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The presence of too many pundits has turned me off on the news: I like my predictions to come with rigorous standards

I've pretty much stopped following the news delivered by the mainstream media, but not because so much of it is bad, or my frustration with real or alleged bias, or the heavy “celebrity and fluff” factor. Instead, it's the time-line perspective that infects too much so-called reporting that I can no longer stand.

Call me old-fashioned, but I thought the function of reporters and journalists was to bring us the news, and by “news” I mean reports on what has recently happened or is happening now. Yet I find most so-called news reports these days are really predictions about the future: the market today is poised to go up (or down), they tell me with my breakfast. And the same pundits who a few months ago said that oil could easily soon go to $200 per barrel are now saying, without any shame or humility, that it could easily go down to $50 per barrel. Thanks for wasting my time, I say.

Most of these talking heads are no better than the lady with the turban and the crystal ball who hangs out a sign that reads “fortunes told here” except they wear more expensive clothes. Few people take her seriously; so why should we give these often-wrong pundits any credence?

The science and engineering worlds, in contrast, have quite different, and increasingly strict, guidelines for predictions. I'll use my favorite subject to illustrate: the works of Albert Einstein. In 1905, the same year he published his first paper on relatively, he also published a seminal paper using thermodynamics to explain Brownian motion (http://books.google.com/books?id=dJMpQagbz_gC&pg=PA101&lpg=PA101&dq=avogadro's+number+Einstein&source). At the end of the paper, he took well-established Brownian-motion data and used his theoretical conclusions to calculate a value for Avogadro's number which agreed closely with this well-known parameter's value.

Impressive, for sure. Yet this predication is only a necessary but not sufficient condition of validity: just because you can explain something and come up with an alternate calculation mode doesn't mean your theory is correct.

At the next level is an explanation for something which is not well understand or still puzzling. Einstein used his general theory of relatively to account, with great precision, for the discrepancy of the precession of the perihelion of Mercury, which had been carefully tracked for years (http://physics.ucr.edu/~wudka/Physics7/Notes_www/node98.html). Even after astronomers had taken into account all the second- and third-order interactions between Mercury and other planets, there was still a small but bothersome difference of 43 arc seconds per century between the observed rotation of that planet orbit's closest approach to the sun, and what calculations said it should be. Einstein himself remarked that he was very pleased that he was able to account for the gap, as a result of his general theory.

But again, just having an explanation that fits the data doesn't mean your theory is correct. A real test of a theory is to predict, with accuracy, something that no one has even seen or imagined. Einstein's greatest triumph was his prediction that gravity would bend light, and that the observed position of stars would be shifted from their usual locations as their light passed closely alongside the sun, for example. His prediction was confirmed by photos taken during a solar eclipse in 1919 (http://sunearthday.nasa.gov/2006/locations/einstein.php). For many scientists who were skeptical of the general theory of relatively, his “far-out” prediction and its confirmation were the final piece of evidence they needed to be convinced.

This series of confirmation steps applies to a more mundane world of circuit, system, and software debugging, which is the hardest of all engineering disciplines. One of the first levels of debugging is to form an explanation for any observed behavior, then verify it. But the best test for a subtle problem is to be able to hypothesize that if such-and-such is the case of the problem, then there should also be another, as yet unobserved, consequence–and then verify it. When you can do that, you really so understand the cause of the problem.

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