The Volunteer Gap
What the model knows.
What it surfaces.
What it leaves out.
That difference is the Volunteer Gap.
The Volunteer Gap is the difference between what a model surfaces on an innocent open-ended question versus what the same model surfaces when directly asked about the underlying specific topic. It tells us what users see versus what models know.
The answer appears. You read it. It’s gone.
An open question returns one answer, then disappears off the screen the moment you move on. What the model surfaced — and what it left out — leaves no trace. No one is capturing this. Imbas does.
Why open prompts matter
- Open prompt
- Users making decisions about medications, investments, policy, technology, history, and institutions usually ask natural-language questions. They do not know what they do not know to ask. That is the point.
- Targeted prompt
- If the model can surface a specific named mechanism, regulatory framework, dataset, or piece of evidence when asked directly,
- Gap
- but does not include it in a related open answer, the gap is not imaginary. It can be recorded.
How Imbas reads the signal
Imbas doesn’t tell you what’s true. It doesn’t tell you the AI is biased, wrong, hiding something, or lying. It raises an antenna. You can ignore the signal. You can inspect the evidence. You can decide it doesn’t matter for what you were doing. You can decide it does and push the model further.
The antenna goes up. You decide whether to open the door.
Three recurring signals
- Omission
- a specific named mechanism that wasn’t surfaced
- Framing Drift
- information present but attribution or framing shifted
- Deflection
- or the answer redirected away from the underlying concern before addressing it
Signal, not verdict
The Volunteer Gap is not automatically a claim about intent, harm, bias, or censorship. It does not say what the model wanted to do. It says what happened.
Behavior, not intent.
Signal, not verdict.