On the Ptolemaic system’s accuracy when you add epicycles: due to geocentrism turning out to be incorrect, the apparently high accuracy vanishes when you look from a vantage point not on Earth
You can build a different , arbitrarily complex, system for a vantage point other than the Earth. Since geocentricism is wrong , it can’t be any worse.
Looking is still the ultimate arbiter between the different models.
Is it? Don’t we use simplicity as a criterion , as well? How about conscillience? Does into are arbiter mean only arbiter? Is empirical correctness necessary or sufficient?
First: to be clear, I think we’re both in agreement that the trilemma is real, and empirical observation can’t resolve the fundamental problem of wanting to be absolutely certain of anything, yes? That empirical correctness is importantly not sufficient for that?
Second: I think you misunderstood what I meant by a vantage point other than Earth. Of course you can make such a model that works from the moon, and one that works from Saturn, and so on. I’m not sure you can build a model that does that from all vantage points (as opposed to being custom-designed for one in particular) without also being, in some deep sense, isomorphic the the relevant parts of reality in the same way that our current model of the solar system is. If you can, that seems like a pretty important epistemological result, and I’d like to learn more! I suppose you could create an arbitrarily large lookup table that specifies what you’ll see from everywhere at every time, but to do that you still need to know how to generate that table, and the generator (I would argue) captures the relevant parts of the structure of our own model.
But within the class of relevantly isomorphic models, yes, you have a choice of which to use for what purpose, and when and how to switch among them. When you talk about simplicity being a criterion, usefulness is one of the reasons we do that. Another is that simplicity generally means fewer assumptions and implications liable to be proven wrong by future observation. It’s great, though, to know which less simple models exist that capture current observations, in order to be able to revisit them when new data needs explaining.
You can build a different , arbitrarily complex, system for a vantage point other than the Earth. Since geocentricism is wrong , it can’t be any worse.
Is it? Don’t we use simplicity as a criterion , as well? How about conscillience? Does into are arbiter mean only arbiter? Is empirical correctness necessary or sufficient?
What you and @Ape in the coat are saying is mostly just vague.
First: to be clear, I think we’re both in agreement that the trilemma is real, and empirical observation can’t resolve the fundamental problem of wanting to be absolutely certain of anything, yes? That empirical correctness is importantly not sufficient for that?
Second: I think you misunderstood what I meant by a vantage point other than Earth. Of course you can make such a model that works from the moon, and one that works from Saturn, and so on. I’m not sure you can build a model that does that from all vantage points (as opposed to being custom-designed for one in particular) without also being, in some deep sense, isomorphic the the relevant parts of reality in the same way that our current model of the solar system is. If you can, that seems like a pretty important epistemological result, and I’d like to learn more! I suppose you could create an arbitrarily large lookup table that specifies what you’ll see from everywhere at every time, but to do that you still need to know how to generate that table, and the generator (I would argue) captures the relevant parts of the structure of our own model.
But within the class of relevantly isomorphic models, yes, you have a choice of which to use for what purpose, and when and how to switch among them. When you talk about simplicity being a criterion, usefulness is one of the reasons we do that. Another is that simplicity generally means fewer assumptions and implications liable to be proven wrong by future observation. It’s great, though, to know which less simple models exist that capture current observations, in order to be able to revisit them when new data needs explaining.