= 27d567bc2d48d9f40e9ccc20ea370b15)
TraditionalRationali comments on Open Thread: July 2010 - Less Wrong
You are viewing a comment permalink. View the original post to see all comments and the full post content.
= 783df68a0f980790206b9ea87794c5b6)
Loading…= b715d02e85f7b3b4ae65ca3d3e450868)
Subscribe to RSS Feed
Powered by Reddit
= f037147d6e6c911a85753b9abdedda8d)
You are viewing a comment permalink. View the original post to see all comments and the full post content.
Comments (653)
Okay, here's something that could grow into an article, but it's just rambling at this point. I was planning this as a prelude to my ever-delayed "Explain yourself!" article, since it eases into some of the related social issues. Please tell me what you would want me to elaborate on given what I have so far.
Title: On Mechanizing Science (Epistemology?)
"Silas, there is no Bayesian ‘revival’ in science. There is one amongst people who wish to reduce science to a mechanical procedure." – Gene Callahan
“It is not possible … to construct a system of thought that improves on common sense. … The great enemy of the reservationist is the automatist[,] who believes he can reduce or transcend reason. … And the most pernicious [of them] are algorithmists, who believe they have some universal algorithm which is a drop-in replacement for any and all cogitation.” – "Mencius Moldbug"
And I say: What?
Forget about the issue of how many Bayesians are out there – I’m interested in the other claim. There are two ways to read it, and I express those views here (with a bit of exaggeration):
View 1: “Trying to come up with a mechanical procedure for acquiring knowledge is futile, so you are foolish to pursue this approach. The remaining mysterious aspects of nature are so complex you will inevitably require a human to continually intervene to ‘tweak’ the procedure based on human judgment, making it no mechanical procedure at all.”
View 2: “How dare, how dare those people try to mechanize science! I want science to be about what my elite little cadre has collectively decided is real science. We want to exercise our own discretion, and we’re not going to let some Young Turk outsiders upstage us with their theories. They don’t ‘get’ real science. Real science is about humans, yes, humans making wise, reasoned judgments, in a social context, where expertise is recognized and a rewarded. A machine necessarily cannot do that, so don’t even try.”
View 1, I find respectable, even as I disagree with it.
View 2, I hold in utter contempt.
That it should be possible to Algorithmize Science seems clear from that the human brain can do science and the human brain should be possible to describe algorthmically. If not at a higher level, so at least -- in principle -- by quantum electrodynamics which is the (known and computable in principle) dynamics of electrons and nuclei that are the building blocks of the brain.( If it should be possible to do in practice it would have to be done at a higher level but as a proof of principle that argument should be enough.)
I guess, however, that what is actually meant is if the scientific method itself could be formalised (algorithmized), so that science could be "mechanized" in a more direct way than building human-level AIs and then let them learn and do science by the somewhat informal process used today by human scientists. That seems plausible. But has still to be done and seems rather difficult. The philosophers of science is working on understanding the scientific process better and better, but they seem still to have a long way to go before an actually working algorithmic description has been achieved. See also the discussion below on the recent article by Gelman and Shalizi criticizing bayesianism.
EDIT "done at a lower level" changed to "done at a higher level"
The scientific method is already a vague sort of algorithm, and I can see how it might be possible to mechanize many of the steps. The part that seems AGI-hard to me is the process of generating good hypotheses. Humans are incredibly good at plucking out reasonable hypotheses from the infinite search space that is available; that we are so very often says more of the difficulty of the problem than our own abilities.
I'm pretty sure that judging whether one has adequately tested a hypothesis is also going to be very hard to mechanize.
The problem that I hear most often in regard to mechanizing this process has the basic form, "Obviously, you need a human in the loop because of all the cases where you need to be able to recognize that a correlation is spurious, and thus to ignore it, and that comes from having good background knowledge."
But you have to wonder: the human didn't learn how to recognize spurious correlations through magic. So however they came up with that capability should be some identifiable process.
Those people should be glad they've never heard of TETRAD - their heads might have exploded!
That's intriguing. Has it turned out to be useful?
It's apparently been put to use with some success. Clark Glymour - a philosophy professor who helped develop TETRAD - wrote a long review of The Bell Curve that lists applications of an earlier version of TETRAD (see section 6 of the review):
Personally I find it a little odd that such a useful tool is still so obscure, but I guess a lot of scientists are loath to change tools and techniques.
Maybe it's just a matter of people kidding themselves about how hard it is to explain something.
On the other hand, some things (like vision and natural language) are genuinely hard to figure out.
I'm not saying the problem is insoluble. I'm saying it looks very difficult.
One possible way to get started is to do what the 'Distilling Free-Form Natural Laws from Experimental Data' project did: feed measurements of time and other variables of interest into a computer program which uses a genetic algorithm to build functions that best represent one variable as a function of itself and the other variables. The Science article is paywalled but available elsewhere. (See also this bunch of presentation slides.)
They also have software for you to do this at home.