Be a Greek, not a Babylonian

There current obsession is with black-box models with increasing performance.

Judea Pearl compares this to ancient Babylonian astronomy:

…the Babylonian astronomers were masters of black-box predictions, far surpassing their Greek rivals in accuracy and consistency of celestial observations. Yet science favored the creative-speculative strategy of the Greek astronomers, which was wild with metaphorical imagery: circular tubes full of fire, small holes through which celestial fire was visible as stars, and hemispherical Earth riding on turtleback. It was this wild modeling strategy, not Babylonian extrapolation, that jolted Eratosthenes (276-194 BC) to perform one of the most creative experiments in the ancient world and calculate the circumference of the Earth. Such an experiment would never have occurred to a Babylonian data-fitter.

Don’t be a Babylonian data-fitter. Be a Greek-style modeler.

Notes mentioning this note

Bayesian
A good way to explain Bayesian inference is as reversible simulations.
Data Science
[[Don’t make type 3 errors]]

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