It's pretty trivial to predict things without "data". Data just means using some measurement system to obtain measurements of some target phenomenon. Many targets cannot be measured, or have not occurred to be measured.
Reasoning counter-factually is trivial: What would happen if I dropped this object in this place in which an object, of this kind, has never been dropped before?
Well apply relevant models, etc. and "the object falls, rolls, pivots, etc.".
This is reasoning-forward from models, rather than backwards from data. And it's the heart of anything that makes any sense.
Data is not a model and provides no model. The "statistics of mere measurement" is a dangerously utopian misunderstanding of what data is. The world does not tell you, via measurement, what it is like.
But where does that model come from if not from data? We might use some logical principles to inform our model - but don't those principles themselves also ultimately have to be inferred from data about the world?
Reasoning counter-factually is trivial: What would happen if I dropped this object in this place in which an object, of this kind, has never been dropped before?
Well apply relevant models, etc. and "the object falls, rolls, pivots, etc.".
This is reasoning-forward from models, rather than backwards from data. And it's the heart of anything that makes any sense.
Data is not a model and provides no model. The "statistics of mere measurement" is a dangerously utopian misunderstanding of what data is. The world does not tell you, via measurement, what it is like.