(p×r)/n=(0.30×0.12)/10=0.0036
Thus, the Median Theoretical Probability of Collective Error (MTPC) ≈ 0.36 %, indicating that when multiple AIs are cross-referenced, the chance that all produce the same incorrect answer is extremely low.

However, the Median Theoretical Probability of Individual Error (MTPI) remains ≈ 30 % for a single-instance query, and 12 % for a repeated query to the same model (assuming partial self-correction between iterations).