I’ve just finished Matthew Crawford’s great book “Shop Class as Soulcraft,” tripped over a paragraph that I thought relevant to the struggles we’re having dealing with science entirely performed through modelling, and thought I’d share.
Some modern motorcycles have begun to include onboard, computerized self-diagnostic functions, just as cars do. But they haven’t eliminated the kind of judgment mechanics exercise. If we can understand why they haven’t, this will help illuminate further the limitations inherent in the idea of an “intellectual technology,” and the perversities that get laid upon work when those limitations aren’t heeded.
Car manufacturers are supposed to standardize their diagnostics under a protocol called OBD-II (for onboard diagnostics), but as any mechanic will tell you, sometimes the system gives the wrong trouble code. Being off by one digit might give a diagnosis of “System fuel too lean on bank one” (P0171), that is, an air-fuel mixture that is too much air and not enough fuel on the first bank of cylinders, when in fact the problem is “System fuel too rich on bank two” (P0172). An experienced mechanic can tell too lean from too rich by looking at the spark plugs; they will look blanched white in the first case and sooty in the second. Representing states of the world in a merely formal way, as “information” of the sort that can be coded, allows them to be entered into a logical syllogism of the sort that computerized diagnostics can solve. But this is to treat states of the world in isolation from the context in which their meaning arises, so such representations are especially liable to nonsense. To rely entirely on computer diagnostics would put one in the situation of the schoolchild who learns to do square roots on a calculator without understanding the principle. If he commits a keying error while taking the square root of thirty-six and gets an answer of eighteen, it will not strike him that there is anything amiss. For the mechanic, the risk is that someone else committed a keying error.
Computerized diagnostics don’t so much replace the mechanic’s judgment as add another layer to the work, one that requires a different sort of cognitive disposition.
[emphasis added]
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Excellent book! (There’s also an analogy to the symbolic AI fallacy from the passage you quote.)
_to question the presumed value of the cubicle working world, deplore society’s disconnection from the material world and vividly convey the reward of working with one’s hands_
True, there is a scientific disconnection from the material world induced by the growth in the characteristics of computers. Modelling them is usually more inexpensive and less thorny than having to do those experiences in labs. More and more works are done on models, and in other branches of science, knowing this problem, the models are required to be validated.
However, in Global Warming models cannot be validated since there is no data. If you cannot validate your model that is not science, that is guessing, and a full field of creativeness is open then to reach whatever conclusion you wish.
The scientific checks and balances work quite well in other fields. The problem has been at least adquately managed in those fields, but cannot be in Global Warming.
Science also tells you when you cannot reach the Truth.
bq. Both sides of the Global warming debate are in their infancy, but the AWG side now holds the preponderance of evidence, whether that evidence eventually points to their conclusions is another issue…. The far greater amount of Donkey work has been done on that side. While the paucity of data on the other leaves it opened to being accused of not doing much more than carping.
That seems to depend on how you evaluate ‘evidence’. We now know that CRU discarded the data claimed to stand behind their HADCRUT ‘evidence’, and was unable to replicate the various modifications that had been made to the raw data in the past. We don’t yet know how many other climate models out there are ultimately depended on that ‘evidence’.
We “do know”:http://wattsupwiththat.com/2009/11/29/when-results-go-bad/ just how the CRU team treated those who went and did some donkey work and came up with results at variance with theirs: denial. And it now turns out that some of the skeptic’s complaints about including stations with ‘urban heat island’ effects in the IPCC base data were absolutely correct – see the actual station list, which had to be extracted by a FOIA request, in the same post.
I started this whole affair not convinced of _catastrophic_ AGW, but finding the AGW argument itself credible, given the known effects of CO2 and our obvious increase in its production. Having now seen the dog’s breakfast that lurks behind the models and nifty graphs, I’m back to ‘not proven’ on the latter. Too many of the skeptics’ charges are proving out, in part or whole.
Hand waving isn’t going to save this one. The AGW research process is discredited, even Monbiot agrees. Right now attempts to enforce stringent public policies based on AGW theory are going to taken as no more than naked force, as they ought, and may be resisted as such. The only way to repair legitimacy is to put everything – the raw data, the intermediate products, the models – out in the open and have the AGW priesthood stand down.
Toc3, those theories may be as mathematically elegant as elegant are the models proposed for Global Warming, but they all need to be proven, as happened to the “General Theory of Relativity”:http://www.knowledgerush.com/kr/encyclopedia/Perihelium_shift_of_the_planet_Mercury/.
Of course, if you move toward pure maths, then you´ll finally reach a point where you don’t need an experimental process anymore. There are also “deductive” theories, which find a mathematical relation to overwhelming existing observations (such as the Restricted Theory of Relativity). Evidently no further experimental processes are needed then.
Anyways, it is not the case for warmologists, who are threatening us with direct physical effects if we don’t follow them.
Maybe we should call it the Theory of Global Warming, that would be far more scientific.