The scientific induction starter pack.pic.twitter.com/N1Hm1W3tpq
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The scientific induction starter pack.pic.twitter.com/N1Hm1W3tpq
The Raven Paradox: under most theories of scientific induction, observing a purple eggplant (a non-black non-raven) is evidence that all ravens are black. Most/all attempted solutions depend on random object sampling, which seems impossible. https://en.wikipedia.org/wiki/Raven_paradox …pic.twitter.com/p5waFK5VHg
But is that an example of scientific induction though? It doesn’t abstract to an underlying causal system. It’s merely a predictor based on past data.
This is controversial within the philosophy of science. Most theories say that good scientific theories are predictive. “Causality” is pretty much impossible to define. Working scientists are likely to have a different view! But they can’t define causality either.
Either you have a statistical model, or you have a model of some internal mechanisms that cause the phenomenon (with perhaps some statistical models at deeper levels). Both are predictive, but with only one can we know what cannot happen.
I think this is right. However, there’s no worked-out version of what a mechanistic model means, in general, so far as I know. This is definitely a problem for the philosophy of science. It think it’s probably also a problem for scientific practice, but that’s less clear!
The problem you point to was one aspect of the problem most prominently solved by Karl Popper. @DavidDeutschOxf is fine on this topic but if we set aside his writings there are still many other elaborations of the remedy.
I’ve read several versions of Popperism and found them unconvincing. Fwiw
(I have not read much of Popper’s own work, however, and my mind is still open on this)
I was sure you had looked at it some. My experience is that the only sound presentations come from advocates. DD is among those but by no means alone.
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