This book is about how humans can deeply understand natural and man-made systems. It details a formal methodology that can be used to gain deep understanding of any system.
Shallow understanding involves building abstract models that can be used to predict future behavior. Simple versions of these models rely on observing the historical statistical correlations between variables in a system. They don’t tell us anything about causal relations between variables.
For example, we can look at historical data to see that when interest rates in the U.S. economy are high, inflation tends to be higher. When interest rates are low, inflation tends to be lower.
https://farmdocdaily.illinois.edu/2022/10/update-on-us-interest-rates-and-inflation.html#:~:text=The annual average Federal Funds,3.3%25).
https://files.stlouisfed.org/files/htdocs/publications/review/98/11/9811wd.pdf
We can use this data to build a model that predicts inflation based on interest rate levels. The model may do a decent job, but it won’t be perfect and we won’t understand why the relationship exists.
More advanced models can be built based on the inferred relationships between the microstates and macrostates of a system.
We can predict the weather by: