One of the main restraints on scientific practice is the seemingly uncongenial proposition that even if a theory, a method, or a model, are perfectly valid, to corroborate them one had better not use just about anything (GARBAGE) that comes to hand as input, because the output can be expected to be on a par with the input: GARBAGE.
This measure seems to have been adopted to guard against unsubstantiated claims, assertions, conjectures, and so on, about the performance of theories, methods, and models. The point is that very often the difficulties we face in the application of models/theories are due to the poor quality of the inputs. So the Garbage In Garbage Out (GIGO) maxim seems to have been “put in place” to serve as a gentle reminder that these difficulties cannot be overcome by … ignoring them, assuming that, somehow, the models/theories in question will yield “good” results even if the input is “poor”.
There are of course cases where the results may be “good” even though the input is “poor”. But the point is that the onus is on anyone making this claim, to prove unambiguously that this is indeed the case. In other words, the default assumption is that if the input is “poor”, so are the results based on this input. The following is an immediate implication of this fundamental maxim:
Results of an analysis are only as good as the estimates on which they are based.
This apparently universally accepted precept seems to explains why the task of dealing with severe uncertainty is generally considered to be such an onerous one.
And by the same token, it seems to explain the major advantage that voodoo theories have over scientific theories. The former are not required to submit to exacting maxims of this type.
In short, the difficulty facing scientific models is the requirement to accept this working assumption:
It would have certainly made life a lot easier had it been possible to contend that the output is … “reliable”.