Keywords: epistemology, machine learning, vibration effects, model realism, pre-paradigmatic science
TL;DR: Science needs statistical reasoning based more on model predictions and less brittle to modeling ingredients
Abstract: Science has progressed by reasoning on what models could not predict because they were missing important ingredients. And yet without correct models, standard statistical methods for scientific evidence are not sound. Here I argue that machine-learning methodology provides solutions to ground reasoning about empirically evidence more on models’ predictions, and less on their ingredients.
Track: Original Research Track