"So, from a Bayesian perspective, what Einstein did is still induction, and still covered by the notion of a simple prior (Occam prior) that gets updated by new evidence. It's just the prior was over the possible characters of physical law, and observing other physical laws let Einstein update his model of the character of physical law, which he then used to predict a particular law of gravitation. If you didn't have the concept of a "character of physical law", what Einstein did would look like magic—plucking the correct model of gravitation out of the space of all possible equations, with vastly insufficient evidence. But Einstein, by looking at other laws, cut down the space of possibilities for the next law. He learned the alphabet in which physics was written, constraints to govern his answer. Not magic, but reasoning on a higher level, across a wider domain, than what a naive reasoner might conceive to be the "model space" of only this one law. So from a probability-theoretic standpoint, Einstein was still data-driven—he just used the data he already had, more effectively. Compared to any alternate Earths that demanded huge quantities of additional data from astronomical observations and clocks on airplanes to hit them over the head with General Relativity."