I have noticed that a lot of people are reluctant to talk about causation, on LessWrong and elsewhere ever since Hume (who was confused on the matter). Even in statistics, where causal analysis is nowadays a large field, time was when you couldn’t talk about causation in statistical papers, and had to disguise causal analysis as the “missing data problem”. Neither Causal Decision Theory nor Evidential Decision Theory work as naturalised decision theories, yet the former is criticised more harshly for failing on Newcomb’s Problem than the latter is for failing on the Smoking Lesion. People readily think that they do not do anything, merely observe what they have done, and do not act to bring things about, but merely predict that the things will happen.
I’m very confused by this comment because LW and AF post talk about causation all the time. They’re definitely a place where I expect causal and causation to appear in 90% of the posts I read, more than once.
I have noticed that a lot of people are reluctant to talk about causation, on LessWrong and elsewhere ever since Hume
I am having trouble understanding what you mean, since I see causation talked about a lot here. But I also think it’s funny how Hume wrote about causation in 1748, and you’re worried that people still haven’t gotten over it.
My aside about Hume referred to the passage where he gives two different definitions of causation in consecutive sentences, yet asserts them to be equivalent:
we may define a cause to be an object, followed by another, and where all the objects similar to the first are followed by objects similar to the second. Or in other words where, if the first object had not been, the second never had existed.
The first of these is the idea of constant conjunction, or as we would now call it, correlation, and the second is the idea of a counterfactual statement. Many have remarked on this contradiction.
I don’t think this works. There are many cases where the gears-level model is causal and the policy level is not, but it’s not the same distinction, and there are cases where they come apart.
E.g., suppose someone claims to have proven P ≠ NP. You can have a policy-level take on this, say “Scott Aarenson think it’s correct therefore I believe it”, or a gears-level model, e.g., “I’ve read the proof and it seems solid”. But neither of them is causal. It doesn’t even make sense to talk about causality for mathematical facts.
Both of these would be clearer if replaced by “causal”. That is what they are both talking about: causes and effects.
I have noticed that a lot of people are reluctant to talk about causation, on LessWrong and elsewhere ever since Hume (who was confused on the matter). Even in statistics, where causal analysis is nowadays a large field, time was when you couldn’t talk about causation in statistical papers, and had to disguise causal analysis as the “missing data problem”. Neither Causal Decision Theory nor Evidential Decision Theory work as naturalised decision theories, yet the former is criticised more harshly for failing on Newcomb’s Problem than the latter is for failing on the Smoking Lesion. People readily think that they do not do anything, merely observe what they have done, and do not act to bring things about, but merely predict that the things will happen.
If I ask myself, “What sort of person would see the world that way?” the answer I get is “Someone who experiences themselves that way.”
I’m very confused by this comment because LW and AF post talk about causation all the time. They’re definitely a place where I expect causal and causation to appear in 90% of the posts I read, more than once.
Talk of causation happens, but talk avoiding causation also happens, for example the EDT and action-as-prediction ideas that I mentioned.
I am having trouble understanding what you mean, since I see causation talked about a lot here. But I also think it’s funny how Hume wrote about causation in 1748, and you’re worried that people still haven’t gotten over it.
My aside about Hume referred to the passage where he gives two different definitions of causation in consecutive sentences, yet asserts them to be equivalent:
“Enquiry Concerning Human Understanding”, V,2,60. Emphasis in the original.
The first of these is the idea of constant conjunction, or as we would now call it, correlation, and the second is the idea of a counterfactual statement. Many have remarked on this contradiction.
I dunno, I just used “gears” about a totally acausal (but still logical) relationship yesterday.
I don’t think this works. There are many cases where the gears-level model is causal and the policy level is not, but it’s not the same distinction, and there are cases where they come apart.
E.g., suppose someone claims to have proven P ≠ NP. You can have a policy-level take on this, say “Scott Aarenson think it’s correct therefore I believe it”, or a gears-level model, e.g., “I’ve read the proof and it seems solid”. But neither of them is causal. It doesn’t even make sense to talk about causality for mathematical facts.
Yes, I’ll grant that “causal” doesn’t fit so well for mathematics. Yet even in mathematics, people still talk in terms of “why” and “because”.