You're looking at Less Wrong's discussion board. This includes all posts, including those that haven't been promoted to the front page yet. For more information, see About Less Wrong.

TheAncientGeek comments on In praise of gullibility? - Less Wrong Discussion

23 Post author: ahbwramc 18 June 2015 04:52AM

You are viewing a comment permalink. View the original post to see all comments and the full post content.

Article Navigation

Comments (106)

Comments (106)

You are viewing a single comment's thread. Show more comments above.

Comment author: Vaniver 18 June 2015 04:59:59PM 1 point [-]

What's that got to do with causal structure?

I am not sure what you mean by "causal structure" in this context. I was attempting to provide some intuition as to why ordinary weather forecasting and climate change modeling would be different, since you stated that you didn't see what the essential difference between them is.

But it was a short comment, and so many things were only left as implications. For example, the cell update laws (i.e. the differential equations guiding the system) will naturally be different for weather forecasting and climate forecasting because the cells are physically different beasts. You'll model cloud dynamics very differently depending on whether or not clouds are bigger or smaller than a model cell, and it's not necessarily the case that a fine-grained model will be more accurate than a coarse-grained model, for many reasons.

Comment author: TheAncientGeek 19 June 2015 10:15:23AM -1 points [-]

Understanding causal structure seems to be something that is kind of shiny and impressive sounding, connotationally, but doesn't mean much, at least not much that is new, denotationally. And it comes up because I thought was replying to DVH, who brought it up.

I don't think CC modelling and weather forecasting are all that essentially different, or at least not as different as Causal Structure is supposed to be from either.

The pattern "the experts in X are actually incompetent fools, because they are not doing Y" is frequent in LessWrong Classic, even if it hasn't been applied to climate change before.

Comment author: IlyaShpitser 19 June 2015 11:29:47AM 2 points [-]

I think one reasonable complaint is that you should not use predictive models to guide policy because of the usual issues with confounding.

Comment author: TheAncientGeek 19 June 2015 02:40:54PM -1 points [-]

Unguided policy is better?

Comment author: IlyaShpitser 19 June 2015 03:12:09PM *  2 points [-]

No? What do you think my position is?

Model bias is not a joke. If your model is severely biased, it is giving you garbage. I am not sure in what sense a model that outputs garbage is better than no model at all. The former just gives you a false sense of confidence, because math was used.

If you think there are [reasons] where the model isn't completely garbage, or we can put bounds on garbage, or something, then that is a useful conversation to have.

If you set up the conversation where it's the garbage model or no science at all, then you are engaged in rhetoric, not science.

Comment author: Lumifer 19 June 2015 04:00:47PM 0 points [-]

If you set up the conversation where it's the garbage model or no science at all

If you don't want to talk in binary black-or-white terms, perhaps you shouldn't lead with a set-up where a model outputs either truth or garbage ;-)

Comment author: TheAncientGeek 19 June 2015 05:19:35PM *  0 points [-]

I don't suppose public policy is based on a single model.

If you read back, nothing has been said about any specific model, so no such claim needs defending.

If you read back, it has been suggested that there is a much better way of doing climate .science than modelling of any kind....but details are lacking.

Comment author: IlyaShpitser 19 June 2015 05:28:18PM *  2 points [-]

If I read back I also read things like this:

Understanding causal structure seems to be something that is kind of shiny and impressive sounding, connotationally, but doesn't mean much

No, it means a whole lot. You need to get the causal structure right, or at least reasonably close, or your model is garbage for policy. See also: "irrational policy of managing the news."

I fight this fight, along with my colleagues, in much simpler settings than weather. And it is still difficult.

Comment author: Lumifer 19 June 2015 05:44:48PM 3 points [-]

You need to get the causal structure right, or at least reasonably close, or your model is garbage for policy.

Related. Sample:

The whole “normative sociology” concept has its origins in a joke that Robert Nozick made, in Anarchy, State and Utopia, where he claimed, in an offhand way, that “Normative sociology, the study of what the causes of problems ought to be, greatly fascinates us all”(247). Despite the casual manner in which he made the remark, the observation is an astute one. Often when we study social problems, there is an almost irresistible temptation to study what we would like the cause of those problems to be (for whatever reason), to the neglect of the actual causes. When this goes uncorrected, you can get the phenomenon of “politically correct” explanations for various social problems – where there’s no hard evidence that A actually causes B, but where people, for one reason or another, think that A ought to be the explanation for B. This can lead to a situation in which denying that A is the cause of B becomes morally stigmatized, and so people affirm the connection primarily because they feel obliged to, not because they’ve been persuaded by any evidence.

Comment author: TheAncientGeek 19 June 2015 05:37:32PM 0 points [-]

Getting causal structure right in that sense is not an alternative to modelling, it is part of getting modelling right.

Powered by Reddit Powered by Reddit