Systems Thinking with AI

Each chapter's own model, made interactive: change one or two values at a time and watch the behavior over time respond.

Every example in these readers is a constructed teaching example built from the chapter's own numbers. Chapters 36 to 39 start from published public records; their fitted values are inferred from those records, and nothing here is a forecast.

Part I

Why systems surprise us

Part II

From a messy problem to a dynamic hypothesis

Part III

The formal machinery

Part IV

Models as software

Part V

The AI roles

Part VI

Cases, calibration, and capstone

Notebooks on GitHub

Every chapter has a Jupyter notebook that reproduces its models and figures.

github.com/KarpelesPublishing/systems-thinking-with-ai