Condition OS: A Thinking Framework Based on Conditions, Probabilities, and Intervention
Condition OS is a general thinking framework designed to shift the starting point of analysis from observed outcomes to the conditions that make those outcomes possible and affect their probabilities. Rather than treating success, failure, behavior, or rare events as self-explanatory, the framework encourages users to identify relevant conditions, map their interactions, estimate their influence, intervene on modifiable conditions, and update the model as new information becomes available. Condition OS is not presented as a new scientific theory. It integrates and simplifies ideas related to probabilistic causation, causal models, configurational causation, optimization, sequential decision-making, and systems thinking into a practical reasoning process intended to be usable across disciplines and everyday decision-making. The central process is: Observe → Decompose → Structure → Estimate → Intervene → Update. This record contains the English version of the document. AI-assisted writing and document preparation are transparently disclosed within the paper.
Authors
- Naori Kurata
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-09-14
- DOI
- https://doi.org/10.5281/zenodo.22740203
- Primary Topic
- Bayesian Modeling and Causal Inference
- Type
- preprint