This is usefully true in many ways, and pretty much completely true for a lot of things that we think of as technical methods (e.g. finite element analysis, or calculus of variations, or functional programming), so the claim seems to be true as it is intended to be understood. But it seems to me that there is an important exception to the claim as it is actually written.

The old ideas of Occam’s Razor and falsifiability are fuzzy enough that they are maybe not technical methods. The new information theoretic and statistical systematizations of those ideas (notably http://en.wikipedia.org/wiki/Minimum_description_length), however, certainly ought to qualify for “technical method” as Chapman wrote the phrase, even if his internal mental state was more narrowly specifically referring to methods like finite element analysis. Also some of the ideas coming in from (mostly) the microeconomics community are methods which are at least borderline technical, where if your idea is really meaningful and you sincerely believe in it, presumably you’d welcome a chance to bet on it or otherwise “put your money where your mouth is” in systems like hanson.gmu.edu/ideafutures.html , right?

Chapman seems to mean “before applying any technical method to construct a specific understanding of the universe…”; the methods like minimum description length that I have in mind are about determining whether your constructed understanding of the universe is any good. Borderline technical methods like idea futures are also playing in the same space.

Once one understands enough math that the puzzle about information theory is “why did it take so long for people to figure this out?” rather than “ow! ow! ow! what does this bafflegab mean?” then applying ideas like MDL to test things that are fondly imagined (by you and/or by others) to be meaningful truths about the world works rather well. And these technical methods slither around the requirement to “already have a pretty good idea” about the form of the answer, because their natural role is “I don’t know what the form will be, but I do know it will satisfy this criterion”. I don’t know what the form of the answer would be in answering macroeconomic questions about e.g. future unemployment rates, I just know if people had a strongly valid answer is, they would be able to pass MDL tests with it and make money betting on it. (That “strongly valid” weaseling is because all these criteria admit borderline cases where a pattern is completely correctly understood but reality happens to provide so few chances to test the pattern that any statistical signal is weak and ambiguous.)

So things like MDL and idea futures play a role similar to the Turing test: the test doesn’t tell you what the form of a general AI will be, it intentionally slithers around that question completely, instead giving you a sufficient condition for recognizing a general AI when you see it. (And incidentally the Turing test is arguably a technical method as the phrase was written, and if so suffices to falsify the claim as written.)