Dynamic Conversational Science (DCS): A Framework for Human–AI Co-Discovery
Dynamic Conversational Science (DCS) is a methodological framework that formalizes human–AI interaction as a unified cognitive system for scientific inquiry.
Rather than treating AI as a tool or oracle, DCS models discovery as an iterative conversational loop in which probabilistic generation (AI) is constrained by memory, intention, and temporal coherence (human).
Within the Oxygen States project, this work functions as the methodological backbone that enables all subsequent structural hypotheses, stress tests, and falsification protocols.
The framework defines its own scope, limitations, and failure modes, and is presented explicitly as reproducible and auditable rather than outcome-guaranteeing
This document serves as the first formal registration of DCS as a generalizable method for real-time conceptual discovery in open scientific networks.
Full methodological details, constraints, and reproducibility notes are provided in the Zenodo record.
