Thursday, October 15, 2015

Quickies: The Pitfalls Of Science As Conducted By Humans

     What Gentle Reader is unaware of the monumental fraud that has been perpetrated on the world in the name of saving us from “global warming?” As bad as it’s been – and as threatening to freedom and prosperity as the endorsements of world governments have made it – it’s a chapter in an ongoing story: the story of how for centuries, scientific method has been subtly and often unintentionally distorted to support the cognitive biases of researchers.

     This morning, Judith Curry cites an excellent article on the enveloping problem and some potential solutions. A brief taste:

     This is the big problem in science that no one is talking about: even an honest person is a master of self-deception. Our brains evolved long ago on the African savannah, where jumping to plausible conclusions about the location of ripe fruit or the presence of a predator was a matter of survival. But a smart strategy for evading lions does not necessarily translate well to a modern laboratory, where tenure may be riding on the analysis of terabytes of multidimensional data. In today’s environment, our talent for jumping to conclusions makes it all too easy to find false patterns in randomness, to ignore alternative explanations for a result or to accept ‘reasonable’ outcomes without question — that is, to ceaselessly lead ourselves astray without realizing it.

     “People forget that when we talk about the scientific method, we don’t mean a finished product,” says Saul Perlmutter, an astrophysicist at the University of California, Berkeley. “Science is an ongoing race between our inventing ways to fool ourselves, and our inventing ways to avoid fooling ourselves.” So researchers are trying a variety of creative ways to debias data analysis — strategies that involve collaborating with academic rivals, getting papers accepted before the study has even been started and working with strategically faked data.

     If you’re at all interested in scientific method, its virtues and its limitations, and the intellectual foundations of the sciences, this is a must-read. It reminds me powerfully of a snippet from the late Sir Fred Hoyle’s SF novel The Black Cloud:

    "It looks to me as if those perturbations of the rockets must have been deliberately engineered," began Weichart.
    "Why do you say that, Dave?" asked Marlowe.
    "Well, the probability of three cities being hit by a hundred-odd rockets moving at random is obviously very small. therefore I conclude that the rockets were not perturbed at random. I think they must have been deliberately guided to give direct hits."
    "There's something of an objection to that," argued McNeil. "If the rockets were deliberately guided, how is it that only three of 'em found their targets?"
    "Maybe only three were guided, or maybe the guiding wasn't all that good. I wouldn't know."
    There was a derisive laugh from Alexandrov.
    "Bloody argument," he asserted.
    "What d'you mean, 'bloody' argument?"
    "Invent bloody argument, like this. Golfer hits ball. Ball lands on tuft of grass -- so. Probability ball landed on tuft very small, very very small. Million other tufts for ball to land on. Probability very small, very, very very small. So golfer did not hit ball, ball deliberately guided onto tuft. Is bloody argument, yes? Like Weichart's argument....Must say what damn target is before shoot, not after shoot. Put shirt on before, not after event."

     Even a very good, completely honest scientist can find what he wants to find rather than what’s actually present in the data.

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