A spherical earth model is useful and a flat earth model is not. Also, as Asimov explains here, wrong is relative and a spherical model of the earth is much less wrong than a flat earth model.
I'd highly recommend reading the article again a little more carefully.
Not if you're going to say the projection is flat. If the projection is flat, and the projection is the model, then I should be able to lay a flat ruler, appropriately scaled, between any two points on the flat map and read off the actual distance between those two points. But I can't do that; and the model knows I can't do that. The model tells me to take the coordinates on the map of two points and plug them into a complicated mathematical formula if I want to get the actual distance between them. So the model is not flat in the sense that matters--in the predictions it makes for distances between points.
Is a constant distance metric part of the definition of flat? Why don't the grid lines on the map count as an appropriately scaled ruler?
Yes. Otherwise "flat" would have no meaning; we can always make a flat map of any surface, if we are willing to allow the distance metric to be distorted to any extent we like, so every possible surface would be "flat".
So all models are wrong but some are indeed useful.
Darwins theory (and later modernizations) are indeed wrong (as in not true) but it's the most useful model we have.
Not true in what sense?
Sure, but that doesn't mean they don't match reality. It just means they don't match all of reality; they leave information out. Of course all of our models have to leave information out, I agree with that. But that's a separate question from the question of whether the information a given model includes matches the portion of reality it is intended to model--or, better, to how good an approximation a given model matches the portion of reality it is intended to model. That's the whole point of Asimov's essay.
Otherwise no model can be representing reality in any objective way they can per definition only be interpretations (The map is not the territory).
Reality don't care about true or false models. Reality has no evolution or planets or black holes. These are all interpretations at a very specific scale from a very specific perspective.
But models that allow us to make predictions does not mean that they match reality it just means that it matches the predictions we can interpret.
Thats a very different thing than reality.
I don't see what "interpretation" is involved in comparing a specific prediction with a specific measurement result. You're just comparing two numbers (with error bars, etc.). And the comparison doesn't care what kind of stuff you put in your model; that can be anything you like. All the comparison cares about is the numbers your model outputs as its predictions.
> models that allow us to make predictions does not mean that they match reality it just means that it matches the predictions we can interpret.
No, it means the model's predictions match the actual measurements we make.
> Thats a very different thing than reality.
Perhaps you are using a different definition of "reality" than I am. In which case I don't see how whatever definition you are using of "reality" is relevant to Asimov's article, which is what we are discussing.
In other words you cannot not interpret. It's not reality. In reality that measurement result doesn't exist.
You are interpreting the world through your very very very limited senses and only seeing it the way your senses allow you to see it.
This is very different from the world as it is.
You are talking about reality within the confines of what humans can interpret. I am talking about reality as it is in it's entirety without any specific vantage point.
Hmm, ok, so we are also giving a different meaning to the term "measurement result". I'm afraid our ontologies are too different to have a meaningful discussion.
Which is a more useful way of looking at it. Theories have a predictive horizon. The point of science is to increase the predictive horizon.
But the other side of that is the ability to create new classes of technology.
Electromagnetic theory, relativity and quantum theory are lot more than a tweak on the Newtonian world view. They make it possible to build completely new kinds of technology that are impossible if all you have is Newton.
Suggesting that everything is a process of gradual refinement to an increasing number of decimal places is a wrong theory about theories.
There's a lot more to science snd technology than the orbit of Mercury.
>Darwins theory (and later modernizations) are indeed wrong (as in not true) but it's the most useful model we have.
That may baffle people, but the problem with the Darwinian view is that it's based on the principle that species evolve - when in fact ecosystem evolve, in the sense that flows of chemicals, information, and energy self-organise into more or less stable configurations.
Species evolution is an interesting epiphenomenon on top of that. But assuming it's all there is to know about natural history is like trying to understand meteorology by classifying icebergs. You're going to catch some of the more obvious patterns, but more complex relationships are going to elude you.
Modelling ecosystems is a very useful skill - especially for long space flight - and it turns out we're still incredibly bad at it, precisely because naive Darwinism doesn't have the predictive horizon to deal with the problem in a useful way.
Without a good theory, systems tend to diverge into instability and everything dies, no matter how fast adaptation happens - which isn't usually the outcome you want.