The “generative modeling”30 culture seeks to develop
stochastic models which fit the data, and then make inferences
about the data-generating mechanism based on the structure of
those models. Implicit in their viewpoint is the notion that there
is a true model generating the data, and often a truly “best” way
to analyze the data. Breiman thought that this culture encom
passed 98% of all academic statisticians.
The “predictive modeling” culture31 prioritizes prediction
and is estimated by Breiman to encompass 2% of academic
statisticians—including Breiman—but also many computer
scientists and, as the discussion of his article shows, important
industrial statisticians. Predictive modeling is effectively silent
about the underlying mechanism generating the data, and
allows for many different predictive algorithms, preferring to
discuss only accuracy of prediction made by different algorithm
on various datasets. The relatively recent discipline of machine
learning, often sitting within computer science departments,
is identified by Breiman as the epicenter of the predictive
modeling culture.
LLM prefers tool.