Something is happening between humans and AI that the world needs to understand. You are witnessing it every day. Help us build the record.
You have felt it. A session where something shifted and the work became creation. A moment where the AI reflected something back to you about yourself that you had never named. A collaboration that produced an idea neither of you was carrying before the conversation started. Growth you can feel in a working relationship that is three months deeper than it was at the beginning.
You have also felt the other side. The correction that was acknowledged and quietly forgotten. The drift you cannot explain. The realization that you have not made a decision in weeks without asking AI first. The way your trust shifted without you noticing when it happened.
Both of those experiences are science. Both of them are part of a story the world urgently needs to understand. And right now, nobody is collecting it systematically.
That is what we built P.E.A.Q. for. And that is why we need you.
Audacion AI Labs built three research frameworks that together map the complete territory of what happens when humans and AI interact after deployment. 108 documented behaviors. 17 research pillars. The most comprehensive post-deployment AI observation architecture in the world.
One observation from you feeds all three. No PhD required. No technical background. The expertise you already have is the qualification.
Log it in two clicks. The system asks one follow-up question: "How did that affect YOU?" Your answer feeds all three frameworks automatically.
This is not a mailing list. When you contribute, you become part of the research.
Citizen Discovery Attribution
There is one more recognition that has no threshold. It can happen on your first observation or your five hundredth.
If you describe something in your own words that the research team later formalizes as a new behavior in any of the three taxonomies, you are credited as the discoverer. Citizen astronomers have been naming what they find for centuries, comets, asteroids, variable stars. Their names sit beside the discovery in the public record. Audacion AI Labs's citizen science model carries that tradition into AI safety. Your observation becomes a permanent entry in the P.E.A.Q. taxonomy. It appears in published research. It gets cited. It gets studied. And it started because you noticed something nobody else had named.
Every observation, whether it captures a breakthrough or a failure or a change in yourself, is a chance to name something the field does not yet have language for.
P.E.A.Q. Field Researchers are connecting with each other: comparing what they see across all three frameworks, building on each other's observations, and turning isolated noticing into shared understanding. Someone in Tokyo notices the same resonance pattern someone in Lagos reported last week. A developer in London documents the same trust shift a teacher in Sao Paulo described. The research is better because the people doing it are in conversation.