Not all explanations are causal. The explanation literature in the philosophy of science goes pretty far back, but here are some of the highlights:
The Deductive Nomological Model (Hempel and Oppenheim, 1948) tries to explain a phenomenon using a deductive argument where the premises include particular facts and a general lawlike statement (like a law of nature) and the conclusion is the thing to be explained.[1]
The Statistical Relevance Model (Wesley Salmon) attempts to fix some shortcomings in the DN model that allowed explanations using particular facts and general laws that were not at all relevant to the phenomenon being explained. The idea is that you can explain why X hasn't become pregnant by saying that X has taken birth control, and people who take birth control do not become pregnant, and that would fit the DN model, but this explanation is not statistically relevant if X is male.[2]
Unificationist accounts (Philip Kitcher) seek to unify scientific explanations under a common umbrella as was done with, e.g. electromagnetism. If it is possible to have a unified theory of something, each element becomes more explainable based on its position within that unified theory [3]
pragmatic and psychological accounts tend to fit more closely with the kinds of rationalizations that we've seen as some explanations of AI. They can be fictional, but they don't have to be [4]
IMO we don't currently have an adequate account of explanation within the philosophy of science that works for deep neural networks. This is what my dissertation research focuses on.
Benjamin is a fascinating figure in the history of philosophy. He had a lot of interesting things to say about fascism and history. Probably the most vivid expression of his understanding of history can be found in his 9th thesis on history [1]
>"A Klee painting named ‘Angelus Novus’ shows an angel looking as though he is about to move away from something he is fixedly contemplating. His eyes are staring, his mouth is open, his wings are spread. This is how one pictures the angel of history. His face is turned toward the past. Where we perceive a chain of events, he sees one single catastrophe which keeps piling wreckage and hurls it in front of his feet. The angel would like to stay, awaken the dead, and make whole what has been smashed. But a storm is blowing in from Paradise; it has got caught in his wings with such a violence that the angel can no longer close them. The storm irresistibly propels him into the future to which his back is turned, while the pile of debris before him grows skyward. This storm is what we call progress."
The list includes The Will to Power as the first entry under Nietzsche. On this basis I'd have to question the degree to which this list was curated at all as this work wasn't actually written by Nietzsche, but rather edited together by his sister whose motives may have been suspect.
The Deductive Nomological Model (Hempel and Oppenheim, 1948) tries to explain a phenomenon using a deductive argument where the premises include particular facts and a general lawlike statement (like a law of nature) and the conclusion is the thing to be explained.[1]
The Statistical Relevance Model (Wesley Salmon) attempts to fix some shortcomings in the DN model that allowed explanations using particular facts and general laws that were not at all relevant to the phenomenon being explained. The idea is that you can explain why X hasn't become pregnant by saying that X has taken birth control, and people who take birth control do not become pregnant, and that would fit the DN model, but this explanation is not statistically relevant if X is male.[2]
Unificationist accounts (Philip Kitcher) seek to unify scientific explanations under a common umbrella as was done with, e.g. electromagnetism. If it is possible to have a unified theory of something, each element becomes more explainable based on its position within that unified theory [3]
pragmatic and psychological accounts tend to fit more closely with the kinds of rationalizations that we've seen as some explanations of AI. They can be fictional, but they don't have to be [4]
IMO we don't currently have an adequate account of explanation within the philosophy of science that works for deep neural networks. This is what my dissertation research focuses on.
[1] https://en.wikipedia.org/wiki/Deductive-nomological_model
[2] https://plato.stanford.edu/entries/scientific-explanation/#S...
[3] https://plato.stanford.edu/entries/scientific-explanation/#U...
[4] https://plato.stanford.edu/entries/scientific-explanation/#P...